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Kükenbrink D, Gardi O, Morsdorf F, Thürig E, Schellenberger A, Mathys L. Above-ground biomass references for urban trees from terrestrial laser scanning data. ANNALS OF BOTANY 2021; 128:709-724. [PMID: 33693550 PMCID: PMC8557373 DOI: 10.1093/aob/mcab002] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 01/07/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND AND AIMS Within extending urban areas, trees serve a multitude of functions (e.g. carbon storage, suppression of air pollution, mitigation of the 'heat island' effect, oxygen, shade and recreation). Many of these services are positively correlated with tree size and structure. The quantification of above-ground biomass (AGB) is of especial importance to assess its carbon storage potential. However, quantification of AGB is difficult and the allometries applied are often based on forest trees, which are subject to very different growing conditions, competition and form. In this article we highlight the potential of terrestrial laser scanning (TLS) techniques to extract highly detailed information on urban tree structure and AGB. METHODS Fifty-five urban trees distributed over seven cities in Switzerland were measured using TLS and traditional forest inventory techniques before they were felled and weighed. Tree structure, volume and AGB from the TLS point clouds were extracted using quantitative structure modelling. TLS-derived AGB estimates were compared with AGB estimates based on forest tree allometries dependent on diameter at breast height only. The correlations of various tree metrics as AGB predictors were assessed. KEY RESULTS Estimates of AGB derived by TLS showed good performance when compared with destructively harvested references, with an R2 of 0.954 (RMSE = 556 kg) compared with 0.837 (RMSE = 1159 kg) for allometrically derived AGB estimates. A correlation analysis showed that different TLS-derived wood volume estimates as well as trunk diameters and tree crown metrics show high correlation in describing total wood AGB, outperforming tree height. CONCLUSIONS Wood volume estimates based on TLS show high potential to estimate tree AGB independent of tree species, size and form. This allows us to retrieve highly accurate non-destructive AGB estimates that could be used to establish new allometric equations without the need for extensive destructive harvesting.
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Affiliation(s)
- Daniel Kükenbrink
- Swiss Federal Institute WSL, Zürichstrasse 111, CH-8903 Birmensdorf, Switzerland
- Remote Sensing Laboratories, University of Zurich, Winterthurerstrasse 190, CH-8045 Zurich, Switzerland
| | - Oliver Gardi
- School of Agricultural, Forest and Food Sciences HAFL, Länggasse 85, CH-3052 Zollikofen, Switzerland
| | - Felix Morsdorf
- Remote Sensing Laboratories, University of Zurich, Winterthurerstrasse 190, CH-8045 Zurich, Switzerland
| | - Esther Thürig
- Swiss Federal Institute WSL, Zürichstrasse 111, CH-8903 Birmensdorf, Switzerland
| | | | - Lukas Mathys
- Nategra LLC, Nydeggstalden 30, CH-3011 Bern, Switzerland
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Assessment of Above-Ground Carbon Storage by Urban Trees Using LiDAR Data: The Case of a University Campus. FORESTS 2021. [DOI: 10.3390/f12010062] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The biomass represented by urban trees is important for urban decision-makers, green space planners, and managers seeking to optimize urban ecosystem services. Carbon storage by urban trees is one of these services. Suitable methods for assessing carbon storage by urban trees are being explored. The latest technologies in remote sensing and data analyses can reduce data collection costs while improving accuracy. This paper introduces an assessment approach that combines ground measurements with unmanned aerial vehicle-based light detection and ranging (LiDAR) data to estimate carbon storage by urban trees. Methods underpinning the approach were tested for the case of the Vancouver campus of the University of British Columbia (UBC), Canada. The study objectives were (1) to test five automated individual tree detection (AITD) algorithms and select one on the basis of the highest segmentation accuracy, (2) to develop a model to estimate the diameter at breast height (DBH), and (3) to estimate and map carbon storage over the UBC campus using LiDAR heights, estimated DBHs, and an existing tree-level above-ground carbon estimation model. Of the segmentation algorithms tested, the Dalponte AITD had the highest F score of 0.83. Of the five CW thresholds (th) tested in the DBH estimation model, we chose one resulting in the lowest Akaike’s information criterion, the highest log-likelihood, and the lowest root-mean-squared error (19.55 cm). Above-ground carbon was estimated for each tree in the study area and subsequently summarized, resulting in an estimated 5.27 kg C·m−2 over the main campus of UBC, Vancouver. The approach could be used in other urban jurisdictions to obtain essential information on urban carbon storage in support of urban landscape governance, planning, and management.
