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Montes-Herrera JC, Cimoli E, Cummings VJ, D'Archino R, Nelson WA, Lucieer A, Lucieer V. Quantifying pigment content in crustose coralline algae using hyperspectral imaging: A case study with Tethysphytum antarcticum (Ross Sea, Antarctica). J Phycol 2024. [PMID: 38558363 DOI: 10.1111/jpy.13449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 02/29/2024] [Accepted: 03/01/2024] [Indexed: 04/04/2024]
Abstract
Crustose coralline algae (CCA) are a highly diverse group of habitat-forming, calcifying red macroalgae (Rhodophyta) with unique adaptations to diverse irradiance regimes. A distinctive CCA phenotype adaptation, which allows them to maximize photosynthetic performance in low light, is their content of a specific group of light-harvesting pigments called phycobilins. In this study, we assessed the potential of noninvasive hyperspectral imaging (HSI) in the visible spectrum (400-800 nm) to describe the phenotypic variability in phycobilin content of an Antarctic coralline, Tethysphytum antarcticum (Hapalidiales), from two distinct locations. We validated our measurements with pigment extractions and spectrophotometry analysis, in addition to DNA barcoding using the psbA marker. Targeted spectral indices were developed and correlated with phycobilin content using linear mixed models (R2 = 0.64-0.7). Once applied to the HSI, the models revealed the distinct phycoerythrin spatial distribution in the two site-specific CCA phenotypes, with thin and thick crusts, respectively. This study advances the capabilities of hyperspectral imaging as a tool to quantitatively study CCA pigmentation in relation to their phenotypic plasticity, which can be applied in laboratory studies and potentially in situ surveys using underwater hyperspectral imaging systems.
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Affiliation(s)
- Juan C Montes-Herrera
- Institute for Marine and Antarctic Studies, College of Sciences and Engineering, University of Tasmania, Hobart, Tasmania, Australia
| | - Emiliano Cimoli
- Institute for Marine and Antarctic Studies, College of Sciences and Engineering, University of Tasmania, Hobart, Tasmania, Australia
| | - Vonda J Cummings
- National Institute of Water and Atmospheric Research, Wellington, New Zealand
| | - Roberta D'Archino
- National Institute of Water and Atmospheric Research, Wellington, New Zealand
| | - Wendy A Nelson
- National Institute of Water and Atmospheric Research, Wellington, New Zealand
- Tāmaki Paenga Hira Auckland Museum & School of Biological Sciences, University of Auckland, Auckland, New Zealand
| | - Arko Lucieer
- School of Geography, Planning, and Spatial Sciences, College of Sciences and Engineering, University of Tasmania, Hobart, Tasmania, Australia
| | - Vanessa Lucieer
- Institute for Marine and Antarctic Studies, College of Sciences and Engineering, University of Tasmania, Hobart, Tasmania, Australia
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2
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Galvan FER, Pavlick R, Trolley G, Aggarwal S, Sousa D, Starr C, Forrestel E, Bolton S, Alsina MDM, Dokoozlian N, Gold KM. Scalable Early Detection of Grapevine Viral Infection with Airborne Imaging Spectroscopy. Phytopathology 2023; 113:1439-1446. [PMID: 37097472 DOI: 10.1094/phyto-01-23-0030-r] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
The U.S. wine and grape industry loses $3B annually due to viral diseases including grapevine leafroll-associated virus complex 3 (GLRaV-3). Current detection methods are labor-intensive and expensive. GLRaV-3 has a latent period in which the vines are infected but do not display visible symptoms, making it an ideal model to evaluate the scalability of imaging spectroscopy-based disease detection. The NASA Airborne Visible and Infrared Imaging Spectrometer Next Generation was deployed to detect GLRaV-3 in Cabernet Sauvignon grapevines in Lodi, CA in September 2020. Foliage was removed from the vines as part of mechanical harvest soon after image acquisition. In September of both 2020 and 2021, industry collaborators scouted 317 hectares on a vine-by-vine basis for visible viral symptoms and collected a subset for molecular confirmation testing. Symptomatic grapevines identified in 2021 were assumed to have been latently infected at the time of image acquisition. Random forest models were trained on a spectroscopic signal of noninfected and GLRaV-3 infected grapevines balanced with synthetic minority oversampling of noninfected and GLRaV-3 infected grapevines. The models were able to differentiate between noninfected and GLRaV-3 infected vines both pre- and postsymptomatically at 1 to 5 m resolution. The best-performing models had 87% accuracy distinguishing between noninfected and asymptomatic vines, and 85% accuracy distinguishing between noninfected and asymptomatic + symptomatic vines. The importance of nonvisible wavelengths suggests that this capacity is driven by disease-induced changes to plant physiology. The results lay a foundation for using the forthcoming hyperspectral satellite Surface Biology and Geology for regional disease monitoring in grapevine and other crop species. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.
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Affiliation(s)
| | - Ryan Pavlick
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109
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3
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Price J, Sousa D, Sousa FJ. Effect of Spatial and Spectral Scaling on Joint Characterization of the Spectral Mixture Residual: Comparative Analysis of AVIRIS and WorldView-3 SWIR for Geologic Mapping in Anza-Borrego Desert State Park. Sensors (Basel) 2023; 23:6742. [PMID: 37571526 PMCID: PMC10422361 DOI: 10.3390/s23156742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 07/24/2023] [Accepted: 07/26/2023] [Indexed: 08/13/2023]
Abstract
A geologic map is both a visual depiction of the lithologies and structures occurring at the Earth's surface and a representation of a conceptual model for the geologic history in a region. The work needed to capture such multifaced information in an accurate geologic map is time consuming. Remote sensing can complement traditional primary field observations, geochemistry, chronometry, and subsurface geophysical data in providing useful information to assist with the geologic mapping process. Two novel sources of remote sensing data are particularly relevant for geologic mapping applications: decameter-resolution imaging spectroscopy (spectroscopic imaging) and meter-resolution multispectral shortwave infrared (SWIR) imaging. Decameter spectroscopic imagery can capture important mineral absorptions but is frequently unable to spatially resolve important geologic features. Meter-resolution multispectral SWIR images are better able to resolve fine spatial features but offer reduced spectral information. Such disparate but complementary datasets can be challenging to integrate into the geologic mapping process. Here, we conduct a comparative analysis of spatial and spectral scaling for two such datasets: one Airborne Visible/Infrared Imaging Spectrometer-Classic (AVIRIS-classic) flightline, and one WorldView-3 (WV3) scene, for a geologically complex landscape in Anza-Borrego Desert State Park, California. To do so, we use a two-stage framework that synthesizes recent advances in the spectral mixture residual and joint characterization. The mixture residual uses the wavelength-explicit misfit of a linear spectral mixture model to capture low variance spectral signals. Joint characterization utilizes nonlinear dimensionality reduction (manifold learning) to visualize spectral feature space topology and identify clusters of statistically similar spectra. For this study area, the spectral mixture residual clearly reveals greater spectral dimensionality in AVIRIS than WorldView (99% of variance in 39 versus 5 residual dimensions). Additionally, joint characterization shows more complex spectral feature space topology for AVIRIS than WorldView, revealing information useful to the geologic mapping process in the form of mineralogical variability both within and among mapped geologic units. These results illustrate the potential of recent and planned imaging spectroscopy missions to complement high-resolution multispectral imagery-along with field and lab observations-in planning, collecting, and interpreting the results from geologic field work.
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Affiliation(s)
- Jeffrey Price
- Department of Geography, San Diego State University, San Diego, CA 92182, USA;
| | - Daniel Sousa
- Department of Geography, San Diego State University, San Diego, CA 92182, USA;
| | - Francis J. Sousa
- College of Earth, Ocean and Atmospheric Sciences, Oregon State University, Corvallis, OR 97331, USA;
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Kaa JM, Konôpková Z, Preston TR, Cerantola V, Sahle CJ, Förster M, Albers C, Libon L, Sakrowski R, Wollenweber L, Buakor K, Dwivedi A, Mishchenko M, Nakatsutsumi M, Plückthun C, Schwinkendorf JP, Spiekermann G, Thiering N, Petitgirard S, Tolan M, Wilke M, Zastrau U, Appel K, Sternemann C. A von Hámos spectrometer for diamond anvil cell experiments at the High Energy Density Instrument of the European X-ray Free-Electron Laser. J Synchrotron Radiat 2023:S1600577523003041. [PMID: 37159289 DOI: 10.1107/s1600577523003041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
A von Hámos spectrometer has been implemented in the vacuum interaction chamber 1 of the High Energy Density instrument at the European X-ray Free-Electron Laser facility. This setup is dedicated, but not necessarily limited, to X-ray spectroscopy measurements of samples exposed to static compression using a diamond anvil cell. Si and Ge analyser crystals with different orientations are available for this setup, covering the hard X-ray energy regime with a sub-eV energy resolution. The setup was commissioned by measuring various emission spectra of free-standing metal foils and oxide samples in the energy range between 6 and 11 keV as well as low momentum-transfer inelastic X-ray scattering from a diamond sample. Its capabilities to study samples at extreme pressures and temperatures have been demonstrated by measuring the electronic spin-state changes of (Fe0.5Mg0.5)O, contained in a diamond anvil cell and pressurized to 100 GPa, via monitoring the Fe Kβ fluorescence with a set of four Si(531) analyser crystals at close to melting temperatures. The efficiency and signal-to-noise ratio of the spectrometer enables valence-to-core emission signals to be studied and single pulse X-ray emission from samples in a diamond anvil cell to be measured, opening new perspectives for spectroscopy in extreme conditions research.
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Affiliation(s)
- Johannes M Kaa
- Technische Universität Dortmund, Fakultät Physik/DELTA, Maria-Goeppert-Mayer-Straße 2, 44227 Dortmund, Germany
| | | | | | | | - Christoph J Sahle
- European Synchrotron Radiation Facility, 71 Avenue des Martyrs, 38000 Grenoble, France
| | - Mirko Förster
- Universität Potsdam, Am Neuen Palais 10, 14469 Potsdam, Germany
| | - Christian Albers
- Technische Universität Dortmund, Fakultät Physik/DELTA, Maria-Goeppert-Mayer-Straße 2, 44227 Dortmund, Germany
| | - Lélia Libon
- Universität Potsdam, Am Neuen Palais 10, 14469 Potsdam, Germany
| | - Robin Sakrowski
- Technische Universität Dortmund, Fakultät Physik/DELTA, Maria-Goeppert-Mayer-Straße 2, 44227 Dortmund, Germany
| | | | | | - Anand Dwivedi
- European XFEL, Holzkoppel 4, 22869 Schenefeld, Germany
| | | | | | | | | | | | - Nicola Thiering
- Technische Universität Dortmund, Fakultät Physik/DELTA, Maria-Goeppert-Mayer-Straße 2, 44227 Dortmund, Germany
| | | | - Metin Tolan
- Technische Universität Dortmund, Fakultät Physik/DELTA, Maria-Goeppert-Mayer-Straße 2, 44227 Dortmund, Germany
| | - Max Wilke
- Universität Potsdam, Am Neuen Palais 10, 14469 Potsdam, Germany
| | - Ulf Zastrau
- European XFEL, Holzkoppel 4, 22869 Schenefeld, Germany
| | - Karen Appel
- European XFEL, Holzkoppel 4, 22869 Schenefeld, Germany
| | - Christian Sternemann
- Technische Universität Dortmund, Fakultät Physik/DELTA, Maria-Goeppert-Mayer-Straße 2, 44227 Dortmund, Germany
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Cucci C, Casini A, Stefani L, Cattaneo B, Picollo M. A Novel Transmittance Vis-NIR Hyper-Spectral Imaging Scanner for Analysis of Photographic Negatives: A Potential Tool for Photography Conservation. Sensors (Basel) 2023; 23:3562. [PMID: 37050624 PMCID: PMC10098514 DOI: 10.3390/s23073562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 03/17/2023] [Accepted: 03/25/2023] [Indexed: 06/19/2023]
Abstract
This work illustrates a novel prototype of a transmittance hyperspectral imaging (HSI) scanner, operating in the 400-900 nm range, and designed on purpose for non-invasive analysis of photographic materials, such as negatives, films and slides. The instrument provides high-quality spectral data and high-definition spectral images on targets of small size (e.g., 35 mm film strips) and is the first example of HSI instrumentation specifically designed for applications in the photographic conservation field. The instrument was tested in laboratory and on a set of specimens selected from a damaged photographic archive. This experimentation, though preliminary, demonstrated the soundness of a technical approach based on HSI for large-scale spectroscopic characterization of photographic archival materials. The obtained results encourage the continuation of experimentation of HSI as an advanced tool for photography conservation.
