Pub Date : 2024-11-13DOI: 10.1016/j.rse.2024.114507
Joseph J. Everest , Elisa Van Cleemput , Alison L. Beamish , Marko J. Spasojevic , Hope C. Humphries , Sarah C. Elmendorf
Plant functional traits are key drivers of ecosystem processes. However, plot-based monitoring of functional composition across both large spatial and temporal extents is a time-consuming and expensive undertaking. Airborne and satellite remote sensing platforms collect data across large spatial expanses, often repeatedly over time, raising the tantalising prospect of detection of biodiversity change over space and time through remotely sensed methods. Here, we test the degree to which in situ measurements of taxonomic and functional β-diversity, defined as pairwise dissimilarity either between sites, or between years within individual sites, is detectable in airborne hyperspectral imagery across both space and time in an alpine vascular plant community in the Front Range, Colorado, USA. Functional and taxonomic dissimilarity were significantly related to spectral dissimilarity across space, but lacked robust relationships with spectral dissimilarity over time. Biomass showed stronger relationships with spectral dissimilarity than either taxonomic or functional dissimilarity over space, but exhibited no significant associations with spectral dissimilarity over time. Comparative analyses using NDVI revealed that NDVI alone explains much of the variation explained by the full-range spectra. Our results support the use of hyperspectral data to detect fine-scale changes in vascular plant β-diversity over space, but suggest that methodological limitations still preclude the use of this technology for long-term monitoring and change detection.
{"title":"Evaluating the utility of hyperspectral data to monitor local-scale β-diversity across space and time","authors":"Joseph J. Everest , Elisa Van Cleemput , Alison L. Beamish , Marko J. Spasojevic , Hope C. Humphries , Sarah C. Elmendorf","doi":"10.1016/j.rse.2024.114507","DOIUrl":"10.1016/j.rse.2024.114507","url":null,"abstract":"<div><div>Plant functional traits are key drivers of ecosystem processes. However, plot-based monitoring of functional composition across both large spatial and temporal extents is a time-consuming and expensive undertaking. Airborne and satellite remote sensing platforms collect data across large spatial expanses, often repeatedly over time, raising the tantalising prospect of detection of biodiversity change over space and time through remotely sensed methods. Here, we test the degree to which in situ measurements of taxonomic and functional β-diversity, defined as pairwise dissimilarity either between sites, or between years within individual sites, is detectable in airborne hyperspectral imagery across both space and time in an alpine vascular plant community in the Front Range, Colorado, USA. Functional and taxonomic dissimilarity were significantly related to spectral dissimilarity across space, but lacked robust relationships with spectral dissimilarity over time. Biomass showed stronger relationships with spectral dissimilarity than either taxonomic or functional dissimilarity over space, but exhibited no significant associations with spectral dissimilarity over time. Comparative analyses using NDVI revealed that NDVI alone explains much of the variation explained by the full-range spectra. Our results support the use of hyperspectral data to detect fine-scale changes in vascular plant β-diversity over space, but suggest that methodological limitations still preclude the use of this technology for long-term monitoring and change detection.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"316 ","pages":"Article 114507"},"PeriodicalIF":11.1,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142601069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-13DOI: 10.1016/j.rse.2024.114500
Peiqi Yang , Christiaan van der Tol , Jing Liu , Zhigang Liu