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Smart N, Eisenman TS, Karvonen A. Street Tree Density and Distribution: An International Analysis of Five Capital Cities. Front Ecol Evol 2020. [DOI: 10.3389/fevo.2020.562646] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Municipal leaders around the world are demonstrating significant interest in urban greening to realize a range of socioecological benefits. The urban greening toolkit often includes street trees, an essential component of urban design informed by historic legacies of both human and environmental factors. To date, there has been little comparative analysis of street tree density and distribution across international and intercontinental settings, and associated research has not been situated within the broader discussion of historical legacies. This study focuses on five capital cities (Ottawa, Stockholm, Buenos Aires, Paris, and Washington, DC) situated in two climate zones and it addresses two research questions: (1) What are the density and distribution of street trees across a given city and its street hierarchy? and (2) How do these metrics compare within and between cities by climate zone? The analysis draws upon up-to-date datasets from local authorities and includes geospatial analysis of street trees across hierarchical street classes within the central zones of each city. The results show clear differences in street tree density in cities within and between climate zones as well as differences in street tree distribution in cities within the same climate zone. Substantial differences within climate zones further suggest that cultural factors—including but not limited to urban form, aesthetic norms, and governance regimes—may play a pivotal role in the distribution and density of street trees. This illustrates the importance of place-specific cultural and environmental legacies as determinants of street tree density and distribution and supports further comparative research on the topic.
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Abstract
Forests in Germany cover around 11.4 million hectares and, thus, a share of 32% of Germany’s surface area. Therefore, forests shape the character of the country’s cultural landscape. Germany’s forests fulfil a variety of functions for nature and society, and also play an important role in the context of climate levelling. Climate change, manifested via rising temperatures and current weather extremes, has a negative impact on the health and development of forests. Within the last five years, severe storms, extreme drought, and heat waves, and the subsequent mass reproduction of bark beetles have all seriously affected Germany’s forests. Facing the current dramatic extent of forest damage and the emerging long-term consequences, the effort to preserve forests in Germany, along with their diversity and productivity, is an indispensable task for the government. Several German ministries have and plan to initiate measures supporting forest health. Quantitative data is one means for sound decision-making to ensure the monitoring of the forest and to improve the monitoring of forest damage. In addition to existing forest monitoring systems, such as the federal forest inventory, the national crown condition survey, and the national forest soil inventory, systematic surveys of forest condition and vulnerability at the national scale can be expanded with the help of a satellite-based earth observation. In this review, we analysed and categorized all research studies published in the last 20 years that focus on the remote sensing of forests in Germany. For this study, 166 citation indexed research publications have been thoroughly analysed with respect to publication frequency, location of studies undertaken, spatial and temporal scale, coverage of the studies, satellite sensors employed, thematic foci of the studies, and overall outcomes, allowing us to identify major research and geoinformation product gaps.
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Abstract
As urban areas continue to expand and play a critical role as both contributors to climate change and hotspots of vulnerability to its effects, cities have become battlegrounds for climate change adaptation and mitigation. Large amounts of earth observations from space have been collected over the last five decades and while most of the measurements have not been designed specifically for monitoring urban areas, an increasing number of these observations is being used for understanding the growth rates of cities and their environmental impacts. Here we reviewed the existing tools available from satellite remote sensing to study urban contribution to climate change, which could be used for monitoring the progress of climate change mitigation strategies at the city level. We described earth observations that are suitable for measuring and monitoring urban population, extent, and structure; urban emissions of greenhouse gases and other air pollutants; urban energy consumption; and extent, intensity, and effects on surrounding regions, including nearby water bodies, of urban heat islands. We compared the observations available and obtainable from space with the measurements desirable for monitoring. Despite considerable progress in monitoring urban extent, structure, heat island intensity, and air pollution from space, many limitations and uncertainties still need to be resolved. We emphasize that some important variables, such as population density and urban energy consumption, cannot be suitably measured from space with available observations.