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Affiliation(s)
- Costanza Cucci
- Institute of Applied Physics "Nello Carrara" of the Consiglio Nazionale delle Ricerche (IFAC-CNR), Via Madonna del Piano, 10, 50019 Firenze, Italy
| | - Andrea Casini
- Institute of Applied Physics "Nello Carrara" of the Consiglio Nazionale delle Ricerche (IFAC-CNR), Via Madonna del Piano, 10, 50019 Firenze, Italy
| | - Lorenzo Stefani
- Institute of Applied Physics "Nello Carrara" of the Consiglio Nazionale delle Ricerche (IFAC-CNR), Via Madonna del Piano, 10, 50019 Firenze, Italy
| | - Barbara Cattaneo
- Institute of Applied Physics "Nello Carrara" of the Consiglio Nazionale delle Ricerche (IFAC-CNR), Via Madonna del Piano, 10, 50019 Firenze, Italy
- Paper and Parchment Department of the Opificio delle Pietre Dure (OPD), Ministry of Culture, Viale F. Strozzi, 1, 50129 Firenze, Italy
| | - Marcello Picollo
- Institute of Applied Physics "Nello Carrara" of the Consiglio Nazionale delle Ricerche (IFAC-CNR), Via Madonna del Piano, 10, 50019 Firenze, Italy
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6
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Stavros EN, Chrone J, Cawse‐Nicholson K, Freeman A, Glenn NF, Guild L, Kokaly R, Lee C, Luvall J, Pavlick R, Poulter B, Schollaert Uz S, Serbin S, Thompson DR, Townsend PA, Turpie K, Yuen K, Thome K, Wang W, Zareh S, Nastal J, Bearden D, Miller CE, Schimel D. Designing an Observing System to Study the Surface Biology and Geology (SBG) of the Earth in the 2020s. J Geophys Res Biogeosci 2023; 128:e2021JG006471. [PMID: 37362830 PMCID: PMC10286770 DOI: 10.1029/2021jg006471] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 03/16/2022] [Accepted: 03/17/2022] [Indexed: 06/28/2023]
Abstract
Observations of planet Earth from space are a critical resource for science and society. Satellite measurements represent very large investments and United States (US) agencies organize their effort to maximize the return on that investment. The US National Research Council conducts a survey of Earth science and applications to prioritize observations for the coming decade. The most recent survey prioritized a visible to shortwave infrared imaging spectrometer and a multispectral thermal infrared imager to meet a range of needs for studying Surface Biology and Geology (SBG). SBG will be the premier integrated observatory for observing the emerging impacts of climate change by characterizing the diversity of plant life and resolving chemical and physiological signatures. It will address wildfire risk, behavior, and recovery as well as responses to hazards such as oil spills, toxic minerals in minelands, harmful algal blooms, landslides, and other geological hazards. The SBG team analyzed needed instrument characteristics (spatial, temporal, and spectral resolutions, measurement uncertainty) and assessed the cost, mass, power, volume, and risk of different architectures. We present an overview of the Research and Applications trade-study analysis of algorithms, calibration and validation needs, and societal applications with specifics of substudies detailed in other articles in this special collection. We provide a value framework to converge from hundreds down to three candidate architectures recommended for development. The analysis identified valuable opportunities for international collaboration to increase the revisit frequency, adding value for all partners, leading to a clear measurement strategy for an observing system architecture.
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Affiliation(s)
- E. Natasha Stavros
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Jon Chrone
- NASA Langley Research CenterHamptonVAUSA
| | | | - Anthony Freeman
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | | | | | | | - Christine Lee
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | | | - Ryan Pavlick
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | | | | | | | - David R. Thompson
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Philip A. Townsend
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
- University of Wisconsin‐MadisonMadisonWIUSA
| | - Kevin Turpie
- NASA Goddard Space Flight CenterGreenbeltMDUSA
- University of Maryland Baltimore CountyGreenbeltMDUSA
| | - Karen Yuen
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Kurt Thome
- NASA Goddard Space Flight CenterGreenbeltMDUSA
| | | | - Shannon‐Kian Zareh
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Jamie Nastal
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - David Bearden
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Charles E. Miller
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - David Schimel
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
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7
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Peng H, Cendrero-Mateo MP, Bendig J, Siegmann B, Acebron K, Kneer C, Kataja K, Muller O, Rascher U. HyScreen: A Ground-Based Imaging System for High-Resolution Red and Far-Red Solar-Induced Chlorophyll Fluorescence. Sensors (Basel) 2022; 22:s22239443. [PMID: 36502141 PMCID: PMC9740991 DOI: 10.3390/s22239443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 11/28/2022] [Accepted: 11/28/2022] [Indexed: 05/14/2023]
Abstract
Solar-induced chlorophyll fluorescence (SIF) is used as a proxy of photosynthetic efficiency. However, interpreting top-of-canopy (TOC) SIF in relation to photosynthesis remains challenging due to the distortion introduced by the canopy's structural effects (i.e., fluorescence re-absorption, sunlit-shaded leaves, etc.) and sun-canopy-sensor geometry (i.e., direct radiation infilling). Therefore, ground-based, high-spatial-resolution data sets are needed to characterize the described effects and to be able to downscale TOC SIF to the leafs where the photosynthetic processes are taking place. We herein introduce HyScreen, a ground-based push-broom hyperspectral imaging system designed to measure red (F687) and far-red (F760) SIF and vegetation indices from TOC with single-leaf spatial resolution. This paper presents measurement protocols, the data processing chain and a case study of SIF retrieval. Raw data from two imaging sensors were processed to top-of-canopy radiance by dark-current correction, radiometric calibration, and empirical line correction. In the next step, the improved Fraunhofer line descrimination (iFLD) and spectral-fitting method (SFM) were used for SIF retrieval, and vegetation indices were calculated. With the developed protocol and data processing chain, we estimated a signal-to-noise ratio (SNR) between 50 and 200 from reference panels with reflectance from 5% to 95% and noise equivalent radiance (NER) of 0.04 (5%) to 0.18 (95%) mW m-2 sr-1 nm-1. The results from the case study showed that non-vegetation targets had SIF values close to 0 mW m-2 sr-1 nm-1, whereas vegetation targets had a mean F687 of 1.13 and F760 of 1.96 mW m-2 sr-1 nm-1 from the SFM method. HyScreen showed good performance for SIF retrievals at both F687 and F760; nevertheless, we recommend further adaptations to correct for the effects of noise, varying illumination and sensor optics. In conclusion, due to its high spatial resolution, Hyscreen is a promising tool for investigating the relationship between leafs and TOC SIF as well as their relationship with plants' photosynthetic capacity.
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Affiliation(s)
- Huaiyue Peng
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52428 Jülich, Germany
- Correspondence: ; Tel.: +49-(0)-2461-61-4514
| | - Maria Pilar Cendrero-Mateo
- Laboratory of Earth Observation, Image Processing Laboratory, University of Valencia, 46980 Paterna, Spain
| | - Juliane Bendig
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52428 Jülich, Germany
| | - Bastian Siegmann
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52428 Jülich, Germany
| | - Kelvin Acebron
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52428 Jülich, Germany
| | - Caspar Kneer
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52428 Jülich, Germany
| | - Kari Kataja
- Specim Spectral Imaging Ltd., 90590 Oulu, Finland
| | - Onno Muller
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52428 Jülich, Germany
| | - Uwe Rascher
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52428 Jülich, Germany
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8
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Cusworth DH, Thorpe AK, Ayasse AK, Stepp D, Heckler J, Asner GP, Miller CE, Yadav V, Chapman JW, Eastwood ML, Green RO, Hmiel B, Lyon DR, Duren RM. Strong methane point sources contribute a disproportionate fraction of total emissions across multiple basins in the United States. Proc Natl Acad Sci U S A 2022; 119:e2202338119. [PMID: 36099297 DOI: 10.1073/pnas.2202338119] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Understanding, prioritizing, and mitigating methane (CH4) emissions requires quantifying CH4 budgets from facility scales to regional scales with the ability to differentiate between source sectors. We deployed a tiered observing system for multiple basins in the United States (San Joaquin Valley, Uinta, Denver-Julesburg, Permian, Marcellus). We quantify strong point source emissions (>10 kg CH4 h-1) using airborne imaging spectrometers, attribute them to sectors, and assess their intermittency with multiple revisits. We compare these point source emissions to total basin CH4 fluxes derived from inversion of Sentinel-5p satellite CH4 observations. Across basins, point sources make up on average 40% of the regional flux. We sampled some basins several times across multiple months and years and find a distinct bimodal structure to emission timescales: the total point source budget is split nearly in half by short-lasting and long-lasting emission events. With the increasing airborne and satellite observing capabilities planned for the near future, tiered observing systems will more fully quantify and attribute CH4 emissions from facility to regional scales, which is needed to effectively and efficiently reduce methane emissions.
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9
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Cawse‐Nicholson K, Raiho AM, Thompson DR, Hulley GC, Miller CE, Miner KR, Poulter B, Schimel D, Schneider FD, Townsend PA, Zareh SK. Intrinsic Dimensionality as a Metric for the Impact of Mission Design Parameters. J Geophys Res Biogeosci 2022; 127:e2022JG006876. [PMID: 36248721 PMCID: PMC9539474 DOI: 10.1029/2022jg006876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 07/05/2022] [Accepted: 07/06/2022] [Indexed: 06/16/2023]
Abstract
High-resolution space-based spectral imaging of the Earth's surface delivers critical information for monitoring changes in the Earth system as well as resource management and utilization. Orbiting spectrometers are built according to multiple design parameters, including ground sampling distance (GSD), spectral resolution, temporal resolution, and signal-to-noise ratio. Different applications drive divergent instrument designs, so optimization for wide-reaching missions is complex. The Surface Biology and Geology component of NASA's Earth System Observatory addresses science questions and meets applications needs across diverse fields, including terrestrial and aquatic ecosystems, natural disasters, and the cryosphere. The algorithms required to generate the geophysical variables from the observed spectral imagery each have their own inherent dependencies and sensitivities, and weighting these objectively is challenging. Here, we introduce intrinsic dimensionality (ID), a measure of information content, as an applications-agnostic, data-driven metric to quantify performance sensitivity to various design parameters. ID is computed through the analysis of the eigenvalues of the image covariance matrix, and can be thought of as the number of significant principal components. This metric is extremely powerful for quantifying the information content in high-dimensional data, such as spectrally resolved radiances and their changes over space and time. We find that the ID decreases for coarser GSD, decreased spectral resolution and range, less frequent acquisitions, and lower signal-to-noise levels. This decrease in information content has implications for all derived products. ID is simple to compute, providing a single quantitative standard to evaluate combinations of design parameters, irrespective of higher-level algorithms, products, applications, or disciplines.
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Affiliation(s)
- K. Cawse‐Nicholson
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - A. M. Raiho
- NASA Goddard Space Flight CenterBiospheric Sciences LabGreenbeltMDUSA
- Earth System Science Interdisciplinary CenterUniversity of MarylandCollege Park, GreenbeltMDUSA
| | - D. R. Thompson
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - G. C. Hulley
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - C. E. Miller
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - K. R. Miner
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - B. Poulter
- NASA Goddard Space Flight CenterBiospheric Sciences LabGreenbeltMDUSA
| | - D. Schimel
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - F. D. Schneider
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - P. A. Townsend
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
- University of WisconsinMadisonWIUSA
| | - S. K. Zareh
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
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10
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Thompson DR, Bohn N, Brodrick PG, Carmon N, Eastwood ML, Eckert R, Fichot CG, Harringmeyer JP, Nguyen HM, Simard M, Thorpe AK. Atmospheric Lengthscales for Global VSWIR Imaging Spectroscopy. J Geophys Res Biogeosci 2022; 127:e2021JG006711. [PMID: 35859986 PMCID: PMC9285454 DOI: 10.1029/2021jg006711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 05/31/2022] [Accepted: 06/01/2022] [Indexed: 06/15/2023]
Abstract
Future global Visible Shortwave Infrared Imaging Spectrometers, such as the Surface Biology and Geology (SBG) mission, will regularly cover the Earth's entire terrestrial land area. These missions need high fidelity atmospheric correction to produce consistent maps of terrestrial and aquatic ecosystem traits. However, estimation of surface reflectance and atmospheric state is computationally challenging, and the terabyte data volumes of global missions will exceed available processing capacity. This article describes how missions can overcome this bottleneck using the spatial continuity of atmospheric fields. Contemporary imaging spectrometers oversample atmospheric spatial variability, so it is not necessary to invert every pixel. Spatially sparse solutions can train local linear emulators that provide fast, exact inversions in their vicinity. We find that estimating the atmosphere at 200 m scales can outperform traditional atmospheric correction, improving speed by one to two orders of magnitude with no measurable penalty to accuracy. We validate performance with an airborne field campaign, showing reflectance accuracies with RMSE of 1.1% or better compared to ground measurements of diverse targets. These errors are statistically consistent with retrieval uncertainty budgets. Local emulators can close the efficiency gap and make rigorous model inversion algorithms feasible for global missions such as SBG.