<div><div>Separation of soil effects from top-of-canopy (TOC) reflectance is crucial for quantitative remote sensing of vegetation. Soil affects TOC reflectance via the soil-vegetation interaction and the direct reflection by soil. Various vegetation indices have been developed semi-empirically to mitigate the interferences caused by soil for specific applications, such estimating biomass and monitoring vegetation phenology. However, a practical approach to separate soil effects from the entire TOC spectral reflectance is still lacking. In this study, we investigate the radiative transfer process in a vegetation canopy with soil contamination and develop three methods to estimate the contribution of soil's direct reflection to TOC reflectance. Theoretical analysis reveals that the soil's direct reflection can be quantified and separated from TOC reflectance due to the distinct spectral characteristics of soil and vegetation. We identify three key features: a) Bands in the visible region where the reflectance of soil-uncontaminated green vegetation approaches zero due to strong pigment absorption. b) Two bands in the visible region where the vegetation reflectance is similar, but soil reflectance is distinguishable. c) Soil reflectance within the range of 400 nm to 1000 nm exhibits a near-linear dependence on wavelength. Using these features, we develop three methods to quantify the contribution of soil's direct reflection to TOC reflectance. For given soil reflectance, feature a) or b) alone allows estimating the fraction of soil that directly contributes to TOC reflectance, and thus the soil's direct reflection. Using all three features enables estimation of the soil's direct reflection without knowing soil reflectance.</div><div>The proposed methods, along with certain assumptions made during their development, are tested and evaluated using field and synthetic datasets of soil, leaf, and canopy. The evaluation of the three methods demonstrates that the estimation of the soil's direct reflection can be achieved through: i) Using TOC reflectance at approximately 675 nm and soil spectral reflectance, termed the red-band-based method (Method-RBB). ii) Using TOC reflectance at approximately 675 nm and 438 nm, along with soil spectral reflectance, termed as the two-band-based method (Method-TBB). iii) Using TOC reflectance at approximately 675 nm and 438 nm, assuming linear dependence of soil reflectance on wavelength in the visible and near-infrared region, termed as the linear-assumption-based method (Method-LAB). Our evaluation indicates that the linearity from 400 nm to 1000 nm holds true for a wide range of soil types. The conditions outlined in features a) and b) are valid for green vegetation with moderate to high leaf chlorophyll content: when leaf chlorophyll content exceeds 20 μg cm<sup>−2</sup>, the leaf albedo at 675 nm is generally below 0.15, and the difference in leaf albedo at 675 nm and 438 nm is sufficiently small. The results reve
{"title":"Separation of the direct reflection of soil from canopy spectral reflectance","authors":"Peiqi Yang , Christiaan van der Tol , Jing Liu , Zhigang Liu","doi":"10.1016/j.rse.2024.114500","DOIUrl":"10.1016/j.rse.2024.114500","url":null,"abstract":"<div><div>Separation of soil effects from top-of-canopy (TOC) reflectance is crucial for quantitative remote sensing of vegetation. Soil affects TOC reflectance via the soil-vegetation interaction and the direct reflection by soil. Various vegetation indices have been developed semi-empirically to mitigate the interferences caused by soil for specific applications, such estimating biomass and monitoring vegetation phenology. However, a practical approach to separate soil effects from the entire TOC spectral reflectance is still lacking. In this study, we investigate the radiative transfer process in a vegetation canopy with soil contamination and develop three methods to estimate the contribution of soil's direct reflection to TOC reflectance. Theoretical analysis reveals that the soil's direct reflection can be quantified and separated from TOC reflectance due to the distinct spectral characteristics of soil and vegetation. We identify three key features: a) Bands in the visible region where the reflectance of soil-uncontaminated green vegetation approaches zero due to strong pigment absorption. b) Two bands in the visible region where the vegetation reflectance is similar, but soil reflectance is distinguishable. c) Soil reflectance within the range of 400 nm to 1000 nm exhibits a near-linear dependence on wavelength. Using these features, we develop three methods to quantify the contribution of soil's direct reflection to TOC reflectance. For given soil reflectance, feature a) or b) alone allows estimating the fraction of soil that directly contributes to TOC reflectance, and thus the soil's direct reflection. Using all three features enables estimation of the soil's direct reflection without knowing soil reflectance.