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Zhang J, Ghirardo A, Gori A, Albert A, Buegger F, Pace R, Georgii E, Grote R, Schnitzler JP, Durner J, Lindermayr C. Improving Air Quality by Nitric Oxide Consumption of Climate-Resilient Trees Suitable for Urban Greening. FRONTIERS IN PLANT SCIENCE 2020; 11:549913. [PMID: 33117411 PMCID: PMC7550725 DOI: 10.3389/fpls.2020.549913] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Accepted: 09/10/2020] [Indexed: 06/11/2023]
Abstract
Nitrogen oxides (NOx), mainly a mixture of nitric oxide (NO) and nitrogen dioxide (NO2), are formed by the reaction of nitrogen and oxygen compounds in the air as a result of combustion processes and traffic. Both deposit into leaves via stomata, which on the one hand benefits air quality and on the other hand provides an additional source of nitrogen for plants. In this study, we first determined the NO and NO2 specific deposition velocities based on projected leaf area (sV d) using a branch enclosure system. We studied four tree species that are regarded as suitable to be planted under predicted future urban climate conditions: Carpinus betulus, Fraxinus ornus, Fraxinus pennsylvanica and Ostrya carpinifolia. The NO and NO2 sVd were found similar in all tree species. Second, in order to confirm NO metabolization, we fumigated plants with 15NO and quantified the incorporation of 15N in leaf materials of these trees and four additional urban tree species (Celtis australis, Alnus spaethii, Alnus glutinosa, and Tilia henryana) under controlled environmental conditions. Based on these 15N-labeling experiments, A. glutinosa showed the most effective incorporation of 15NO. Third, we tried to elucidate the mechanism of metabolization. Therefore, we generated transgenic poplars overexpressing Arabidopsis thaliana phytoglobin 1 or 2. Phytoglobins are known to metabolize NO to nitrate in the presence of oxygen. The 15N uptake in phytoglobin-overexpressing poplars was significantly increased compared to wild-type trees, demonstrating that the NO uptake is enzymatically controlled besides stomatal dependence. In order to upscale the results and to investigate if a trade-off exists between air pollution removal and survival probability under future climate conditions, we have additionally carried out a modeling exercise of NO and NO2 deposition for the area of central Berlin. If the actually dominant deciduous tree species (Acer platanoides, Tilia cordata, Fagus sylvatica, Quercus robur) would be replaced by the species suggested for future conditions, the total annual NO and NO2 deposition in the modeled urban area would hardly change, indicating that the service of air pollution removal would not be degraded. These results may help selecting urban tree species in future greening programs.