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Affiliation(s)
- David R Thompson
- Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA
| | - Niklas Bohn
- Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences Potsdam Germany
| | - Philip G Brodrick
- Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA
| | - Nimrod Carmon
- Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA
| | - Michael L Eastwood
- Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA
| | - Regina Eckert
- Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA
| | - Cédric G Fichot
- Department of Earth and Environment Boston University Boston MA USA
| | | | - Hai M Nguyen
- Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA
| | - Marc Simard
- Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA
| | - Andrew K Thorpe
- Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA
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11
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Brodrick PG, Thompson DR, Garay MJ, Giles DM, Holben BN, Kalashnikova OV. Simultaneous Characterization of Wildfire Smoke and Surface Properties With Imaging Spectroscopy During the FIREX-AQ Field Campaign. J Geophys Res Atmos 2022; 127:e2021JD034905. [PMID: 35865790 PMCID: PMC9286569 DOI: 10.1029/2021jd034905] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 08/09/2021] [Accepted: 09/15/2021] [Indexed: 06/15/2023]
Abstract
We introduce and evaluate an approach for the simultaneous retrieval of aerosol and surface properties from Airborne Visible/Infrared Imaging Spectrometer Classic (AVIRIS-C) data collected during wildfires. The joint National Aeronautics and Space Administration (NASA) National Oceanic and Atmospheric Administration Fire Influence on Regional to Global Environments and Air Quality field campaign took place in August 2019, and involved two aircraft and coordinated ground-based observations. The AVIRIS-C instrument acquired data from onboard NASA's high altitude ER-2 research aircraft, coincident in space and time with aerosol observations obtained from the Aerosol Robotic Network (AERONET) DRAGON mobile platform in the smoke plume downwind of the Williams Flats Fire in northern Washington in August 2019. Observations in this smoke plume were used to assess the capacity of optimal-estimation based retrievals to simultaneously estimate aerosol optical depth (AOD) and surface reflectance from Visible Shortwave Infrared (VSWIR) imaging spectroscopy. Radiative transfer modeling of the sensitivities in spectral information collected over smoke reveal the potential capacity of high spectral resolution retrievals to distinguish between sulfate and smoke aerosol models, as well as sensitivity to the aerosol size distribution. Comparison with ground-based AERONET observations demonstrates that AVIRIS-C retrievals of AOD compare favorably with direct sun AOD measurements. Our analyses suggest that spectral information collected from the full VSWIR spectral interval, not just the shortest wavelengths, enables accurate retrievals. We use this approach to continuously map both aerosols and surface reflectance at high spatial resolution across heterogeneous terrain, even under relatively high AOD conditions associated with wildfire smoke.
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Affiliation(s)
- Philip G. Brodrick
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - David R. Thompson
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Michael J. Garay
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - David M. Giles
- Science Systems and Applications Inc. (SSAI)LanhamMDUSA
- NASA Goddard Space Flight Center (GSFC)GreenbeltMDUSA
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12
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Blonder B, Brodrick PG, Walton JA, Chadwick KD, Breckheimer IK, Marchetti S, Ray CA, Mock KE. Remote sensing of cytotype and its consequences for canopy damage in quaking aspen. Glob Chang Biol 2022; 28:2491-2504. [PMID: 34962013 DOI: 10.1111/gcb.16064] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Revised: 12/19/2021] [Accepted: 12/19/2021] [Indexed: 06/14/2023]
Abstract
Mapping geographic mosaics of genetic variation and their consequences via genotype x environment interactions at large extents and high resolution has been limited by the scalability of DNA sequencing. Here, we address this challenge for cytotype (chromosome copy number) variation in quaking aspen, a drought-impacted foundation tree species. We integrate airborne imaging spectroscopy data with ground-based DNA sequencing data and canopy damage data in 391 km2 of southwestern Colorado. We show that (1) aspen cover and cytotype can be remotely sensed at 1 m spatial resolution, (2) the geographic mosaic of cytotypes is heterogeneous and interdigitated, (3) triploids have higher leaf nitrogen, canopy water content, and carbon isotope shifts (δ13 C) than diploids, and (4) canopy damage varies among cytotypes and depends on interactions with topography, canopy height, and trait variables. Triploids are at higher risk in hotter and drier conditions.
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Affiliation(s)
- Benjamin Blonder
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, Berkeley, California, USA
- Rocky Mountain Biological Laboratory, Crested Butte, Colorado, USA
- School of Life Sciences, Arizona State University, Tempe, Arizona, USA
| | - Philip G Brodrick
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
| | - James A Walton
- Department of Wildland Resources, Utah State University, Logan, Utah, USA
| | - Katherine Dana Chadwick
- Department of Earth System Science, Stanford University, Stanford, California, USA
- Climate and Ecosystems Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA
| | | | - Suzanne Marchetti
- Forest Health Protection, United States Forest Service, Gunnison, Colorado, USA
| | - Courtenay A Ray
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, Berkeley, California, USA
- Rocky Mountain Biological Laboratory, Crested Butte, Colorado, USA
- School of Life Sciences, Arizona State University, Tempe, Arizona, USA
| | - Karen E Mock
- Department of Wildland Resources, Utah State University, Logan, Utah, USA
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13
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Weingarten E, Martin RE, Hughes RF, Vaughn NR, Shafron E, Asner GP. Early detection of a tree pathogen using airborne remote sensing. Ecol Appl 2022; 32:e2519. [PMID: 34918400 DOI: 10.1002/eap.2519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 08/25/2021] [Indexed: 06/14/2023]
Abstract
Native forests of Hawai'i Island are experiencing an ecological crisis in the form of Rapid 'Ōhi'a Death (ROD), a recently characterized disease caused by two fungal pathogens in the genus Ceratocystis. Since approximately 2010, this disease has caused extensive mortality of Hawai'i's keystone endemic tree, known as 'ōhi'a (Metrosideros polymorpha). Visible symptoms of ROD include rapid browning of canopy leaves, followed by death of the tree within weeks. This quick progression leading to tree mortality makes early detection critical to understanding where the disease will move at a timescale feasible for controlling the disease. We used repeat laser-guided imaging spectroscopy (LGIS) of forests on Hawai'i Island collected by the Global Airborne Observatory (GAO) in 2018 and 2019 to derive maps of foliar trait indices previously found to be important in distinguishing between ROD-infected and healthy 'ōhi'a canopies. Data from these maps were used to develop a prognostic indicator of tree stress prior to the visible onset of browning. We identified canopies that were green in 2018, but became brown in 2019 (defined as "to become brown"; TBB), and a corresponding set of canopies that remained green. The data mapped in 2018 showed separability of foliar trait indices between TBB and green 'ōhi'a, indicating early detection of canopy stress prior to the onset of ROD. Overall, a combination of linear and non-linear analyses revealed canopy water content (CWC), foliar tannins, leaf mass per area (LMA), phenols, cellulose, and non-structural carbohydrates (NSC) are primary drivers of the prognostic spectral capability which collectively result in strong consistent changes in leaf spectral reflectance in the near-infrared (700-1300 nm) and shortwave-infrared regions (1300-2500 nm). Results provide insight into the underlying foliar traits that are indicative of physiological responses of M. polymorpha trees infected with Ceratocycstis and suggest that imaging spectroscopy is an effective tool for identifying trees likely to succumb to ROD prior to the onset of visible symptoms.
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Affiliation(s)
- Erin Weingarten
- Center for Global Discovery and Conservation Science, Arizona State University, Tempe, Arizona, USA
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, Arizona, USA
| | - Roberta E Martin
- Center for Global Discovery and Conservation Science, Arizona State University, Tempe, Arizona, USA
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, Arizona, USA
| | | | - Nicholas R Vaughn
- Center for Global Discovery and Conservation Science, Arizona State University, Tempe, Arizona, USA
| | - Ethan Shafron
- Center for Global Discovery and Conservation Science, Arizona State University, Tempe, Arizona, USA
| | - Gregory P Asner
- Center for Global Discovery and Conservation Science, Arizona State University, Tempe, Arizona, USA
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14
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Queally N, Ye Z, Zheng T, Chlus A, Schneider F, Pavlick RP, Townsend PA. FlexBRDF: A Flexible BRDF Correction for Grouped Processing of Airborne Imaging Spectroscopy Flightlines. J Geophys Res Biogeosci 2022; 127:e2021JG006622. [PMID: 35865141 PMCID: PMC9286663 DOI: 10.1029/2021jg006622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 12/16/2021] [Accepted: 12/22/2021] [Indexed: 06/15/2023]
Abstract
Bidirectional reflectance distribution function (BRDF) effects are a persistent issue for the analysis of vegetation in airborne imaging spectroscopy data, especially when mosaicking results from adjacent flightlines. With the advent of large airborne imaging efforts from NASA and the U.S. National Ecological Observatory Network (NEON), there is increasing need for methods that are flexible and automatable across images with diverse land cover. Flexible bidirectional reflectance distribution function (FlexBRDF) is built upon the widely used kernel method, with additional features including stratified random sampling across flightline groups, dynamic land cover stratification by normalized difference vegetation index (NDVI), interpolation of correction coefficients across NDVI bins, and the use of a reference solar zenith angle. We demonstrate FlexBRDF using nine long (150-400 km) airborne visible/infrared imaging spectrometer (AVIRIS)-Classic flightlines collected on 22 May 2013 over Southern California, where diverse land cover and a wide range of solar illumination yield significant BRDF effects. We further test the approach on additional AVIRIS-Classic data from California, AVIRIS-Next Generation data from the Arctic and India, and NEON imagery from Wisconsin. Comparison of overlapping areas of flightlines show that models built from multiple flightlines performed better than those built for single images (root mean square error improved up to 2.3% and mean absolute deviation 2.5%). Standardization to a common solar zenith angle among a flightline group improved performance, and interpolation across bins minimized between-bin boundaries. While BRDF corrections for individual sites suffice for local studies, FlexBRDF is an open source option that is compatible with bulk processing of large airborne data sets covering diverse land cover needed for calibration/validation of forthcoming spaceborne imaging spectroscopy missions.
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Affiliation(s)
- Natalie Queally
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWIUSA
| | - Zhiwei Ye
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWIUSA
| | - Ting Zheng
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWIUSA
| | - Adam Chlus
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWIUSA
| | - Fabian Schneider
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Ryan P. Pavlick
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Philip A. Townsend
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWIUSA
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15
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Agrawal A, Petersen MR. Detecting Arsenic Contamination Using Satellite Imagery and Machine Learning. Toxics 2021; 9:333. [PMID: 34941767 DOI: 10.3390/toxics9120333] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 11/17/2021] [Accepted: 11/29/2021] [Indexed: 11/17/2022]
Abstract
Arsenic, a potent carcinogen and neurotoxin, affects over 200 million people globally. Current detection methods are laborious, expensive, and unscalable, being difficult to implement in developing regions and during crises such as COVID-19. This study attempts to determine if a relationship exists between soil’s hyperspectral data and arsenic concentration using NASA’s Hyperion satellite. It is the first arsenic study to use satellite-based hyperspectral data and apply a classification approach. Four regression machine learning models are tested to determine this correlation in soil with bare land cover. Raw data are converted to reflectance, problematic atmospheric influences are removed, characteristic wavelengths are selected, and four noise reduction algorithms are tested. The combination of data augmentation, Genetic Algorithm, Second Derivative Transformation, and Random Forest regression (R2=0.840 and normalized root mean squared error (re-scaled to [0,1]) = 0.122) shows strong correlation, performing better than past models despite using noisier satellite data (versus lab-processed samples). Three binary classification machine learning models are then applied to identify high-risk shrub-covered regions in ten U.S. states, achieving strong accuracy (=0.693) and F1-score (=0.728). Overall, these results suggest that such a methodology is practical and can provide a sustainable alternative to arsenic contamination detection.