</div><div>The proposed methods, along with certain assumptions made during their development, are tested and evaluated using field and synthetic datasets of soil, leaf, and canopy. The evaluation of the three methods demonstrates that the estimation of the soil's direct reflection can be achieved through: i) Using TOC reflectance at approximately 675 nm and soil spectral reflectance, termed the red-band-based method (Method-RBB). ii) Using TOC reflectance at approximately 675 nm and 438 nm, along with soil spectral reflectance, termed as the two-band-based method (Method-TBB). iii) Using TOC reflectance at approximately 675 nm and 438 nm, assuming linear dependence of soil reflectance on wavelength in the visible and near-infrared region, termed as the linear-assumption-based method (Method-LAB). Our evaluation indicates that the linearity from 400 nm to 1000 nm holds true for a wide range of soil types. The conditions outlined in features a) and b) are valid for green vegetation with moderate to high leaf chlorophyll content: when leaf chlorophyll content exceeds 20 μg cm<sup>−2</sup>, the leaf albedo at 675 nm is generally below 0.15, and the difference in leaf albedo at 675 nm and 438 nm is sufficiently small. The results reve","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"316 ","pages":"Article 114500"},"PeriodicalIF":11.1,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142609810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-12DOI: 10.1016/j.rse.2024.114494
Yulong Zhang , Jiafu Mao , Ge Sun , Qinfeng Guo , Jeffrey Atkins , Wenhong Li , Mingzhou Jin , Conghe Song , Jingfeng Xiao , Taehee Hwang , Tong Qiu , Lin Meng , Daniel M. Ricciuto , Xiaoying Shi , Xing Li , Peter Thornton , Forrest Hoffman
Terrestrial vegetation is a crucial component of Earth's biosphere, regulating global carbon and water cycles and contributing to human welfare. Despite an overall greening trend, terrestrial vegetation exhibits a significant inter-annual variability. The mechanisms driving this variability, particularly those related to climatic and anthropogenic factors, remain poorly understood, which hampers our ability to project the long-term sustainability of ecosystem services. Here, by leveraging diverse remote sensing measurements, we pinpointed 2020 as a historic landmark, registering as the greenest year in modern satellite records from 2001 to 2020. Using ensemble machine learning and Earth system models, we found this exceptional greening primarily stemmed from consistent growth in boreal and temperate vegetation, attributed to rising CO2 levels, climate warming, and reforestation efforts, alongside a transient tropical green-up linked to the enhanced rainfall. Contrary to expectations, the COVID-19 pandemic lockdowns had a limited impact on this global greening anomaly. Our findings highlight the resilience and dynamic nature of global vegetation in response to diverse climatic and anthropogenic influences, offering valuable insights for optimizing ecosystem management and informing climate mitigation strategies.
{"title":"Earth's record-high greenness and its attributions in 2020","authors":"Yulong Zhang , Jiafu Mao , Ge Sun , Qinfeng Guo , Jeffrey Atkins , Wenhong Li , Mingzhou Jin , Conghe Song , Jingfeng Xiao , Taehee Hwang , Tong Qiu , Lin Meng , Daniel M. Ricciuto , Xiaoying Shi , Xing Li , Peter Thornton , Forrest Hoffman","doi":"10.1016/j.rse.2024.114494","DOIUrl":"10.1016/j.rse.2024.114494","url":null,"abstract":"<div><div>Terrestrial vegetation is a crucial component of Earth's biosphere, regulating global carbon and water cycles and contributing to human welfare. Despite an overall greening trend, terrestrial vegetation exhibits a significant inter-annual variability. The mechanisms driving this variability, particularly those related to climatic and anthropogenic factors, remain poorly understood, which hampers our ability to project the long-term sustainability of ecosystem services. Here, by leveraging diverse remote sensing measurements, we pinpointed 2020 as a historic landmark, registering as the greenest year in modern satellite records from 2001 to 2020. Using ensemble machine learning and Earth system models, we found this exceptional greening primarily stemmed from consistent growth in boreal and temperate vegetation, attributed to rising CO<sub>2</sub> levels, climate warming, and reforestation efforts, alongside a transient tropical green-up linked to the enhanced rainfall. Contrary to expectations, the COVID-19 pandemic lockdowns had a limited impact on this global greening anomaly. Our findings highlight the resilience and dynamic nature of global vegetation in response to diverse climatic and anthropogenic influences, offering valuable insights for optimizing ecosystem management and informing climate mitigation strategies.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"316 ","pages":"Article 114494"},"PeriodicalIF":11.1,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142601010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-11DOI: 10.1016/j.rse.2024.114496