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Affiliation(s)
- Jiangli Zhang
- Institute of Biochemical Plant Pathology, Helmholtz Zentrum München, Neuherberg/Munich, Germany
- College of Life Sciences, Henan Normal University, Xinxiang, China
| | - Andrea Ghirardo
- Research Unit Environmental Simulation, Institute of Biochemical Plant Pathology, Helmholtz Zentrum München, Neuherberg/Munich, Germany
| | - Antonella Gori
- Department of Agriculture, Food, Environment, and Forestry (DAGRI), University of Florence, Florence, Italy
- Department of Biology, Agriculture and Food Sciences, Institute for Sustainable Plant Protection, The National Research Council of Italy (CNR), Florence, Italy
| | - Andreas Albert
- Research Unit Environmental Simulation, Institute of Biochemical Plant Pathology, Helmholtz Zentrum München, Neuherberg/Munich, Germany
| | - Franz Buegger
- Institute of Biochemical Plant Pathology, Helmholtz Zentrum München, Neuherberg/Munich, Germany
| | - Rocco Pace
- Institute of Meteorology and Climate Research — Institute of Atmospheric Environmental Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
- Institute of Research on Terrestrial Ecosystems (IRET), National Research Council (CNR), Porano, Italy
| | - Elisabeth Georgii
- Institute of Biochemical Plant Pathology, Helmholtz Zentrum München, Neuherberg/Munich, Germany
| | - Rüdiger Grote
- Institute of Meteorology and Climate Research — Institute of Atmospheric Environmental Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
| | - Jörg-Peter Schnitzler
- Research Unit Environmental Simulation, Institute of Biochemical Plant Pathology, Helmholtz Zentrum München, Neuherberg/Munich, Germany
| | - Jörg Durner
- Institute of Biochemical Plant Pathology, Helmholtz Zentrum München, Neuherberg/Munich, Germany
- Chair of Biochemical Plant Pathology, Technische Universität München, Freising, Germany
| | - Christian Lindermayr
- Institute of Biochemical Plant Pathology, Helmholtz Zentrum München, Neuherberg/Munich, Germany
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Developing General Equations for Urban Tree Biomass Estimation with High-Resolution Satellite Imagery. SUSTAINABILITY 2019. [DOI: 10.3390/su11164347] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Urban trees provide various important ecological services, the quantification of which is vital to sustainable urban development and requires accurate estimation of tree biomass. A limited number of allometric biomass equations, however, have been developed for urban species due to the prohibitive cost. Remote sensing has provided cost-effective means for estimating urban forest biomass, although the propagation of error in the estimation process is not well understood. This study aimed to offer a baseline assessment of the feasibility of estimating urban tree biomass with remote sensing-based general equations applicable to broad taxonomic groups by conducting a large urban tree inventory on a university campus. The biomasses of 191 trees of seven species from the inventory, separated into two categories (i.e., evergreen and deciduous), were calculated exclusively with urban-based species-specific allometric equations. WorldView-2 satellite imagery data were acquired to retrieve normalized difference vegetation index (NDVI) values at the location, crown, and stand levels. The results indicated that biomass correlated with NDVI in varying forms and degrees. The general equations at the crown level yielded the most accurate biomass estimates, while the location-level estimates were the least accurate. Crown-level spectral responses provided adequate information for delivering spatially explicit biomass estimation.
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Urban Ecosystem Services Quantification through Remote Sensing Approach: A Systematic Review. ENVIRONMENTS 2019. [DOI: 10.3390/environments6050051] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Urban ecosystem services (UES) is an essential approach to the development of sustainable cities and must be incorporated into urban planning to be able to improve humans’ life quality. This paper aimed to identify remote sensing (RS) data/techniques used in the literature in five years (2013–2017) for UES investigation and to analyze the similarity between them. For this purpose, we used the Scopus database of scientific journals, and a set of appropriate filters were applied. A total of 44 studies were selected, being 93.18% of them located in the Northern Hemisphere, mostly in Europe. The most common dataset used was the secondary data, followed by the Landsat family products. Land use and land cover (LULC) was the most common approach utilized, succeeded by radiometric indexes and band related. All four main classes (provision, regulation, supporting, and cultural) of ecosystem services (ES) were identified in the reviewed papers, wherein regulating services were the most popular modality mentioned. Seven different groups were established as having 100% of similarity between methods and ES results. Therefore, RS is identified in the literature as an important technique to reach this goal. However, we highlight the lack of studies in the southern hemisphere.