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16
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Baeza A, Martin RE, Stephenson NL, Das AJ, Hardwick P, Nydick K, Mallory J, Slaton M, Evans K, Asner GP. Mapping the vulnerability of giant sequoias after extreme drought in California using remote sensing. Ecol Appl 2021; 31:e02395. [PMID: 34164888 DOI: 10.1002/eap.2395] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 01/07/2021] [Accepted: 02/04/2021] [Indexed: 06/13/2023]
Abstract
Between 2012 and 2016, California suffered one of the most severe droughts on record. During this period Sequoiadendron giganteum (giant sequoias) in the Sequoia and Kings Canyon National Parks (SEKI), California, USA experienced canopy water content (CWC) loss, unprecedented foliage senescence, and, in a few cases, death. We present an assessment of the vulnerability of giant sequoia populations to droughts that is currently lacking and needed for management. We used a temporal trend of remotely sensed CWC obtained between 2015 and 2017, and recently georeferenced giant sequoia crowns to quantify the vulnerability of 7,408 individuals in 10 groves in the northern portion of SEKI. CWC is sensitive to changes in liquid water in tree canopies; therefore, it is a useful metric for quantifying the response of sequoia trees to drought. Temporal trends indicated that 9% of giant sequoias had a significant decline or consistently low CWC, suggesting these trees were likely operating at low photosynthetic capacity and potentially at high risk to drought stress. We also found that 20% of the giant sequoias had an increase or consistently high level of CWC, indicating these trees were at low risk to drought stress. These vulnerability categories were used in a random forest model with a combination of topographic, fire-related, and climate variables to generate high-resolution vulnerability risk maps. These maps show that higher risk is associated with lower elevation and higher climate water deficit. We also found that sequoias at higher elevations but located near meadows had higher vulnerability risk. These results and the vulnerability maps can identify vulnerable sequoias that may be difficult to save or locations of refugia to be protected, and thus may aid forest managers in preparation for future droughts.
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Affiliation(s)
- Andres Baeza
- Center for Global Discovery and Conservation Science, Arizona State University. Tempe, Arizona, USA
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, Arizona, USA
| | - Roberta E Martin
- Center for Global Discovery and Conservation Science, Arizona State University. Tempe, Arizona, USA
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, Arizona, USA
| | - Nathan L Stephenson
- U.S. Geological Survey, Western Ecological Research Center, Three Rivers, California, USA
| | - Adrian J Das
- U.S. Geological Survey, Western Ecological Research Center, Three Rivers, California, USA
| | - Paul Hardwick
- Sequoia and Kings Canyon National Parks, Division of Resources Management and Science, Three Rivers, California, USA
| | - Koren Nydick
- Sequoia and Kings Canyon National Parks, Division of Resources Management and Science, Three Rivers, California, USA
| | - Jeff Mallory
- USDA Forest Service, Pacific Southwest Region, Remote Sensing Laboratory, McClellan, California, USA
| | - Michèle Slaton
- USDA Forest Service, Pacific Southwest Region, Remote Sensing Laboratory, McClellan, California, USA
| | - Kirk Evans
- USDA Forest Service, Pacific Southwest Region, Remote Sensing Laboratory, McClellan, California, USA
| | - Gregory P Asner
- Center for Global Discovery and Conservation Science, Arizona State University. Tempe, Arizona, USA
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17
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Su WH, Xue H. Imaging Spectroscopy and Machine Learning for Intelligent Determination of Potato and Sweet Potato Quality. Foods 2021; 10:2146. [PMID: 34574253 PMCID: PMC8472741 DOI: 10.3390/foods10092146] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 08/30/2021] [Accepted: 09/07/2021] [Indexed: 11/16/2022] Open
Abstract
Imaging spectroscopy has emerged as a reliable analytical method for effectively characterizing and quantifying quality attributes of agricultural products. By providing spectral information relevant to food quality properties, imaging spectroscopy has been demonstrated to be a potential method for rapid and non-destructive classification, authentication, and prediction of quality parameters of various categories of tubers, including potato and sweet potato. The imaging technique has demonstrated great capacities for gaining rapid information about tuber physical properties (such as texture, water binding capacity, and specific gravity), chemical components (such as protein, starch, and total anthocyanin), varietal authentication, and defect aspects. This paper emphasizes how recent developments in spectral imaging with machine learning have enhanced overall capabilities to evaluate tubers. The machine learning algorithms coupled with feature variable identification approaches have obtained acceptable results. This review briefly introduces imaging spectroscopy and machine learning, then provides examples and discussions of these techniques in tuber quality determinations, and presents the challenges and future prospects of the technology. This review will be of great significance to the study of tubers using spectral imaging technology.
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Affiliation(s)
- Wen-Hao Su
- Department of Agricultural Engineering, College of Engineering, China Agricultural University, Beijing 100083, China;
| | - Huidan Xue
- School of Economics and Management, Beijing University of Technology, Beijing 100124, China
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18
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Greenberger RN, Harris M, Ehlmann BL, Crotteau MA, Kelemen PB, Manning CE, Teagle DAH. Hydrothermal Alteration of the Ocean Crust and Patterns in Mineralization With Depth as Measured by Micro-Imaging Infrared Spectroscopy. J Geophys Res Solid Earth 2021; 126:e2021JB021976. [PMID: 34595085 PMCID: PMC8459238 DOI: 10.1029/2021jb021976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 06/24/2021] [Accepted: 07/11/2021] [Indexed: 06/13/2023]
Abstract
Processes for formation, cooling, and altering Earth's ocean crust are not yet completely understood due to challenges in access and sampling. Here, we use contiguous micro-imaging infrared spectroscopy to develop complete-core maps of mineral occurrence and investigate spatial patterns in the hydrothermal alteration of 1.2 km of oceanic crust recovered from Oman Drilling Project Holes GT1A, GT2A, and GT3A drilled in the Samail Ophiolite, Oman. The imaging spectrometer shortwave infrared sensor measured reflectance of light at wavelengths 1.0-2.6 μm at 250-260 μm/pixel, resulting in >1 billion independent measurements. We map distributions of nine key primary and secondary minerals/mineral groups-clinopyroxene, amphibole, calcite, chlorite, epidote, gypsum, kaolinite/montmorillonite, prehnite, and zeolite-and find differences in their spatial occurrences and pervasiveness. Accuracy of spectral mapping of occurrence is 68%-100%, established using X-ray diffraction measurements from the core description. The sheeted dikes and gabbros of upper oceanic crust Hole GT3A show more pervasive alteration and alteration dominated by chlorite, amphibole, and epidote. The foliated/layered gabbros of GT2A from intermediate crustal depths have similarly widespread chlorite but more zeolite and little amphibole and epidote. The layered gabbros of the lower oceanic crust (GT1A) have remnant pyroxene and 2X less chlorite, but alteration is extensive within and surrounding major fault zones with widespread occurrences of amphibole. The results indicate greater distribution of higher temperature alteration minerals in the upper oceanic crust relative to deeper gabbros and highlight the importance of fault zones in hydrothermal convection in the lower ocean crust.
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Affiliation(s)
- Rebecca N. Greenberger
- Division of Geological and Planetary SciencesCalifornia Institute of TechnologyPasadenaCAUSA
| | - Michelle Harris
- School of Geography, Earth, and Environmental SciencesPlymouth UniversityPlymouthUK
| | - Bethany L. Ehlmann
- Division of Geological and Planetary SciencesCalifornia Institute of TechnologyPasadenaCAUSA
| | - Molly A. Crotteau
- Division of Geological and Planetary SciencesCalifornia Institute of TechnologyPasadenaCAUSA
| | - Peter B. Kelemen
- Department of Earth & Environmental SciencesLamont‐Doherty Earth ObservatoryColumbia UniversityPalisadesNYUSA
| | - Craig E. Manning
- Department of Earth, Planetary, and Space SciencesUniversity of CaliforniaLos AngelesCAUSA
| | - Damon A. H. Teagle
- School of Ocean and Earth ScienceNational Oceanography Centre SouthamptonUniversity of SouthamptonSouthamptonUK
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19
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Wang Z, Chlus A, Geygan R, Ye Z, Zheng T, Singh A, Couture JJ, Cavender-Bares J, Kruger EL, Townsend PA. Foliar functional traits from imaging spectroscopy across biomes in eastern North America. New Phytol 2020; 228:494-511. [PMID: 32463927 DOI: 10.1111/nph.16711] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Accepted: 05/15/2020] [Indexed: 05/28/2023]
Abstract
Foliar functional traits are widely used to characterize leaf and canopy properties that drive ecosystem processes and to infer physiological processes in Earth system models. Imaging spectroscopy provides great potential to map foliar traits to characterize continuous functional variation and diversity, but few studies have demonstrated consistent methods for mapping multiple traits across biomes. With airborne imaging spectroscopy data and field data from 19 sites, we developed trait models using partial least squares regression, and mapped 26 foliar traits in seven NEON (National Ecological Observatory Network) ecoregions (domains) including temperate and subtropical forests and grasslands of eastern North America. Model validation accuracy varied among traits (normalized root mean squared error, 9.1-19.4%; coefficient of determination, 0.28-0.82), with phenolic concentration, leaf mass per area and equivalent water thickness performing best across domains. Across all trait maps, 90% of vegetated pixels had reasonable values for one trait, and 28-81% provided high confidence for multiple traits concurrently. Maps of 26 traits and their uncertainties for eastern US NEON sites are available for download, and are being expanded to the western United States and tundra/boreal zone. These data enable better understanding of trait variations and relationships over large areas, calibration of ecosystem models, and assessment of continental-scale functional diversity.
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Affiliation(s)
- Zhihui Wang
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI, 53706, USA
| | - Adam Chlus
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI, 53706, USA
| | - Ryan Geygan
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI, 53706, USA
| | - Zhiwei Ye
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI, 53706, USA
| | - Ting Zheng
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI, 53706, USA
| | - Aditya Singh
- Department of Agricultural and Biological Engineering, University of Florida, 1741 Museum Rd, Gainesville, FL, 32611, USA
| | - John J Couture
- Departments of Entomology and Forestry and Natural Resources and Center for Plant Biology, Purdue University, 901 W. State St, West Lafayette, IN, 47907, USA
| | - Jeannine Cavender-Bares
- Department of Ecology, Evolution and Behavior, University of Minnesota, Saint Paul, MN, 55108, USA
| | - Eric L Kruger
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI, 53706, USA
| | - Philip A Townsend
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI, 53706, USA
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20
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Czyż EA, Guillén Escribà C, Wulf H, Tedder A, Schuman MC, Schneider FD, Schaepman ME. Intraspecific genetic variation of a Fagus sylvatica population in a temperate forest derived from airborne imaging spectroscopy time series. Ecol Evol 2020; 10:7419-7430. [PMID: 32760538 PMCID: PMC7391319 DOI: 10.1002/ece3.6469] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Revised: 05/06/2020] [Accepted: 05/11/2020] [Indexed: 01/26/2023] Open
Abstract
The growing pace of environmental change has increased the need for large-scale monitoring of biodiversity. Declining intraspecific genetic variation is likely a critical factor in biodiversity loss, but is especially difficult to monitor: assessments of genetic variation are commonly based on measuring allele pools, which requires sampling of individuals and extensive sample processing, limiting spatial coverage. Alternatively, imaging spectroscopy data from remote platforms may hold the potential to reveal genetic structure of populations. In this study, we investigated how differences detected in an airborne imaging spectroscopy time series correspond to genetic variation within a population of Fagus sylvatica under natural conditions.We used multi-annual APEX (Airborne Prism Experiment) imaging spectrometer data from a temperate forest located in the Swiss midlands (Laegern, 47°28'N, 8°21'E), along with microsatellite data from F. sylvatica individuals collected at the site. We identified variation in foliar reflectance independent of annual and seasonal changes which we hypothesize is more likely to correspond to stable genetic differences. We established a direct connection between the spectroscopy and genetics data by using partial least squares (PLS) regression to predict the probability of belonging to a genetic cluster from spectral data.We achieved the best genetic structure prediction by using derivatives of reflectance and a subset of wavebands rather than full-analyzed spectra. Our model indicates that spectral regions related to leaf water content, phenols, pigments, and wax composition contribute most to the ability of this approach to predict genetic structure of F. sylvatica population in natural conditions.This study advances the use of airborne imaging spectroscopy to assess tree genetic diversity at canopy level under natural conditions, which could overcome current spatiotemporal limitations on monitoring, understanding, and preventing genetic biodiversity loss imposed by requirements for extensive in situ sampling.