Zhaoying Zhang , Yongguang Zhang
Solar-induced chlorophyll fluorescence (SIF) is a promising tool to estimate gross primary production (GPP), but the retrieval of SIF is commonly noisy and highly sensitive to various interference factors. Particularly, the retrieval of SIF in the red band (RSIF) is more challenging than in the far-red SIF (FRSIF) due to the weaker fluorescence signal and the weaker absorption depth of oxygen at the red band compared with the far-red band. A comprehensive evaluation of all factors will allow a reproducible interpretation of SIF signals and advance the estimation of GPP from SIF. Recent studies have assessed the sensitivity of SIF retrieval to sensor characteristics, retrieval methods, and hardware specifications. However, none of these studies have systematically investigated the directional retrieval error of SIF resulting from the mismatch between irradiance measured above the canopy and the true irradiance reaching the canopy components viewed by a sensor. This study illustrated the effect of mismatched irradiance on the retrieval of RSIF using the commonly used standard 3FLD method based on SCOPE model simulations. The retrieval accuracy was highest in the hotspot direction, but it decreased as the observation direction was away from the hotspot. The relative root mean square error (RRMSE) was generally higher than 20 % in the forward directions. To reduce the retrieval error due to the mismatch effect, we proposed a modified 3FLD method (MFLD) by calculating the true irradiance reaching the canopy in a given direction based on geometric optical theory. The results showed that MFLD clearly improved the retrieval accuracy for RSIF, especially in the forward directions where RRMSE decreased by 10 % in most cases. For example, the RRMSE was reduced from 19.26 % to 5.50 % after mitigating the mismatch between the measured and actual solar irradiance, when the solar zenith angle was 40° and viewing zenith angle was 30° in the forward solar principal plane. Even at the nadir observation, the RRMSE was also reduced from 12.84 % to 5.64 %. In summary, MFLD can effectively mitigate the irradiance mismatch effect on the retrieval of RSIF. These results will improve our interpretation of the relationship between GPP and RSIF at different observation directions.
{"title":"Mitigating the directional retrieval error of solar-induced chlorophyll fluorescence in the red band","authors":"Zhaoying Zhang , Yongguang Zhang","doi":"10.1016/j.rse.2024.114496","DOIUrl":"10.1016/j.rse.2024.114496","url":null,"abstract":"<div><div>Solar-induced chlorophyll fluorescence (SIF) is a promising tool to estimate gross primary production (GPP), but the retrieval of SIF is commonly noisy and highly sensitive to various interference factors. Particularly, the retrieval of SIF in the red band (RSIF) is more challenging than in the far-red SIF (FRSIF) due to the weaker fluorescence signal and the weaker absorption depth of oxygen at the red band compared with the far-red band. A comprehensive evaluation of all factors will allow a reproducible interpretation of SIF signals and advance the estimation of GPP from SIF. Recent studies have assessed the sensitivity of SIF retrieval to sensor characteristics, retrieval methods, and hardware specifications. However, none of these studies have systematically investigated the directional retrieval error of SIF resulting from the mismatch between irradiance measured above the canopy and the true irradiance reaching the canopy components viewed by a sensor. This study illustrated the effect of mismatched irradiance on the retrieval of RSIF using the commonly used standard 3FLD method based on SCOPE model simulations. The retrieval accuracy was highest in the hotspot direction, but it decreased as the observation direction was away from the hotspot. The relative root mean square error (RRMSE) was generally higher than 20 % in the forward directions. To reduce the retrieval error due to the mismatch effect, we proposed a modified 3FLD method (MFLD) by calculating the true irradiance reaching the canopy in a given direction based on geometric optical theory. The results showed that MFLD clearly improved the retrieval accuracy for RSIF, especially in the forward directions where RRMSE decreased by 10 % in most cases. For example, the RRMSE was reduced from 19.26 % to 5.50 % after mitigating the mismatch between the measured and actual solar irradiance, when the solar zenith angle was 40° and viewing zenith angle was 30° in the forward solar principal plane. Even at the nadir observation, the RRMSE was also reduced from 12.84 % to 5.64 %. In summary, MFLD can effectively mitigate the irradiance mismatch effect on the retrieval of RSIF. These results will improve our interpretation of the relationship between GPP and RSIF at different observation directions.