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Wilkes P, Disney M, Vicari MB, Calders K, Burt A. Estimating urban above ground biomass with multi-scale LiDAR. CARBON BALANCE AND MANAGEMENT 2018; 13:10. [PMID: 29943069 PMCID: PMC6020103 DOI: 10.1186/s13021-018-0098-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2017] [Accepted: 05/26/2018] [Indexed: 06/08/2023]
Abstract
BACKGROUND Urban trees have long been valued for providing ecosystem services (mitigation of the "heat island" effect, suppression of air pollution, etc.); more recently the potential of urban forests to store significant above ground biomass (AGB) has also be recognised. However, urban areas pose particular challenges when assessing AGB due to plasticity of tree form, high species diversity as well as heterogeneous and complex land cover. Remote sensing, in particular light detection and ranging (LiDAR), provide a unique opportunity to assess urban AGB by directly measuring tree structure. In this study, terrestrial LiDAR measurements were used to derive new allometry for the London Borough of Camden, that incorporates the wide range of tree structures typical of an urban setting. Using a wall-to-wall airborne LiDAR dataset, individual trees were then identified across the Borough with a new individual tree detection (ITD) method. The new allometry was subsequently applied to the identified trees, generating a Borough-wide estimate of AGB. RESULTS Camden has an estimated median AGB density of 51.6 Mg ha-1 where maximum AGB density is found in pockets of woodland; terrestrial LiDAR-derived AGB estimates suggest these areas are comparable to temperate and tropical forest. Multiple linear regression of terrestrial LiDAR-derived maximum height and projected crown area explained 93% of variance in tree volume, highlighting the utility of these metrics to characterise diverse tree structure. Locally derived allometry provided accurate estimates of tree volume whereas a Borough-wide allometry tended to overestimate AGB in woodland areas. The new ITD method successfully identified individual trees; however, AGB was underestimated by ≤ 25% when compared to terrestrial LiDAR, owing to the inability of ITD to resolve crown overlap. A Monte Carlo uncertainty analysis identified assigning wood density values as the largest source of uncertainty when estimating AGB. CONCLUSION Over the coming century global populations are predicted to become increasingly urbanised, leading to an unprecedented expansion of urban land cover. Urban areas will become more important as carbon sinks and effective tools to assess carbon densities in these areas are therefore required. Using multi-scale LiDAR presents an opportunity to achieve this, providing a spatially explicit map of urban forest structure and AGB.
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Affiliation(s)
- Phil Wilkes
- Department of Geography, University College London, Gower Street, London, WC1E 6BT UK
- NERC National Centre for Earth Observation,
Leicester, UK
| | - Mathias Disney
- Department of Geography, University College London, Gower Street, London, WC1E 6BT UK
- NERC National Centre for Earth Observation,
Leicester, UK
| | - Matheus Boni Vicari
- Department of Geography, University College London, Gower Street, London, WC1E 6BT UK
| | - Kim Calders
- Department of Geography, University College London, Gower Street, London, WC1E 6BT UK
- Earth Observation, Climate and Optical Group, National Physical Laboratory, Hampton Road, Teddington, TW11 0LW UK
- Computational & Applied Vegetation Ecology, Ghent University, Ghent, Belgium
| | - Andrew Burt
- Department of Geography, University College London, Gower Street, London, WC1E 6BT UK
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Miller DL, Roberts DA, Clarke KC, Lin Y, Menzer O, Peters EB, McFadden JP. Gross primary productivity of a large metropolitan region in midsummer using high spatial resolution satellite imagery. Urban Ecosyst 2018. [DOI: 10.1007/s11252-018-0769-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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11
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Mitchell MGE, Johansen K, Maron M, McAlpine CA, Wu D, Rhodes JR. Identification of fine scale and landscape scale drivers of urban aboveground carbon stocks using high-resolution modeling and mapping. THE SCIENCE OF THE TOTAL ENVIRONMENT 2018; 622-623:57-70. [PMID: 29202369 DOI: 10.1016/j.scitotenv.2017.11.255] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2017] [Revised: 11/22/2017] [Accepted: 11/22/2017] [Indexed: 06/07/2023]
Abstract