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Affiliation(s)
- Ewa A. Czyż
- Remote Sensing LaboratoriesDepartment of GeographyUniversity of ZürichZürichSwitzerland
| | - Carla Guillén Escribà
- Remote Sensing LaboratoriesDepartment of GeographyUniversity of ZürichZürichSwitzerland
| | - Hendrik Wulf
- Remote Sensing LaboratoriesDepartment of GeographyUniversity of ZürichZürichSwitzerland
| | - Andrew Tedder
- Department of Evolutionary Biology and Environmental StudiesUniversity of ZürichZürichSwitzerland
- School of Chemistry and BiosciencesFaculty of Life SciencesUniversity of BradfordBradfordUK
| | - Meredith C. Schuman
- Remote Sensing LaboratoriesDepartment of GeographyUniversity of ZürichZürichSwitzerland
- Department of ChemistryUniversity of ZürichZürichSwitzerland
| | - Fabian D. Schneider
- Remote Sensing LaboratoriesDepartment of GeographyUniversity of ZürichZürichSwitzerland
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Michael E. Schaepman
- Remote Sensing LaboratoriesDepartment of GeographyUniversity of ZürichZürichSwitzerland
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21
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Chadwick KD, Asner GP. Geomorphic transience moderates topographic controls on tropical canopy foliar traits. Ecol Lett 2020; 23:1276-1286. [PMID: 32452136 DOI: 10.1111/ele.13531] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 12/18/2019] [Accepted: 04/13/2020] [Indexed: 11/28/2022]
Abstract
Tropical ecosystems that exist on mountainous terrain harbour enormous species and functional diversity. In addition, the morphology of these complex landscapes is dynamic. Stream channels respond to mountain uplift by eroding into rising rock bodies. Many local factors determine whether channels are actively downcutting, in relative steady-state, or aggrading. It is possible to assess the trajectory of catchment-level landscape evolution utilising lidar-based models, but the effect of these trajectories on biogeochemical gradients and organisation of canopy traits across climatic and geochemical conditions remain uncertain. We use canopy trait maps to assess how variable erosion rate within catchments influence hillslope controls on canopy traits across Mt. Kinabalu, Borneo. While foliar nutrient content generally increased along hillslopes, these relationships were moderated by catchment responses to changing erosion pressure, with active downcutting associated with greater turnover in canopy traits along hillslopes. These results provide an understanding of geomorphic process controls on forest functional diversity.
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Affiliation(s)
- K Dana Chadwick
- Department of Earth System Science, Stanford University, Stanford, CA, USA.,Earth and Environmental Sciences Area, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Gregory P Asner
- Center for Global Discovery and Conservation Science, Arizona State University, Tempe, AZ, USA
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22
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Swinfield T, Both S, Riutta T, Bongalov B, Elias D, Majalap‐Lee N, Ostle N, Svátek M, Kvasnica J, Milodowski D, Jucker T, Ewers RM, Zhang Y, Johnson D, Teh YA, Burslem DFRP, Malhi Y, Coomes D. Imaging spectroscopy reveals the effects of topography and logging on the leaf chemistry of tropical forest canopy trees. Glob Chang Biol 2020; 26:989-1002. [PMID: 31845482 PMCID: PMC7027875 DOI: 10.1111/gcb.14903] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Accepted: 10/03/2019] [Indexed: 05/31/2023]
Abstract
Logging, pervasive across the lowland tropics, affects millions of hectares of forest, yet its influence on nutrient cycling remains poorly understood. One hypothesis is that logging influences phosphorus (P) cycling, because this scarce nutrient is removed in extracted timber and eroded soil, leading to shifts in ecosystem functioning and community composition. However, testing this is challenging because P varies within landscapes as a function of geology, topography and climate. Superimposed upon these trends are compositional changes in logged forests, with species with more acquisitive traits, characterized by higher foliar P concentrations, more dominant. It is difficult to resolve these patterns using traditional field approaches alone. Here, we use airborne light detection and ranging-guided hyperspectral imagery to map foliar nutrient (i.e. P, nitrogen [N]) concentrations, calibrated using field measured traits, over 400 km2 of northeastern Borneo, including a landscape-level disturbance gradient spanning old-growth to repeatedly logged forests. The maps reveal that canopy foliar P and N concentrations decrease with elevation. These relationships were not identified using traditional field measurements of leaf and soil nutrients. After controlling for topography, canopy foliar nutrient concentrations were lower in logged forest than in old-growth areas, reflecting decreased nutrient availability. However, foliar nutrient concentrations and specific leaf area were greatest in relatively short patches in logged areas, reflecting a shift in composition to pioneer species with acquisitive traits. N:P ratio increased in logged forest, suggesting reduced soil P availability through disturbance. Through the first landscape scale assessment of how functional leaf traits change in response to logging, we find that differences from old-growth forest become more pronounced as logged forests increase in stature over time, suggesting exacerbated phosphorus limitation as forests recover.
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Affiliation(s)
- Tom Swinfield
- Forest Ecology and Conservation GroupDepartment of Plant SciencesUniversity of CambridgeCambridgeUK
- Centre for Conservation ScienceRoyal Society for the Protection of BirdsCambridgeUK
| | - Sabine Both
- School of Biological SciencesUniversity of AberdeenAberdeenUK
- Environmental and Rural ScienceUniversity of New EnglandArmidaleNSWAustralia
| | - Terhi Riutta
- Environmental Change InstituteSchool of Geography and the EnvironmentUniversity of OxfordOxfordUK
| | - Boris Bongalov
- Forest Ecology and Conservation GroupDepartment of Plant SciencesUniversity of CambridgeCambridgeUK
| | - Dafydd Elias
- Centre for Ecology & HydrologyLancaster Environment CentreLancasterUK
- Lancaster Environment CentreLancaster UniversityLancasterUK
| | | | - Nicholas Ostle
- Lancaster Environment CentreLancaster UniversityLancasterUK
| | - Martin Svátek
- Department of Forest Botany, Dendrology and GeobiocoenologyFaculty of Forestry and Wood TechnologyMendel University in BrnoBrnoCzech Republic
| | - Jakub Kvasnica
- Department of Forest Botany, Dendrology and GeobiocoenologyFaculty of Forestry and Wood TechnologyMendel University in BrnoBrnoCzech Republic
| | - David Milodowski
- School of GeoSciencesUniversity of EdinburghEdinburghUK
- National Centre for Earth ObservationUniversity of EdinburghEdinburghUK
| | - Tommaso Jucker
- School of Biological SciencesUniversity of BristolBristolUK
| | | | - Yi Zhang
- Forest Ecology and Conservation GroupDepartment of Plant SciencesUniversity of CambridgeCambridgeUK
| | - David Johnson
- School of Earth and Environmental SciencesThe University of ManchesterManchesterUK
| | - Yit Arn Teh
- School of Biological SciencesUniversity of AberdeenAberdeenUK
| | | | - Yadvinder Malhi
- Environmental Change InstituteSchool of Geography and the EnvironmentUniversity of OxfordOxfordUK
| | - David Coomes
- Forest Ecology and Conservation GroupDepartment of Plant SciencesUniversity of CambridgeCambridgeUK
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23
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Laliberté E, Schweiger AK, Legendre P. Partitioning plant spectral diversity into alpha and beta components. Ecol Lett 2020; 23:370-380. [PMID: 31773839 PMCID: PMC7027829 DOI: 10.1111/ele.13429] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Revised: 10/21/2019] [Accepted: 10/27/2019] [Indexed: 02/01/2023]
Abstract
Plant spectral diversity - how plants differentially interact with solar radiation - is an integrator of plant chemical, structural, and taxonomic diversity that can be remotely sensed. We propose to measure spectral diversity as spectral variance, which allows the partitioning of the spectral diversity of a region, called spectral gamma (γ) diversity, into additive alpha (α; within communities) and beta (β; among communities) components. Our method calculates the contributions of individual bands or spectral features to spectral γ-, β-, and α-diversity, as well as the contributions of individual plant communities to spectral diversity. We present two case studies illustrating how our approach can identify 'hotspots' of spectral α-diversity within a region, and discover spectrally unique areas that contribute strongly to β-diversity. Partitioning spectral diversity and mapping its spatial components has many applications for conservation since high local diversity and distinctiveness in composition are two key criteria used to determine the ecological value of ecosystems.
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Affiliation(s)
- Etienne Laliberté
- Institut de recherche en biologie végétaleUniversité de Montréal4101 Sherbrooke EstMontréalQCH1X 2B2Canada
- Département de sciences biologiquesUniversité de MontréalC. P. 6128, succursale Centre‐villeMontréalQCH3C 3J7Canada
| | - Anna K. Schweiger
- Institut de recherche en biologie végétaleUniversité de Montréal4101 Sherbrooke EstMontréalQCH1X 2B2Canada
- Département de sciences biologiquesUniversité de MontréalC. P. 6128, succursale Centre‐villeMontréalQCH3C 3J7Canada
| | - Pierre Legendre
- Département de sciences biologiquesUniversité de MontréalC. P. 6128, succursale Centre‐villeMontréalQCH3C 3J7Canada
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24
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Liu B, Li R, Li H, You G, Yan S, Tong Q. Crop/Weed Discrimination Using a Field Imaging Spectrometer System. Sensors (Basel) 2019; 19:s19235154. [PMID: 31775304 PMCID: PMC6928640 DOI: 10.3390/s19235154] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Revised: 11/14/2019] [Accepted: 11/21/2019] [Indexed: 11/16/2022]
Abstract
Nowadays, sensors begin to play an essential role in smart-agriculture practices. Spectroscopy and the ground-based sensors have inspired widespread interest in the field of weed detection. Most studies focused on detection under ideal conditions, such as indoor or under artificial lighting, and more studies in the actual field environment are needed to test the applicability of this sensor technology. Meanwhile, hyperspectral image data collected by imaging spectrometer often has hundreds of channels and, thus, are large in size and highly redundant in information. Therefore, a key element in this application is to perform dimensionality reduction and feature extraction. However, the processing of highly dimensional spectral imaging data has not been given due attention in recent studies. In this study, a field imaging spectrometer system (FISS; 380-870 nm and 344 bands) was designed and used to discriminate carrot and three weed species (purslane, humifuse, and goosegrass) in the crop field. Dimensionality reduction was performed on the spectral data based on wavelet transform; the wavelet coefficients were extracted and used as the classification features in the weed detection model, and the results were compared with those obtained by using spectral bands as the classification feature. The classification features were selected using Wilks' statistic-based stepwise selection, and the results of Fisher linear discriminant analysis (LDA) and the highly dimensional data processing-oriented support vector machine (SVM) were compared. The results indicated that multiclass discrimination among weeds or between crops and weeds can be achieved using a limited number of spectral bands (8 bands) with an overall classification accuracy of greater than 85%. When the number of spectral bands increased to 15, the classification accuracy was improved to greater than 90%; further increasing the number of bands did not significantly improve the accuracy. Bands in the red edge region of plant spectra had strong discriminant capability. In terms of classification features, wavelet coefficients outperformed raw spectral bands when there were a limited number of variables. However, the difference between the two was minimal when the number of variables increased to a certain level. Among different discrimination methods, SVM, which is capable of nonlinear classification, performed better.
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Affiliation(s)
- Bo Liu
- School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China;
| | - Ru Li
- Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China; (R.L.); (Q.T.)
| | - Haidong Li
- Nanjing Institute of Environmental Sciences, Ministry of Environmental Protection, Nanjing 210042, China; (H.L.); (G.Y.)
| | - Guangyong You
- Nanjing Institute of Environmental Sciences, Ministry of Environmental Protection, Nanjing 210042, China; (H.L.); (G.Y.)
| | - Shouguang Yan
- Nanjing Institute of Environmental Sciences, Ministry of Environmental Protection, Nanjing 210042, China; (H.L.); (G.Y.)