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"316 ","pages":"Article 114496"},"PeriodicalIF":11.1,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142599132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-11DOI: 10.1016/j.rse.2024.114493
Jiashuang Jiao , Yuanjin Pan , Xiaoming Cui , Hussein A. Mohasseb , Hao Ding
Runoff variability in glacierized transboundary river basins over High Mountain Asia (HMA) directly affects the stability of water supply for more than one billion people in Asia. However, limited by insufficient in-situ gauges and imprecise hydrological model output, it is still a challenge to accurately monitor and comprehensively analyze the HMA runoff change. In this paper, we construct a water budget closure test of water balance equation based on satellite gravimetry constraints to assess the accuracy of hydrological dataset outputs, and propose a multi-dataset merging method to evaluate runoff variability in ten HMA transboundary basins over the past two decades. Results show that the runoff quantified by the hydrological dataset has relatively maximum uncertainty compared to precipitation and evapotranspiration. The performance of the reconstructed terrestrial water storage change (TWSC) from hydrological dataset varies with basins, and the maximum Nash-Sutcliffe Efficiency (NSE) value ranges from 0.31 to 0.94. Nevertheless, the current hydrological dataset struggles to accurately reconstruct the interannual and annual variability of TWSC, with the maximum cyclostationary NSE (NSEc) value ranging from −1.07 to 0.24. Runoff change in HMA exhibits both overall stability and regional climatic condition-related spatial heterogeneity. A significant downstream change-driven increase trend of runoff occurs in Indus Basin (0.2 ± 0.1 mm/mon/yr), while Brahmaputra Basin (−0.5 ± 0.4 mm/mon/yr) and Salween Basin (−0.4 ± 0.2 mm/mon/yr) show significant runoff decrease trends driven by upstream and downstream changes, respectively. Climate change has exacerbated the instability of runoff in the arid basins over northern HMA, leading to evident increase in annual amplitude. Furthermore, negative correlation is found between temperature and runoff at the interannual scale, especially in Ganges Basin (−19.73 ± 12.53 Gt/month per °C) and Mekong Basin (−17.46 ± 9.43 Gt/month per °C). Our multi-dataset merging methodology can improve the reliability of using global hydrological datasets to quantify runoff variability in poorly in-situ gauged regions, and may also be applicable to the evaluation of precipitation and evapotranspiration.
{"title":"Evaluation of runoff variability in transboundary basins over High Mountain Asia: Multi-dataset merging based on satellite gravimetry constraint","authors":"Jiashuang Jiao , Yuanjin Pan , Xiaoming Cui , Hussein A. Mohasseb , Hao Ding","doi":"10.1016/j.rse.2024.114493","DOIUrl":"10.1016/j.rse.2024.114493","url":null,"abstract":"<div><div>Runoff variability in glacierized transboundary river basins over High Mountain Asia (HMA) directly affects the stability of water supply for more than one billion people in Asia. However, limited by insufficient in-situ gauges and imprecise hydrological model output, it is still a challenge to accurately monitor and comprehensively analyze the HMA runoff change. In this paper, we construct a water budget closure test of water balance equation based on satellite gravimetry constraints to assess the accuracy of hydrological dataset outputs, and propose a multi-dataset merging method to evaluate runoff variability in ten HMA transboundary basins over the past two decades. Results show that the runoff quantified by the hydrological dataset has relatively maximum uncertainty compared to precipitation and evapotranspiration. The performance of the reconstructed terrestrial water storage change (TWSC) from hydrological dataset varies with basins, and the maximum