Urban areas are sources of land use change and CO2 emissions that contribute to global climate change. Despite this, assessments of urban vegetation carbon stocks often fail to identify important landscape-scale drivers of variation in urban carbon, especially the potential effects of landscape structure variables at different spatial scales. We combined field measurements with Light Detection And Ranging (LiDAR) data to build high-resolution models of woody plant aboveground carbon across the urban portion of Brisbane, Australia, and then identified landscape scale drivers of these carbon stocks. First, we used LiDAR data to quantify the extent and vertical structure of vegetation across the city at high resolution (5×5m). Next, we paired this data with aboveground carbon measurements at 219 sites to create boosted regression tree models and map aboveground carbon across the city. We then used these maps to determine how spatial variation in land cover/land use and landscape structure affects these carbon stocks. Foliage densities above 5m height, tree canopy height, and the presence of ground openings had the strongest relationships with aboveground carbon. Using these fine-scale relationships, we estimate that 2.2±0.4 TgC are stored aboveground in the urban portion of Brisbane, with mean densities of 32.6±5.8MgCha-1 calculated across the entire urban land area, and 110.9±19.7MgCha-1 calculated within treed areas. Predicted carbon densities within treed areas showed strong positive relationships with the proportion of surrounding tree cover and how clumped that tree cover was at both 1km2 and 1ha resolutions. Our models predict that even dense urban areas with low tree cover can have high carbon densities at fine scales. We conclude that actions and policies aimed at increasing urban carbon should focus on those areas where urban tree cover is most fragmented.
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Affiliation(s)
- Matthew G E Mitchell
- School of Earth and Environmental Sciences, The University of Queensland, Brisbane, QLD 4072, Australia.
| | - Kasper Johansen
- School of Earth and Environmental Sciences, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Martine Maron
- School of Earth and Environmental Sciences, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Clive A McAlpine
- School of Earth and Environmental Sciences, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Dan Wu
- School of Earth and Environmental Sciences, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Jonathan R Rhodes
- School of Earth and Environmental Sciences, The University of Queensland, Brisbane, QLD 4072, Australia
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Rieb JT, Chaplin-Kramer R, Daily GC, Armsworth PR, Böhning-Gaese K, Bonn A, Cumming GS, Eigenbrod F, Grimm V, Jackson BM, Marques A, Pattanayak SK, Pereira HM, Peterson GD, Ricketts TH, Robinson BE, Schröter M, Schulte LA, Seppelt R, Turner MG, Bennett EM. Response to Kabisch and Colleagues. Bioscience 2018. [DOI: 10.1093/biosci/bix154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Jesse T Rieb
- Department of Natural Resource Sciences, and EMB is affiliated with the McGill School of Environment, at McGill University, in Ste-Anne-de-Bellevue, Quebec, Canada
| | - Rebecca Chaplin-Kramer
- Natural Capital Project at Stanford University, in Stanford, California; GCD is also affiliated with the Department of Biology and the Woods Institute for the Environment at Stanford University
| | - Gretchen C Daily
- Natural Capital Project at Stanford University, in Stanford, California; GCD is also affiliated with the Department of Biology and the Woods Institute for the Environment at Stanford University
| | - Paul R Armsworth
- Department of Ecology and Evolutionary Biology at the University of Tennessee, Knoxville
| | - Katrin Böhning-Gaese
- Senckenberg Biodiversity and Climate Research Centre, in Frankfurt (Main), Germany, and the Institute for Ecology, Evolution, and Diversity at Goethe University Frankfurt
| | - Aletta Bonn
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, in Germany
- Institute of Ecology at Friedrich Schiller University Jena, in Germany
| | - Graeme S Cumming
- ARC Centre of Excellence in Coral Reef Studies at James Cook University, in Townsville, Queensland, Australia
| | - Felix Eigenbrod
- Geography and Environment and the Centre for Biological Sciences at the University of Southampton, in Southampton, United Kingdom
| | - Volker Grimm
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, in Germany
- Department of Ecological Modelling
| | - Bethanna M Jackson
- School of Geography at Victoria University of Wellington, in New Zealand
| | - Alexandra Marques
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, in Germany
- Institute of Biology
- Institute of Environmental Sciences (CML) at Leiden University, in The Netherlands
| | - Subhrendu K Pattanayak