- Correspondence: ; Tel.: +86-025-85287056
| | - Qingxi Tong
- Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China; (R.L.); (Q.T.)
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25
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Yesilkoy F. Optical Interrogation Techniques for Nanophotonic Biochemical Sensors. Sensors (Basel) 2019; 19:s19194287. [PMID: 31623315 PMCID: PMC6806184 DOI: 10.3390/s19194287] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 09/25/2019] [Accepted: 09/27/2019] [Indexed: 12/14/2022]
Abstract
The manipulation of light via nanoengineered surfaces has excited the optical community in the past few decades. Among the many applications enabled by nanophotonic devices, sensing has stood out due to their capability of identifying miniscule refractive index changes. In particular, when free-space propagating light effectively couples into subwavelength volumes created by nanostructures, the strongly-localized near-fields can enhance light’s interaction with matter at the nanoscale. As a result, nanophotonic sensors can non-destructively detect chemical species in real-time without the need of exogenous labels. The impact of such nanophotonic devices on biochemical sensor development became evident as the ever-growing research efforts in the field started addressing many critical needs in biomedical sciences, such as low-cost analytical platforms, simple quantitative bioassays, time-resolved sensing, rapid and multiplexed detection, single-molecule analytics, among others. In this review, the optical transduction methods used to interrogate optical resonances of nanophotonic sensors will be highlighted. Specifically, the optical methodologies used thus far will be evaluated based on their capability of addressing key requirements of the future sensor technologies, including miniaturization, multiplexing, spatial and temporal resolution, cost and sensitivity.
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Affiliation(s)
- Filiz Yesilkoy
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA.
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26
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Kellner JR, Albert LP, Burley JT, Cushman KC. The case for remote sensing of individual plants. Am J Bot 2019; 106:1139-1142. [PMID: 31469408 DOI: 10.1002/ajb2.1347] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Accepted: 06/29/2019] [Indexed: 06/10/2023]
Affiliation(s)
- James R Kellner
- Department of Ecology and Evolutionary Biology, Brown University, Providence, RI, 02912, USA
- Institute at Brown for Environment and Society, Brown University, Providence, RI, 02912, USA
| | - Loren P Albert
- Department of Ecology and Evolutionary Biology, Brown University, Providence, RI, 02912, USA
- Institute at Brown for Environment and Society, Brown University, Providence, RI, 02912, USA
| | - John T Burley
- Department of Ecology and Evolutionary Biology, Brown University, Providence, RI, 02912, USA
- Institute at Brown for Environment and Society, Brown University, Providence, RI, 02912, USA
| | - K C Cushman
- Department of Ecology and Evolutionary Biology, Brown University, Providence, RI, 02912, USA
- Institute at Brown for Environment and Society, Brown University, Providence, RI, 02912, USA
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27
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DuBois S, Desai AR, Singh A, Serbin SP, Goulden ML, Baldocchi DD, Ma S, Oechel WC, Wharton S, Kruger EL, Townsend PA. Using imaging spectroscopy to detect variation in terrestrial ecosystem productivity across a water-stressed landscape. Ecol Appl 2018; 28:1313-1324. [PMID: 29694698 DOI: 10.1002/eap.1733] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2017] [Revised: 01/30/2018] [Accepted: 03/14/2018] [Indexed: 06/08/2023]
Abstract
A central challenge to understanding how climate anomalies, such as drought and heatwaves, impact the terrestrial carbon cycle, is quantification and scaling of spatial and temporal variation in ecosystem gross primary productivity (GPP). Existing empirical and model-based satellite broadband spectra-based products have been shown to miss critical variation in GPP. Here, we evaluate the potential of high spectral resolution (10 nm) shortwave (400-2,500 nm) imagery to better detect spatial and temporal variations in GPP across a range of ecosystems, including forests, grassland-savannas, wetlands, and shrublands in a water-stressed region. Estimates of GPP from eddy covariance observations were compared against airborne hyperspectral imagery, collected across California during the 2013-2014 HyspIRI airborne preparatory campaign. Observations from 19 flux towers across 23 flight campaigns (102 total image-flux tower pairs) showed GPP to be strongly correlated to a suite of spectral wavelengths and band ratios associated with foliar physiology and chemistry. A partial least squares regression (PLSR) modeling approach was then used to predict GPP with higher validation accuracy (adjusted R2 = 0.71) and low bias (0.04) compared to existing broadband approaches (e.g., adjusted R2 = 0.68 and bias = -5.71 with the Sims et al. model). Significant wavelengths contributing to the PLSR include those previously shown to coincide with Rubisco (wavelengths 1,680, 1,740, and 2,290 nm) and Vcmax (wavelengths 1,680, 1,722, 1,732, 1,760, and 2,300 nm). These results provide strong evidence that advances in satellite spectral resolution offer significant promise for improved satellite-based monitoring of GPP variability across a diverse range of terrestrial ecosystems.
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Affiliation(s)
- Sean DuBois
- ICF, Fairfax, Virginia, 22031, USA
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA
- Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA
| | - Ankur R Desai
- Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA
| | - Aditya Singh
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA
- Department of Agricultural and Biological Engineering, University of Florida, Gainesville, Florida, 32611, USA
| | - Shawn P Serbin
- Environment and Climate Sciences Department, Brookhaven National Laboratory, Upton, New York, 11973, USA
| | - Michael L Goulden
- Department of Earth System Science, University of California-Irvine, Irvine, California, 92697, USA
| | - Dennis D Baldocchi
- Department of Environmental Science, Policy, and Management, University of California-Berkeley, Berkeley, California, 94720, USA
| | - Siyan Ma
- Department of Environmental Science, Policy, and Management, University of California-Berkeley, Berkeley, California, 94720, USA
| | - Walter C Oechel
- Department of Biology, San Diego State University, San Diego, California, 92182, USA
- Department of Geography, University of Exeter, Exeter, EX4 4QD, UK
| | - Sonia Wharton
- Atmospheric, Earth and Energy Division, Lawrence Livermore National Laboratory, Livermore, California, 94550, USA
| | - Eric L Kruger
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA
| | - Philip A Townsend
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA
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28
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Wang R, Gamon JA, Cavender-Bares J, Townsend PA, Zygielbaum AI. The spatial sensitivity of the spectral diversity-biodiversity relationship: an experimental test in a prairie grassland. Ecol Appl 2018; 28:541-556. [PMID: 29266500 DOI: 10.1002/eap.1669] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Revised: 05/12/2017] [Accepted: 05/26/2017] [Indexed: 06/07/2023]
Abstract
Remote sensing has been used to detect plant biodiversity in a range of ecosystems based on the varying spectral properties of different species or functional groups. However, the most appropriate spatial resolution necessary to detect diversity remains unclear. At coarse resolution, differences among spectral patterns may be too weak to detect. In contrast, at fine resolution, redundant information may be introduced. To explore the effect of spatial resolution, we studied the scale dependence of spectral diversity in a prairie ecosystem experiment at Cedar Creek Ecosystem Science Reserve, Minnesota, USA. Our study involved a scaling exercise comparing synthetic pixels resampled from high-resolution images within manipulated diversity treatments. Hyperspectral data were collected using several instruments on both ground and airborne platforms. We used the coefficient of variation (CV) of spectral reflectance in space as the indicator of spectral diversity and then compared CV at different scales ranging from 1 mm2 to 1 m2 to conventional biodiversity metrics, including species richness, Shannon's index, Simpson's index, phylogenetic species variation, and phylogenetic species evenness. In this study, higher species richness plots generally had higher CV. CV showed higher correlations with Shannon's index and Simpson's index than did species richness alone, indicating evenness contributed to the spectral diversity. Correlations with species richness and Simpson's index were generally higher than with phylogenetic species variation and evenness measured at comparable spatial scales, indicating weaker relationships between spectral diversity and phylogenetic diversity metrics than with species diversity metrics. High resolution imaging spectrometer data (1 mm2 pixels) showed the highest sensitivity to diversity level. With decreasing spatial resolution, the difference in CV between diversity levels decreased and greatly reduced the optical detectability of biodiversity. The optimal pixel size for distinguishing α diversity in these prairie plots appeared to be around 1 mm to 10 cm, a spatial scale similar to the size of an individual herbaceous plant. These results indicate a strong scale-dependence of the spectral diversity-biodiversity relationships, with spectral diversity best able to detect a combination of species richness and evenness, and more weakly detecting phylogenetic diversity. These findings can be used to guide airborne studies of biodiversity and develop more effective large-scale biodiversity sampling methods.
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Affiliation(s)
- Ran Wang
- Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, Alberta, T6G 2E3, Canada
| | - John A Gamon
- Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, Alberta, T6G 2E3, Canada
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, T6G 2E9, Canada
- School of Natural Resources, University of Nebraska, Lincoln, Nebraska, 68583, USA
| | - Jeannine Cavender-Bares
- Department of Ecology, Evolution and Behavior, University of Minnesota, Saint Paul, Minnesota, 55108, USA
| | - Philip A Townsend
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA
| | - Arthur I Zygielbaum
- School of Natural Resources, University of Nebraska, Lincoln, Nebraska, 68583, USA
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29
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Paz-Kagan T, Brodrick PG, Vaughn NR, Das AJ, Stephenson NL, Nydick KR, Asner GP. What mediates tree mortality during drought in the southern Sierra Nevada? Ecol Appl 2017; 27:2443-2457. [PMID: 28871610 DOI: 10.1002/eap.1620] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2017] [Revised: 07/13/2017] [Accepted: 07/18/2017] [Indexed: 06/07/2023]
Abstract
Severe drought has the potential to cause selective mortality within a forest, thereby inducing shifts in forest species composition. The southern Sierra Nevada foothills and mountains of California have experienced extensive forest dieback due to drought stress and insect outbreak. We used high-fidelity imaging spectroscopy (HiFIS) and light detection and ranging (LiDAR) from the Carnegie Airborne Observatory (CAO) to estimate the effect of forest dieback on species composition in response to drought stress in Sequoia National Park. Our aims were (1) to quantify site-specific conditions that mediate tree mortality along an elevation gradient in the southern Sierra Nevada Mountains, (2) to assess where mortality events have a greater probability of occurring, and (3) to estimate which tree species have a greater likelihood of mortality along the elevation gradient. A series of statistical models were generated to classify species composition and identify tree mortality, and the influences of different environmental factors were spatially quantified and analyzed to assess where mortality events have a greater likelihood of occurring. A higher probability of mortality was observed in the lower portion of the elevation gradient, on southwest- and west-facing slopes, in areas with shallow soils, on shallower slopes, and at greater distances from water. All of these factors are related to site water balance throughout the landscape. Our results also suggest that mortality is species-specific along the elevation gradient, mainly affecting Pinus ponderosa and Pinus lambertiana at lower elevations. Selective mortality within the forest may drive long-term shifts in community composition along the elevation gradient.
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Affiliation(s)
- Tarin Paz-Kagan
- Department of Global Ecology, Carnegie Institution for Science, Stanford, California, 94305, USA
| | - Philip G Brodrick
- Department of Global Ecology, Carnegie Institution for Science, Stanford, California, 94305, USA
| | - Nicholas R Vaughn
- Department of Global Ecology, Carnegie Institution for Science, Stanford, California, 94305, USA
| | - Adrian J Das
- U.S. Geological Survey, Western Ecological Research Center, Three Rivers, California, 93271, USA
| | - Nathan L Stephenson
- U.S. Geological Survey, Western Ecological Research Center, Three Rivers, California, 93271, USA
| | - Koren R Nydick
- Sequoia and Kings Canyon National Parks, Three Rivers, California, 93271, USA
| | - Gregory P Asner
- Department of Global Ecology, Carnegie Institution for Science, Stanford, California, 94305, USA
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30
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Paz-Kagan T, Asner GP. Drivers of woody canopy water content responses to drought in a Mediterranean-type ecosystem. Ecol Appl 2017; 27:2220-2233. [PMID: 28727205 DOI: 10.1002/eap.1603] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2016] [Revised: 05/01/2017] [Accepted: 06/20/2017] [Indexed: 06/07/2023]
Abstract
Severe droughts increase physiological stress in woody plant species, which can lead to mortality, fundamentally altering the composition, structure, and biogeography of forests in many regions. Little is known, however, about the factors determining the physiological response of woody plants to drought at landscape scales. Our objective was to understand woody plant species responses to ongoing changes in climate, using remotely sensed canopy water content (CWC) as an indicator of plant physiological and phenological status. We used fused imaging spectroscopy and light detection and ranging from the Carnegie Airborne Observatory to quantify the factors affecting species compositional changes in CWC in a diverse Mediterranean-type ecosystem (Jasper Ridge Biological Preserve, California, USA) between 2013 and 2015. Mapped CWC was spatially variable in both of the observation years, and proved to be most closely tied to species composition and distribution across the landscape. The secondary predictors of CWC were elevation and soil substrate. In contrast, we found that CWC change was much more related to environmental factors than to the species composition. We suggest that the effect of environment on CWC change is mediated through species resistance and resilience to drought. Monitoring CWC change with imaging spectroscopy is a powerful approach to identifying species-level responses to climatic events and long-term change, which may provide support for policy decisions and conservation at large spatial scales.
