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Berger K, Machwitz M, Kycko M, Kefauver SC, Van Wittenberghe S, Gerhards M, Verrelst J, Atzberger C, van der Tol C, Damm A, Rascher U, Herrmann I, Paz VS, Fahrner S, Pieruschka R, Prikaziuk E, Buchaillot ML, Halabuk A, Celesti M, Koren G, Gormus ET, Rossini M, Foerster M, Siegmann B, Abdelbaki A, Tagliabue G, Hank T, Darvishzadeh R, Aasen H, Garcia M, Pôças I, Bandopadhyay S, Sulis M, Tomelleri E, Rozenstein O, Filchev L, Stancile G, Schlerf M. Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review. Remote Sens Environ 2022; 280:113198. [PMID: 36090616 PMCID: PMC7613382 DOI: 10.1016/j.rse.2022.113198] [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] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Remote detection and monitoring of the vegetation responses to stress became relevant for sustainable agriculture. Ongoing developments in optical remote sensing technologies have provided tools to increase our understanding of stress-related physiological processes. Therefore, this study aimed to provide an overview of the main spectral technologies and retrieval approaches for detecting crop stress in agriculture. Firstly, we present integrated views on: i) biotic and abiotic stress factors, the phases of stress, and respective plant responses, and ii) the affected traits, appropriate spectral domains and corresponding methods for measuring traits remotely. Secondly, representative results of a systematic literature analysis are highlighted, identifying the current status and possible future trends in stress detection and monitoring. Distinct plant responses occurring under shortterm, medium-term or severe chronic stress exposure can be captured with remote sensing due to specific light interaction processes, such as absorption and scattering manifested in the reflected radiance, i.e. visible (VIS), near infrared (NIR), shortwave infrared, and emitted radiance, i.e. solar-induced fluorescence and thermal infrared (TIR). From the analysis of 96 research papers, the following trends can be observed: increasing usage of satellite and unmanned aerial vehicle data in parallel with a shift in methods from simpler parametric approaches towards more advanced physically-based and hybrid models. Most study designs were largely driven by sensor availability and practical economic reasons, leading to the common usage of VIS-NIR-TIR sensor combinations. The majority of reviewed studies compared stress proxies calculated from single-source sensor domains rather than using data in a synergistic way. We identified new ways forward as guidance for improved synergistic usage of spectral domains for stress detection: (1) combined acquisition of data from multiple sensors for analysing multiple stress responses simultaneously (holistic view); (2) simultaneous retrieval of plant traits combining multi-domain radiative transfer models and machine learning methods; (3) assimilation of estimated plant traits from distinct spectral domains into integrated crop growth models. As a future outlook, we recommend combining multiple remote sensing data streams into crop model assimilation schemes to build up Digital Twins of agroecosystems, which may provide the most efficient way to detect the diversity of environmental and biotic stresses and thus enable respective management decisions.
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Affiliation(s)
- Katja Berger
- Image Processing Laboratory (IPL), University of Valencia, C/Catedrático José Beltrán 2, Paterna 46980, Valencia, Spain
- Department of Geography, Ludwig-Maximilians-Universität München (LMU), Luisenstr. 37, 80333 Munich, Germany
| | - Miriam Machwitz
- Remote Sensing and Natural Resources Modelling Group, Environmental Research and Innovation Department, Luxembourg Institute of Science and Technology (LIST), 41, rue du Brill, L-4422 Belvaux, Luxembourg
| | - Marlena Kycko
- Department of Geoinformatics Cartography and Remote Sensing, Chair of Geomatics and Information Systems, Faculty of Geography and Regional Studies, University of Warsaw, 00-927 Warszawa, Poland
| | - Shawn C. Kefauver
- Integrative Crop Ecophysiology Group, Plant Physiology Section, Faculty of Biology, University of Barcelona, 08028 Barcelona, Spain
- AGROTECNIO (Center for Research in Agrotechnology), Av. Rovira Roure 191, 25198 Lleida, Spain
| | - Shari Van Wittenberghe
- Image Processing Laboratory (IPL), University of Valencia, C/Catedrático José Beltrán 2, Paterna 46980, Valencia, Spain
| | - Max Gerhards
- Earth Observation and Climate Processes, Trier University, 54286 Trier, Germany
| | - Jochem Verrelst
- Image Processing Laboratory (IPL), University of Valencia, C/Catedrático José Beltrán 2, Paterna 46980, Valencia, Spain