- Sanford School of Public Policy, the Duke Global Health Institute, and the Nicholas School of the Environment at Duke University, in Durham, North Carolina
| | - Henrique M Pereira
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, in Germany
- School of Geography at Victoria University of Wellington, in New Zealand
| | | | - Taylor H Ricketts
- Gund Institute for Ecological Economics and the Rubenstein School of Environment and Natural Resources at the University of Vermont, in Burlington
| | - Brian E Robinson
- Department of Geography at McGill University, in Montreal, Quebec, Canada
| | - Matthias Schröter
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, in Germany
- Department of Ecosystem Services
| | - Lisa A Schulte
- Department of Natural Resource Ecology and Management at Iowa State University, in Ames
| | - Ralf Seppelt
- Department of Computational Landscape Ecology at UFZ–Helmholtz Centre for Environmental Research, in Leipzig
- Institute of Geoscience and Geography, at Martin Luther University Halle-Wittenberg, in Halle (Saale), Germany
| | - Monica G Turner
- Department of Zoology at the University of Wisconsin–Madison
| | - Elena M Bennett
- Department of Natural Resource Sciences, and EMB is affiliated with the McGill School of Environment, at McGill University, in Ste-Anne-de-Bellevue, Quebec, Canada
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Tigges J, Lakes T. High resolution remote sensing for reducing uncertainties in urban forest carbon offset life cycle assessments. CARBON BALANCE AND MANAGEMENT 2017; 12:17. [PMID: 28980218 PMCID: PMC5628095 DOI: 10.1186/s13021-017-0085-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/10/2017] [Accepted: 09/27/2017] [Indexed: 06/07/2023]
Abstract
BACKGROUND Urban forests reduce greenhouse gas emissions by storing and sequestering considerable amounts of carbon. However, few studies have considered the local scale of urban forests to effectively evaluate their potential long-term carbon offset. The lack of precise, consistent and up-to-date forest details is challenging for long-term prognoses. Therefore, this review aims to identify uncertainties in urban forest carbon offset assessment and discuss the extent to which such uncertainties can be reduced by recent progress in high resolution remote sensing. We do this by performing an extensive literature review and a case study combining remote sensing and life cycle assessment of urban forest carbon offset in Berlin, Germany. MAIN TEXT Recent progress in high resolution remote sensing and methods is adequate for delivering more precise details on the urban tree canopy, individual tree metrics, species, and age structures compared to conventional land use/cover class approaches. These area-wide consistent details can update life cycle inventories for more precise future prognoses. Additional improvements in classification accuracy can be achieved by a higher number of features derived from remote sensing data of increasing resolution, but first studies on this subject indicated that a smart selection of features already provides sufficient data that avoids redundancies and enables more efficient data processing. Our case study from Berlin could use remotely sensed individual tree species as consistent inventory of a life cycle assessment. However, a lack of growth, mortality and planting data forced us to make assumptions, therefore creating uncertainty in the long-term prognoses. Regarding temporal changes and reliable long-term estimates, more attention is required to detect changes of gradual growth, pruning and abrupt changes in tree planting and mortality. As such, precise long-term urban ecological monitoring using high resolution remote sensing should be intensified, especially due to increasing climate change effects. This is important for calibrating and validating recent prognoses of urban forest carbon offset, which have so far scarcely addressed longer timeframes. Additionally, higher resolution remote sensing of urban forest carbon estimates can improve upscaling approaches, which should be extended to reach a more precise global estimate for the first time. CONCLUSIONS Urban forest carbon offset can be made more relevant by making more standardized assessments available for science and professional practitioners, and the increasing availability of high resolution remote sensing data and the progress in data processing allows for precisely that.
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Affiliation(s)
- Jan Tigges
- Geoinformation Science Lab, Department of Geography, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany
| | - Tobia Lakes
- Geoinformation Science Lab, Department of Geography, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany
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