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Affiliation(s)
- Tarin Paz-Kagan
- Department of Global Ecology, Carnegie Institution for Science, Stanford, California, 94305, USA
| | - Gregory P Asner
- Department of Global Ecology, Carnegie Institution for Science, Stanford, California, 94305, USA
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31
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Rogass C, Koerting FM, Mielke C, Brell M, Boesche NK, Bade M, Hohmann C. Translational Imaging Spectroscopy for Proximal Sensing. Sensors (Basel) 2017; 17:s17081857. [PMID: 28800111 PMCID: PMC5579726 DOI: 10.3390/s17081857] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/13/2017] [Revised: 08/07/2017] [Accepted: 08/08/2017] [Indexed: 11/25/2022]
Abstract
Proximal sensing as the near field counterpart of remote sensing offers a broad variety of applications. Imaging spectroscopy in general and translational laboratory imaging spectroscopy in particular can be utilized for a variety of different research topics. Geoscientific applications require a precise pre-processing of hyperspectral data cubes to retrieve at-surface reflectance in order to conduct spectral feature-based comparison of unknown sample spectra to known library spectra. A new pre-processing chain called GeoMAP-Trans for at-surface reflectance retrieval is proposed here as an analogue to other algorithms published by the team of authors. It consists of a radiometric, a geometric and a spectral module. Each module consists of several processing steps that are described in detail. The processing chain was adapted to the broadly used HySPEX VNIR/SWIR imaging spectrometer system and tested using geological mineral samples. The performance was subjectively and objectively evaluated using standard artificial image quality metrics and comparative measurements of mineral and Lambertian diffuser standards with standard field and laboratory spectrometers. The proposed algorithm provides highly qualitative results, offers broad applicability through its generic design and might be the first one of its kind to be published. A high radiometric accuracy is achieved by the incorporation of the Reduction of Miscalibration Effects (ROME) framework. The geometric accuracy is higher than 1 μpixel. The critical spectral accuracy was relatively estimated by comparing spectra of standard field spectrometers to those from HySPEX for a Lambertian diffuser. The achieved spectral accuracy is better than 0.02% for the full spectrum and better than 98% for the absorption features. It was empirically shown that point and imaging spectrometers provide different results for non-Lambertian samples due to their different sensing principles, adjacency scattering impacts on the signal and anisotropic surface reflection properties.
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Affiliation(s)
- Christian Rogass
- Section 1.4 Remote Sensing, Helmholtz Centre Potsdam-GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany.
| | - Friederike M Koerting
- Section 1.4 Remote Sensing, Helmholtz Centre Potsdam-GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany.
| | - Christian Mielke
- Section 1.4 Remote Sensing, Helmholtz Centre Potsdam-GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany.
| | - Maximilian Brell
- Section 1.4 Remote Sensing, Helmholtz Centre Potsdam-GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany.
| | - Nina K Boesche
- Section 1.4 Remote Sensing, Helmholtz Centre Potsdam-GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany.
| | - Maria Bade
- Section 1.4 Remote Sensing, Helmholtz Centre Potsdam-GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany.
| | - Christian Hohmann
- Section 1.4 Remote Sensing, Helmholtz Centre Potsdam-GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany.
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Jilge M, Heiden U, Habermeyer M, Mende A, Juergens C. Detecting Unknown Artificial Urban Surface Materials Based on Spectral Dissimilarity Analysis. Sensors (Basel) 2017; 17:s17081826. [PMID: 28786947 PMCID: PMC5579714 DOI: 10.3390/s17081826] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/31/2017] [Revised: 08/04/2017] [Accepted: 08/06/2017] [Indexed: 11/16/2022]
Abstract
High resolution imaging spectroscopy data have been recognised as a valuable data resource for augmenting detailed material inventories that serve as input for various urban applications. Image-specific urban spectral libraries are successfully used in urban imaging spectroscopy studies. However, the regional- and sensor-specific transferability of such libraries is limited due to the wide range of different surface materials. With the developed methodology, incomplete urban spectral libraries can be utilised by assuming that unknown surface material spectra are dissimilar to the known spectra in a basic spectral library (BSL). The similarity measure SID-SCA (Spectral Information Divergence-Spectral Correlation Angle) is applied to detect image-specific unknown urban surfaces while avoiding spectral mixtures. These detected unknown materials are categorised into distinct and identifiable material classes based on their spectral and spatial metrics. Experimental results demonstrate a successful redetection of material classes that had been previously erased in order to simulate an incomplete BSL. Additionally, completely new materials e.g., solar panels were identified in the data. It is further shown that the level of incompleteness of the BSL and the defined dissimilarity threshold are decisive for the detection of unknown material classes and the degree of spectral intra-class variability. A detailed accuracy assessment of the pre-classification results, aiming to separate natural and artificial materials, demonstrates spectral confusions between spectrally similar materials utilizing SID-SCA. However, most spectral confusions occur between natural or artificial materials which are not affecting the overall aim. The dissimilarity analysis overcomes the limitations of working with incomplete urban spectral libraries and enables the generation of image-specific training databases.
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Affiliation(s)
- Marianne Jilge
- Geomatics/Remote Sensing Group, Geography Department, Ruhr-University Bochum, Universitaetsstrasse 150, D-44780 Bochum, Germany.
| | - Uta Heiden
- German Aerospace Center (DLR), German Remote Sensing Data Center (DFD), Muenchner Strasse 20, D-82234 Wessling, Germany.
| | - Martin Habermeyer
- German Aerospace Center (DLR), German Remote Sensing Data Center (DFD), Muenchner Strasse 20, D-82234 Wessling, Germany.
| | - André Mende
- Administrative District Office Zwickau, Department for Surveying, Geodata Management, Scherbergplatz 4, D-08371 Glauchau, Germany.
| | - Carsten Juergens
- Geomatics/Remote Sensing Group, Geography Department, Ruhr-University Bochum, Universitaetsstrasse 150, D-44780 Bochum, Germany.
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Paz-Kagan T, Caras T, Herrmann I, Shachak M, Karnieli A. Multiscale mapping of species diversity under changed land use using imaging spectroscopy. Ecol Appl 2017; 27:1466-1484. [PMID: 28370671 DOI: 10.1002/eap.1540] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2016] [Revised: 11/29/2016] [Accepted: 12/13/2016] [Indexed: 06/07/2023]
Abstract
Land use changes are one of the most important factors causing environmental transformations and species diversity alterations. The aim of the current study was to develop a geoinformatics-based framework to quantify alpha and beta diversity indices in two sites in Israel with different land uses, i.e., an agricultural system of fruit orchards, an afforestation system of planted groves, and an unmanaged system of groves. The framework comprises four scaling steps: (1) classification of a tree species distribution (SD) map using imaging spectroscopy (IS) at a pixel size of 1 m; (2) estimation of local species richness by calculating the alpha diversity index for 30-m grid cells; (3) calculation of beta diversity for different land use categories and sub-categories at different sizes; and (4) calculation of the beta diversity difference between the two sites. The SD was classified based on a hyperspectral image with 448 bands within the 380-2500 nm spectral range and a spatial resolution of 1 m. Twenty-three tree species were classified with high overall accuracy values of 82.57% and 86.93% for the two sites. Significantly high values of the alpha index characterize the unmanaged land use, and the lowest values were calculated for the agricultural land use. In addition, high values of alpha indices were found at the borders between the polygons related to the "edge-effect" phenomenon, whereas low alpha indices were found in areas with high invasion species rates. The beta index value, calculated for 58 polygons, was significantly lower in the agricultural land use. The suggested framework of this study succeeded in quantifying land use effects on tree species distribution, evenness, and richness. IS and spatial statistics techniques offer an opportunity to study woody plant species variation with a multiscale approach that is useful for managing land use, especially under increasing environmental changes.
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Affiliation(s)
- Tarin Paz-Kagan
- Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boqer Campus, Midreshet Ben Gurion, 84990, Israel
| | - Tamir Caras
- Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boqer Campus, Midreshet Ben Gurion, 84990, Israel
| | - Ittai Herrmann
- Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boqer Campus, Midreshet Ben Gurion, 84990, Israel
| | - Moshe Shachak
- Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boqer Campus, Midreshet Ben Gurion, 84990, Israel
| | - Arnon Karnieli
- Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boqer Campus, Midreshet Ben Gurion, 84990, Israel
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Dahlin KM. Spectral diversity area relationships for assessing biodiversity in a wildland-agriculture matrix. Ecol Appl 2016; 26:2756-2766. [PMID: 27907259 DOI: 10.1002/eap.1390] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2015] [Revised: 04/15/2016] [Accepted: 05/31/2016] [Indexed: 06/06/2023]
Abstract
Species-area relationships have long been used to assess patterns of species diversity across scales. Here, this concept is extended to spectral diversity using hyperspectral data collected by NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) over western Michigan. This mixture of mesic forest and agricultural lands offers two end-points on the local-scale diversity continuum; one set of well-mixed forest patches and one set of highly homogeneous agricultural patches. Using the sum of the first three principal component values and the principal components' convex hull volume, spectral diversity was compared within and among these plots and to null expectations for perfectly random and perfectly patchy landscapes. Overall, the spectral diversity-area relationship confirms the patterns that would be expected for this landscape, but this application suggests that this approach could be extended to less well-understood landscapes and could reveal key insights about the relative importance of different drivers of community assembly, even in the absence of additional data about plant functional traits or species' identities.
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Affiliation(s)
- Kyla Marie Dahlin
- Department of Geography, Environment, and Spatial Sciences and Program in Ecology, Evolutionary Biology, and Behavior, Michigan State University, Geography Building, 673 Auditorium Road, East Lansing, Michigan, 48824, USA
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Chance CM, Coops NC, Plowright AA, Tooke TR, Christen A, Aven N. Invasive Shrub Mapping in an Urban Environment from Hyperspectral and LiDAR-Derived Attributes. Front Plant Sci 2016; 7:1528. [PMID: 27818664 PMCID: PMC5073150 DOI: 10.3389/fpls.2016.01528] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2016] [Accepted: 09/29/2016] [Indexed: 05/23/2023]
Abstract
Proactive management of invasive species in urban areas is critical to restricting their overall distribution. The objective of this work is to determine whether advanced remote sensing technologies can help to detect invasions effectively and efficiently in complex urban ecosystems such as parks. In Surrey, BC, Canada, Himalayan blackberry (Rubus armeniacus) and English ivy (Hedera helix) are two invasive shrub species that can negatively affect native ecosystems in cities and managed urban parks. Random forest (RF) models were created to detect these two species using a combination of hyperspectral imagery, and light detection and ranging (LiDAR) data. LiDAR-derived predictor variables included irradiance models, canopy structural characteristics, and orographic variables. RF detection accuracy ranged from 77.8 to 87.8% for Himalayan blackberry and 81.9 to 82.1% for English ivy, with open areas classified more accurately than areas under canopy cover. English ivy was predicted to occur across a greater area than Himalayan blackberry both within parks and across the entire city. Both Himalayan blackberry and English ivy were mostly located in clusters according to a Local Moran's I analysis. The occurrence of both species decreased as the distance from roads increased. This study shows the feasibility of producing highly accurate detection maps of plant invasions in urban environments using a fusion of remotely sensed data, as well as the ability to use these products to guide management decisions.