| | - Clement Atzberger
- Institute of Geomatics, University of Natural Resources and Life Sciences, Vienna (BOKU), Peter Jordan Str. 82, 1190 Vienna, Austria
| | - Christiaan van der Tol
- Faculty Geo-Information Science and Earth Observation, ITC, University of Twente, the Netherlands
| | - Alexander Damm
- Department of Geography, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Überlandstrasse 133, 8600 Dübendorf, Switzerland
| | - Uwe Rascher
- Institute of Bio- and Geosciences, Plant Sciences (IBG-2), Forschungszentrum Jülich, 52428 Jülich, Germany
| | - Ittai Herrmann
- The Plant Sensing Laboratory, The Robert H. Smith Institute for Plant Sciences and Genetics in Agriculture, The Robert H. Smith Faculty of Agriculture, Food and Environment, The Hebrew University of Jerusalem, P.O. Box 12, Rehovot 7610001, Israel
| | - Veronica Sobejano Paz
- Department of Environmental Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark
| | - Sven Fahrner
- Institute of Bio- and Geosciences, Plant Sciences (IBG-2), Forschungszentrum Jülich, 52428 Jülich, Germany
| | - Roland Pieruschka
- Institute of Bio- and Geosciences, Plant Sciences (IBG-2), Forschungszentrum Jülich, 52428 Jülich, Germany
| | - Egor Prikaziuk
- Faculty Geo-Information Science and Earth Observation, ITC, University of Twente, the Netherlands
| | - Ma. Luisa Buchaillot
- Integrative Crop Ecophysiology Group, Plant Physiology Section, Faculty of Biology, University of Barcelona, 08028 Barcelona, Spain
- AGROTECNIO (Center for Research in Agrotechnology), Av. Rovira Roure 191, 25198 Lleida, Spain
| | - Andrej Halabuk
- Institute of Landscape Ecology, Slovak Academy of Sciences, 814 99 Bratislava, Slovakia
| | - Marco Celesti
- HE Space for ESA - European Space Agency, European Space Research and Technology Centre (ESA-ESTEC), Keplerlaan 1, 2201, AZ Noordwijk, the Netherlands
| | - Gerbrand Koren
- Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, the Netherlands
| | - Esra Tunc Gormus
- Department of Geomatics Engineering, Karadeniz Technical University, 61080 Trabzon, Turkey
| | - Micol Rossini
- Remote Sensing of Environmental Dynamics Laboratory (LTDA), University of Milano - Bicocca, Piazza della Scienza 1, 20126 Milano, Italy
| | - Michael Foerster
- Geoinformation in Environmental Planning Lab, Technische Universität Berlin, 10623 Berlin, Germany
| | - Bastian Siegmann
- Institute of Bio- and Geosciences, Plant Sciences (IBG-2), Forschungszentrum Jülich, 52428 Jülich, Germany
| | - Asmaa Abdelbaki
- Earth Observation and Climate Processes, Trier University, 54286 Trier, Germany
| | - Giulia Tagliabue
- Remote Sensing of Environmental Dynamics Laboratory (LTDA), University of Milano - Bicocca, Piazza della Scienza 1, 20126 Milano, Italy
| | - Tobias Hank
- Department of Geography, Ludwig-Maximilians-Universität München (LMU), Luisenstr. 37, 80333 Munich, Germany
| | - Roshanak Darvishzadeh
- Faculty Geo-Information Science and Earth Observation, ITC, University of Twente, the Netherlands
| | - Helge Aasen
- Earth Observation and Analysis of Agroecosystems Team, Division Agroecology and Environment, Agroscope, Zurich, Switzerland
- Institute of Agricultural Science, ETH Zürich, Zurich, Switzerland
| | - Monica Garcia
- Research Centre for the Management of Agricultural and Environmental Risks (CEIGRAM), ETSIAAB, Universidad Politécnica de Madrid, 28040, Spain
| | - Isabel Pôças
- ForestWISE - Collaborative Laboratory for Integrated Forest & Fire Management, Quinta de Prados, Campus da UTAD, 5001-801 Vila Real, Portugal
| | | | - Mauro Sulis
- Remote Sensing and Natural Resources Modelling Group, Environmental Research and Innovation Department, Luxembourg Institute of Science and Technology (LIST), 41, rue du Brill, L-4422 Belvaux, Luxembourg
| | - Enrico Tomelleri
- Faculty of Science and Technology, Free University of Bozen/Bolzano, Italy
| | - Offer Rozenstein
- Institute of Soil, Water and Environmental Sciences, Agricultural Research Organization—Volcani Institute, HaMaccabim Road 68, P.O. Box 15159, Rishon LeZion 7528809, Israel
| | - Lachezar Filchev
- Space Research and Technology Institute, Bulgarian Academy of Sciences (SRTI-BAS), Bulgaria
| | - Gheorghe Stancile
- National Meteorological Administration, Building A, Soseaua Bucuresti-Ploiesti 97, 013686 Bucuresti, Romania
| | - Martin Schlerf
- Remote Sensing and Natural Resources Modelling Group, Environmental Research and Innovation Department, Luxembourg Institute of Science and Technology (LIST), 41, rue du Brill, L-4422 Belvaux, Luxembourg
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Bar-On P, Yaakobi A, Moran U, Rozenstein O, Kopler I, Klein T. A montane species treeline is defined by both temperature and drought effects on growth season length. Tree Physiol 2022; 42:1700-1719. [PMID: 35738872 DOI: 10.1093/treephys/tpac070] [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: 03/28/2022] [Accepted: 06/11/2022] [Indexed: 06/15/2023]
Abstract
Montane treelines are defined by a threshold low temperature. However, what are the dynamics when the snow-free summer growth season coincides with a 6-month seasonal drought? We tested this fundamental question by measuring tree growth and leaf activity across elevations in Mt Hermon (2814 m; in Israel and Syria), where oak trees (Quercus look and Quercus boissieri) form an observed treeline at 1900 m. While in theory, individuals can be established at higher elevations (minimum daily temperature >6.5 °C for >4 months even at the summit), soil drying and vapor pressure deficit in summer enforces growth cessation in August, leaving only 2-3 months for tree growth. At lower elevations, Q. look Kotschy is replaced by Quercus cerris L. (1300 m) and Quercus calliprinos Webb (1000 m) in accompanying Q. boissieri Reut., and growth season length (GSL) is longer due to an earlier start in April. Leaf gas exchange continues during autumn, but assimilates are no longer utilized in growth. Interestingly, the growth and activity of Q. boissieri were equivalent to that of each of the other three species across the ~1 km elevation gradient. A planting experiment at 2100 m showed that seedlings of the four oak species survived the cold winter and showed budding of leaves in summer, but wilted in August. Our unique mountain site in the Eastern Mediterranean introduces a new factor to the formation of treelines, involving a drought limitation on GSL. This site presents the elevation edge for each species and the southern distribution edge for both the endemic Q. look and the broad-range Q. cerris. With ongoing warming, Q. look and Q. boissieri are slowly expanding to higher elevations, while Q. cerris is at risk of future extirpation.
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Affiliation(s)
- Peleg Bar-On
- Department of Plant and Environmental Science, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Assaf Yaakobi
- Department of Plant and Environmental Science, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Uri Moran
- Department of Plant and Environmental Science, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Offer Rozenstein
- Institute of Soil, Water, and Environmental Studies, Agricultural Research Organization, Volcani Center, Rishon LeZion 7505101, Israel
| | - Idan Kopler
- MIGAL - Galilee Research Institute, South Industrial Zone, PO Box 831, Kiryat Shmona 11016, Israel
| | - Tamir Klein
- Department of Plant and Environmental Science, Weizmann Institute of Science, Rehovot 7610001, Israel
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Weksler S, Rozenstein O, Ben Dor E. Continuous seasonal monitoring of nitrogen and water content in lettuce using a dual phenomics system. J Exp Bot 2022; 73:5294-5305. [PMID: 34958347 DOI: 10.1093/jxb/erab561] [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] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 12/23/2021] [Indexed: 06/14/2023]
Abstract
The collection and analysis of large amounts of information on a plant-by-plant basis contributes to the development of precision fertigation and may be achieved by combining remote-sensing technology with high-throughput phenotyping methods. Here, lettuce plants (Lactuca sativa) were grown under optimal and suboptimal nitrogen and irrigation treatments from seedlings to harvest. A Plantarray system was used to calculate and log weights, daily transpiration, and momentary transpiration rates throughout the experiment. From 15 d after planting until experiment termination, the entire array of plants was imaged hourly (from 09.00 h to 14.00 h) using a hyperspectral moving camera. Three vegetation indices were calculated from the plants' reflectance signal: red-edge chlorophyll index (RECI), photochemical reflectance index (PRI), and water index (WI), and combined treatments, physiological measurements, and vegetation indices were compared. RECI values differed significantly between nitrogen treatments from the first day of imaging, and WI values distinguished well-irrigated from drought-treated groups before detecting significant differences in daily transpiration rate. The PRI, calculated hourly during the drought-treatment phase, changed with the momentary transpiration rate. Thus, hyperspectral imaging might be used in growing facilities to detect nitrogen or water shortages in plants before their physiological response affects yields.