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Affiliation(s)
- Curtis M. Chance
- Department of Forest Resources Management, Faculty of Forestry, University of British ColumbiaVancouver, BC, Canada
| | - Nicholas C. Coops
- Department of Forest Resources Management, Faculty of Forestry, University of British ColumbiaVancouver, BC, Canada
| | - Andrew A. Plowright
- Department of Forest Resources Management, Faculty of Forestry, University of British ColumbiaVancouver, BC, Canada
| | | | - Andreas Christen
- Department of Geography, Faculty of Arts, University of British ColumbiaVancouver, BC, Canada
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Pinto F, Damm A, Schickling A, Panigada C, Cogliati S, Müller-Linow M, Balvora A, Rascher U. Sun-induced chlorophyll fluorescence from high-resolution imaging spectroscopy data to quantify spatio-temporal patterns of photosynthetic function in crop canopies. Plant Cell Environ 2016; 39:1500-12. [PMID: 26763162 DOI: 10.1111/pce.12710] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2015] [Revised: 12/29/2015] [Accepted: 12/30/2015] [Indexed: 05/04/2023]
Abstract
Passive detection of sun-induced chlorophyll fluorescence (SIF) using spectroscopy has been proposed as a proxy to quantify changes in photochemical efficiency at canopy level under natural light conditions. In this study, we explored the use of imaging spectroscopy to quantify spatio-temporal dynamics of SIF within crop canopies and its sensitivity to track patterns of photosynthetic activity originating from the interaction between vegetation structure and incoming radiation as well as variations in plant function. SIF was retrieved using the Fraunhofer Line Depth (FLD) principle from imaging spectroscopy data acquired at different time scales a few metres above several crop canopies growing under natural illumination. We report the first maps of canopy SIF in high spatial resolution. Changes of SIF were monitored at different time scales ranging from quick variations under induced stress conditions to seasonal dynamics. Natural changes were primarily determined by varying levels and distribution of photosynthetic active radiation (PAR). However, this relationship changed throughout the day demonstrating an additional physiological component modulating spatio-temporal patterns of SIF emission. We successfully used detailed SIF maps to track changes in the canopy's photochemical activity under field conditions, providing a new tool to evaluate complex patterns of photosynthesis within the canopy.
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Affiliation(s)
- Francisco Pinto
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52428, Jülich, Germany
| | - Alexander Damm
- Remote Sensing Laboratories, Department of Geography, University of Zurich, 8057, Zürich, Switzerland
| | - Anke Schickling
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52428, Jülich, Germany
| | - Cinzia Panigada
- Remote Sensing of Environmental Dynamics Laboratory, Department of Earth and Environmental Science (DISAT), University of Milano-Bicocca, 20126, Milan, Italy
| | - Sergio Cogliati
- Remote Sensing of Environmental Dynamics Laboratory, Department of Earth and Environmental Science (DISAT), University of Milano-Bicocca, 20126, Milan, Italy
| | - Mark Müller-Linow
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52428, Jülich, Germany
| | - Agim Balvora
- INRES-Plant Breeding, University of Bonn, 53115, Bonn, Germany
- Experimental Station of University of Bonn in Klein-Altendorf, 53359, Rheinbach, Germany
| | - Uwe Rascher
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, 52428, Jülich, Germany
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37
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Asner GP, Brodrick PG, Anderson CB, Vaughn N, Knapp DE, Martin RE. Progressive forest canopy water loss during the 2012-2015 California drought. Proc Natl Acad Sci U S A 2016; 113:E249-55. [PMID: 26712020 DOI: 10.1073/pnas.1523397113] [Citation(s) in RCA: 109] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The 2012-2015 drought has left California with severely reduced snowpack, soil moisture, ground water, and reservoir stocks, but the impact of this estimated millennial-scale event on forest health is unknown. We used airborne laser-guided spectroscopy and satellite-based models to assess losses in canopy water content of California's forests between 2011 and 2015. Approximately 10.6 million ha of forest containing up to 888 million large trees experienced measurable loss in canopy water content during this drought period. Severe canopy water losses of greater than 30% occurred over 1 million ha, affecting up to 58 million large trees. Our measurements exclude forests affected by fire between 2011 and 2015. If drought conditions continue or reoccur, even with temporary reprieves such as El Niño, we predict substantial future forest change.
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38
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Rascher U, Alonso L, Burkart A, Cilia C, Cogliati S, Colombo R, Damm A, Drusch M, Guanter L, Hanus J, Hyvärinen T, Julitta T, Jussila J, Kataja K, Kokkalis P, Kraft S, Kraska T, Matveeva M, Moreno J, Muller O, Panigada C, Pikl M, Pinto F, Prey L, Pude R, Rossini M, Schickling A, Schurr U, Schüttemeyer D, Verrelst J, Zemek F. Sun-induced fluorescence - a new probe of photosynthesis: First maps from the imaging spectrometer HyPlant. Glob Chang Biol 2015; 21:4673-84. [PMID: 26146813 DOI: 10.1111/gcb.13017] [Citation(s) in RCA: 68] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2014] [Accepted: 05/26/2015] [Indexed: 05/27/2023]
Abstract
Variations in photosynthesis still cause substantial uncertainties in predicting photosynthetic CO2 uptake rates and monitoring plant stress. Changes in actual photosynthesis that are not related to greenness of vegetation are difficult to measure by reflectance based optical remote sensing techniques. Several activities are underway to evaluate the sun-induced fluorescence signal on the ground and on a coarse spatial scale using space-borne imaging spectrometers. Intermediate-scale observations using airborne-based imaging spectroscopy, which are critical to bridge the existing gap between small-scale field studies and global observations, are still insufficient. Here we present the first validated maps of sun-induced fluorescence in that critical, intermediate spatial resolution, employing the novel airborne imaging spectrometer HyPlant. HyPlant has an unprecedented spectral resolution, which allows for the first time quantifying sun-induced fluorescence fluxes in physical units according to the Fraunhofer Line Depth Principle that exploits solar and atmospheric absorption bands. Maps of sun-induced fluorescence show a large spatial variability between different vegetation types, which complement classical remote sensing approaches. Different crop types largely differ in emitting fluorescence that additionally changes within the seasonal cycle and thus may be related to the seasonal activation and deactivation of the photosynthetic machinery. We argue that sun-induced fluorescence emission is related to two processes: (i) the total absorbed radiation by photosynthetically active chlorophyll; and (ii) the functional status of actual photosynthesis and vegetation stress.
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Affiliation(s)
- U Rascher
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Leo-Brandt-Str., 52425, Jülich, Germany
| | - L Alonso
- Department of Earth Physics and Thermodynamics, University of Valencia, Dr Moliner 50 46100 Burjassot, Valencia, Spain
| | - A Burkart
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Leo-Brandt-Str., 52425, Jülich, Germany
| | - C Cilia
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Leo-Brandt-Str., 52425, Jülich, Germany
- Remote Sensing of Environmental Dynamics Lab, DISAT, Università degli Studi Milano-Bicocca, Milano, Italy
| | - S Cogliati
- Remote Sensing of Environmental Dynamics Lab, DISAT, Università degli Studi Milano-Bicocca, Milano, Italy
| | - R Colombo
- Remote Sensing of Environmental Dynamics Lab, DISAT, Università degli Studi Milano-Bicocca, Milano, Italy
| | - A Damm
- Remote Sensing Laboratories, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland
| | - M Drusch
- European Space Agency (ESA), ESTEC, Keplerlaan 1, 2200 AG, Noordwijk, the Netherlands
| | - L Guanter
- Institute for Space Sciences, Free University of Berlin, Carl-Heinrich-Becker-Weg 6-10, 12165, Berlin, Germany
| | - J Hanus
- Global Change Research Centre AS CR, Bělidla 986/4a, 603 00, Brno, Czech Republic
| | - T Hyvärinen
- Specim Spectral Imaging Ltd., Teknologiantie 18A, 90590, Oulu, Finland
| | - T Julitta
- Remote Sensing of Environmental Dynamics Lab, DISAT, Università degli Studi Milano-Bicocca, Milano, Italy
| | - J Jussila
- Specim Spectral Imaging Ltd., Teknologiantie 18A, 90590, Oulu, Finland
| | - K Kataja
- Specim Spectral Imaging Ltd., Teknologiantie 18A, 90590, Oulu, Finland
| | - P Kokkalis
- Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, National Observatory of Athens, 15236, Athens, Greece
| | - S Kraft
- European Space Agency (ESA), ESTEC, Keplerlaan 1, 2200 AG, Noordwijk, the Netherlands
| | - T Kraska
- Field Lab Campus Klein-Altendorf, Agricultural Faculty, University of Bonn, Klein-Altendorf 3, 53359, Rheinbach, Germany
| | - M Matveeva
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Leo-Brandt-Str., 52425, Jülich, Germany
| | - J Moreno
- Department of Earth Physics and Thermodynamics, University of Valencia, Dr Moliner 50 46100 Burjassot, Valencia, Spain
| | - O Muller
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Leo-Brandt-Str., 52425, Jülich, Germany
| | - C Panigada
- Remote Sensing of Environmental Dynamics Lab, DISAT, Università degli Studi Milano-Bicocca, Milano, Italy
| | - M Pikl
- Global Change Research Centre AS CR, Bělidla 986/4a, 603 00, Brno, Czech Republic
| | - F Pinto
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Leo-Brandt-Str., 52425, Jülich, Germany
| | - L Prey
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Leo-Brandt-Str., 52425, Jülich, Germany
| | - R Pude
- Field Lab Campus Klein-Altendorf, Agricultural Faculty, University of Bonn, Klein-Altendorf 3, 53359, Rheinbach, Germany
| | - M Rossini
- Remote Sensing of Environmental Dynamics Lab, DISAT, Università degli Studi Milano-Bicocca, Milano, Italy
| | - A Schickling
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Leo-Brandt-Str., 52425, Jülich, Germany
| | - U Schurr
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Leo-Brandt-Str., 52425, Jülich, Germany
| | - D Schüttemeyer
- European Space Agency (ESA), ESTEC, Keplerlaan 1, 2200 AG, Noordwijk, the Netherlands
| | - J Verrelst
- Department of Earth Physics and Thermodynamics, University of Valencia, Dr Moliner 50 46100 Burjassot, Valencia, Spain
| | - F Zemek
- Global Change Research Centre AS CR, Bělidla 986/4a, 603 00, Brno, Czech Republic
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Abstract
Understanding how and why plant communities vary across space has long been a goal of ecology, yet parsing the relative importance of different influences has remained a challenge. Species-specific models are not generalizable, whereas broad plant functional type models lack important detail. Here we consider plant trait patterns at the local scale and ask whether plant chemical traits are more closely linked to environmental gradients or to changes in species composition. We used the visible-to-shortwave infrared (VSWIR) spectrometer of the Carnegie Airborne Observatory to develop maps of four plant chemical traits--leaf nitrogen per mass, leaf carbon per mass, leaf water concentration, and canopy water content--across a diverse Mediterranean-type ecosystem (Jasper Ridge Biological Preserve, CA). For all four traits, plant community alone was the strongest predictor of trait variation (explaining 46-61% of the heterogeneity), whereas environmental gradients accounted for just one fourth of the variation in the traits. This result emphasizes the critical role that species composition plays in mediating nutrient and carbon cycling within and among different communities. Environmental filtering and limits to similarity can act strongly, simultaneously, in a spatially heterogeneous environment, but the local-scale environmental gradients alone cannot account for the variation across this landscape.
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Affiliation(s)
- Kyla M Dahlin
- Department of Biology, Stanford University, Stanford, CA 94305, USA.
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40
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Oppelt N, Mauser W. The Airborne Visible / Infrared Imaging Spectrometer AVIS: Design, Characterization and Calibration. Sensors (Basel) 2007; 7:1934-1953. [PMID: 28903206 PMCID: PMC3841855 DOI: 10.3390/s7091934] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/31/2007] [Accepted: 09/13/2007] [Indexed: 11/16/2022]
Abstract
The Airborne Visible / Infrared imaging Spectrometer AVIS is a hyperspectralimager designed for environmental monitoring purposes. The sensor, which wasconstructed entirely from commercially available components, has been successfullydeployed during several experiments between 1999 and 2007. We describe the instrumentdesign and present the results of laboratory characterization and calibration of the system'ssecond generation, AVIS-2, which is currently being operated. The processing of the datais described and examples of remote sensing reflectance data are presented.
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Affiliation(s)
- Natascha Oppelt
- Ludwig-Maximilians-Universität München, Dept. for Geography, Luisenstr. 37, 80333 Munich, Germany.
| | - Wolfram Mauser
- Ludwig-Maximilians-Universität München, Dept. for Geography, Luisenstr. 37, 80333 Munich, Germany.
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