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Affiliation(s)
- Shahar Weksler
- Porter School of Environment and Earth Sciences, Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 6997801, Israel
- Institute of Soil, Water and Environmental Sciences, Agricultural Research Organization-Volcani Institute, HaMaccabim Road 68, P.O.B 15159, Rishon LeZion 7528809, Israel
| | - Offer Rozenstein
- Institute of Soil, Water and Environmental Sciences, Agricultural Research Organization-Volcani Institute, HaMaccabim Road 68, P.O.B 15159, Rishon LeZion 7528809, Israel
| | - Eyal Ben Dor
- Porter School of Environment and Earth Sciences, Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 6997801, Israel
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Weksler S, Rozenstein O, Haish N, Moshelion M, Wallach R, Ben-Dor E. Detection of Potassium Deficiency and Momentary Transpiration Rate Estimation at Early Growth Stages Using Proximal Hyperspectral Imaging and Extreme Gradient Boosting. Sensors (Basel) 2021; 21:s21030958. [PMID: 33535447 PMCID: PMC7867110 DOI: 10.3390/s21030958] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 01/21/2021] [Accepted: 01/27/2021] [Indexed: 12/02/2022]
Abstract
Potassium is a macro element in plants that is typically supplied to crops in excess throughout the season to avoid a deficit leading to reduced crop yield. Transpiration rate is a momentary physiological attribute that is indicative of soil water content, the plant’s water requirements, and abiotic stress factors. In this study, two systems were combined to create a hyperspectral–physiological plant database for classification of potassium treatments (low, medium, and high) and estimation of momentary transpiration rate from hyperspectral images. PlantArray 3.0 was used to control fertigation, log ambient conditions, and calculate transpiration rates. In addition, a semi-automated platform carrying a hyperspectral camera was triggered every hour to capture images of a large array of pepper plants. The combined attributes and spectral information on an hourly basis were used to classify plants into their given potassium treatments (average accuracy = 80%) and to estimate transpiration rate (RMSE = 0.025 g/min, R2 = 0.75) using the advanced ensemble learning algorithm XGBoost (extreme gradient boosting algorithm). Although potassium has no direct spectral absorption features, the classification results demonstrated the ability to label plants according to potassium treatments based on a remotely measured hyperspectral signal. The ability to estimate transpiration rates for different potassium applications using spectral information can aid in irrigation management and crop yield optimization. These combined results are important for decision-making during the growing season, and particularly at the early stages when potassium levels can still be corrected to prevent yield loss.
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Affiliation(s)
- Shahar Weksler
- Porter School of Environment and Earth Sciences, Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 6997801, Israel;
- Institute of Soil, Water and Environmental Sciences, Agricultural Research Organization, Rishon LeZion 7528809, Israel;
- Correspondence: ; Tel.: +972-3-640-5679
| | - Offer Rozenstein
- Institute of Soil, Water and Environmental Sciences, Agricultural Research Organization, Rishon LeZion 7528809, Israel;
| | - Nadav Haish
- The Robert H Smith Institute of Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, Rehovot 7610001, Israel; (N.H.); (M.M.)
| | - Menachem Moshelion
- The Robert H Smith Institute of Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, Rehovot 7610001, Israel; (N.H.); (M.M.)
| | - Rony Wallach
- Department of Soil and Water Sciences, The Robert H. Smith Faculty of Agriculture, Food and Environment, The Hebrew University of Jerusalem, Rehovot 76100, Israel;
| | - Eyal Ben-Dor
- Porter School of Environment and Earth Sciences, Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 6997801, Israel;
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Rozenstein O, Puckrin E, Adamowski J. Development of a new approach based on midwave infrared spectroscopy for post-consumer black plastic waste sorting in the recycling industry. Waste Manag 2017; 68:38-44. [PMID: 28736049 DOI: 10.1016/j.wasman.2017.07.023] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [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: 11/10/2016] [Revised: 06/28/2017] [Accepted: 07/15/2017] [Indexed: 06/07/2023]
Abstract
Waste sorting is key to the process of waste recycling. Exact identification of plastic resin and wood products using Near Infrared (NIR, 1-1.7µm) sensing is currently in use. Yet, dark targets characterized by low reflectance, such as black plastics, are hard to identify by this method. Following the recent success of Midwave Infrared (MWIR, 3-12µm) measurements to identify coloured plastic polymers, the aim of this study was to assess whether this technique is applicable to sorting black plastic polymers and wood products. We performed infrared reflectance contact measurements of 234 plastic samples and 29 samples of wood and paper products. Plastic samples included black, coloured and transparent Polyethylene Terephthalate (PET), Polyethylene (PE), Polyvinyl Chloride (PVC), Polypropylene (PP), Polylactic acid (PLA) and Polystyrene (PS). The spectral signatures of the black and coloured plastic samples were compared with clear plastic samples and signatures documented in the literature to identify the polymer spectral features in the presence of coloured material. This information was used to determine the spectral bands that best suit the sorting of black plastic polymers. The main NIR-MWIR absorption features of wood, cardboard and paper were identified as well according to the spectral measurements. Good agreement was found between our measurements and the absorption features documented in the literature. The new approach using MWIR spectral features appears to be useful for black plastics as it overcomes some of the limitations in the NIR region to identify them. The main limitation of this technique for industrial applications is the trade-off between the signal-to-noise ratio of the sensor operating in standoff mode and the speed at which waste is moved under the sensor. This limitation can be resolved by reducing the system's spectral resolution to 16cm-1, which allows for faster spectra acquisition while maintaining a reasonable signal-to-noise ratio.
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Affiliation(s)
- Offer Rozenstein
- Institute of Soil, Water and Environmental Sciences, Agricultural Research Organization, Volcani Center, HaMaccabim Road 68, P.O.B 15159, Rishon LeZion 7528809, Israel.
| | - Eldon Puckrin
- Defence Research and Development Canada (DRDC) - Valcartier, 2459 de la Bravoure, Québec, QC G3J 1X5, Canada
| | - Jan Adamowski
- Department of Bioresource Engineering, McGill University, Macdonald Campus 21, 111 Lakeshore Road, Ste-Anne-de-Bellevue, QC H9X 3V9, Canada
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Rozenstein O, Agam N, Serio C, Masiello G, Venafra S, Achal S, Puckrin E, Karnieli A. Diurnal emissivity dynamics in bare versus biocrusted sand dunes. Sci Total Environ 2015; 506-507:422-429. [PMID: 25437760 DOI: 10.1016/j.scitotenv.2014.11.035] [Citation(s) in RCA: 8] [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: 07/31/2014] [Revised: 11/07/2014] [Accepted: 11/09/2014] [Indexed: 06/04/2023]
Abstract
Land surface emissivity (LSE) in the thermal infrared depends mainly on the ground cover and on changes in soil moisture. The LSE is a critical variable that affects the prediction accuracy of geophysical models requiring land surface temperature as an input, highlighting the need for an accurate derivation of LSE. The primary aim of this study was to test the hypothesis that diurnal changes in emissivity, as detected from space, are larger for areas mostly covered by biocrusts (composed mainly of cyanobacteria) than for bare sand areas. The LSE dynamics were monitored from geostationary orbit by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) over a sand dune field in a coastal desert region extending across both sides of the Israel-Egypt political borderline. Different land-use practices by the two countries have resulted in exposed, active sand dunes on the Egyptian side (Sinai), and dunes stabilized by biocrusts on the Israeli side (Negev). Since biocrusts adsorb more moisture from the atmosphere than bare sand does, and LSE is affected by the soil moisture, diurnal fluctuations in LSE were larger for the crusted dunes in the 8.7 μm channel. This phenomenon is attributed to water vapor adsorption by the sand/biocrust particles. The results indicate that LSE is sensitive to minor changes in soil water content caused by water vapor adsorption and can, therefore, serve as a tool for quantifying this effect, which has a large spatial impact. As biocrusts cover vast regions in deserts worldwide, this discovery has repercussions for LSE estimations in deserts around the globe, and these LSE variations can potentially have considerable effects on geophysical models from local to regional scales.
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Affiliation(s)
- Offer Rozenstein
- Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boker Campus, 84990, Israel
| | - Nurit Agam
- Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boker Campus, 84990, Israel
| | - Carmine Serio
- School of Engineering and CNISM, Potenza Research Unit, University of Basilicata, Potenza, Italy
| | - Guido Masiello
- School of Engineering and CNISM, Potenza Research Unit, University of Basilicata, Potenza, Italy
| | - Sara Venafra
- School of Engineering and CNISM, Potenza Research Unit, University of Basilicata, Potenza, Italy
| | - Stephen Achal
- ITRES Research Ltd. #110, 3553 31st Street, N.W. Calgary, Alberta T2L 2K7, Canada
| | - Eldon Puckrin
- Defence Research and Development Canada (DRDC) - Valcartier, 2459 de la Bravoure, Québec, QC G3J 1X5, Canada
| | - Arnon Karnieli
- Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boker Campus, 84990, Israel.
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