Nash-Sutcliffe Efficiency (NSE) value ranges from 0.31 to 0.94. Nevertheless, the current hydrological dataset struggles to accurately reconstruct the interannual and annual variability of TWSC, with the maximum cyclostationary NSE (NSEc) value ranging from −1.07 to 0.24. Runoff change in HMA exhibits both overall stability and regional climatic condition-related spatial heterogeneity. A significant downstream change-driven increase trend of runoff occurs in Indus Basin (0.2 ± 0.1 mm/mon/yr), while Brahmaputra Basin (−0.5 ± 0.4 mm/mon/yr) and Salween Basin (−0.4 ± 0.2 mm/mon/yr) show significant runoff decrease trends driven by upstream and downstream changes, respectively. Climate change has exacerbated the instability of runoff in the arid basins over northern HMA, leading to evident increase in annual amplitude. Furthermore, negative correlation is found between temperature and runoff at the interannual scale, especially in Ganges Basin (−19.73 ± 12.53 Gt/month per °C) and Mekong Basin (−17.46 ± 9.43 Gt/month per °C). Our multi-dataset merging methodology can improve the reliability of using global hydrological datasets to quantify runoff variability in poorly in-situ gauged regions, and may also be applicable to the evaluation of precipitation and evapotranspiration.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"316 ","pages":"Article 114493"},"PeriodicalIF":11.1,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142599131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-11DOI: 10.1016/j.rse.2024.114499
Liding Wang , Mingyang Lv , Changyong Dou , Yue Cao , Steve Carver , Xiancai Lu , Shaochun Dong , Siming Deng , Huadong Guo
Long-distance hiking trails worldwide serve as vital ‘threads’ connecting vast wilderness areas, offering unique opportunities to evaluate progress toward the United Nations' Sustainable Development Goals (SDGs). However, their extensive lengths pose challenges for data collection, limiting their potential use in sustainable development research. Remote sensing technologies, such as high-spatial-resolution and color glimmer imager data from SDGSAT-1, hold promise in addressing these challenges. This study focuses on seven prominent U.S. long-distance trails: the Appalachian Trail, Arizona National Scenic Trail, Buckeye Trail, Hayduke Trail, Ice Age National Scenic Trail, Pacific Crest Trail, and Pacific Northwest Trail, along with 20 km buffer zones surrounding each trail. By integrating glimmer and population data, we introduce a method to quantify human populations within these wilderness areas. Anthropogenic indicators, including population density, land use, grazing intensity, and transportation networks, are used to develop a wilderness evaluation methodology, employing an enhanced human footprint index. Our findings offer a comparative assessment of the wilderness conditions across the selected trails, providing insights into varying levels of human impact and identifying areas where conservation efforts are most urgently needed.
{"title":"Evaluating the wilderness status of long-distance trails in the United States - Exploring the potential of SDGSAT-1 glimmer imager data","authors":"Liding Wang , Mingyang Lv , Changyong Dou , Yue Cao , Steve Carver , Xiancai Lu , Shaochun Dong , Siming Deng , Huadong Guo","doi":"10.1016/j.rse.2024.114499","DOIUrl":"10.1016/j.rse.2024.114499","url":null,"abstract":"<div><div>Long-distance hiking trails worldwide serve as vital ‘threads’ connecting vast wilderness areas, offering unique opportunities to evaluate progress toward the United Nations' Sustainable Development Goals (SDGs). However, their extensive lengths pose challenges for data collection, limiting their potential use in sustainable development research. Remote sensing technologies, such as high-spatial-resolution and color glimmer imager data from SDGSAT-1, hold promise in addressing these challenges. This study focuses on seven prominent U.S. long-distance trails: the Appalachian Trail, Arizona National Scenic Trail, Buckeye Trail, Hayduke Trail, Ice Age National Scenic Trail, Pacific Crest Trail, and Pacific Northwest Trail, along with 20 km buffer zones surrounding each trail. By integrating glimmer and population data, we introduce a method to quantify human populations within these wilderness areas. Anthropogenic indicators, including population density, land use, grazing intensity, and transportation networks, are used to develop a wilderness evaluation methodology, employing an enhanced human footprint index. Our findings offer a comparative assessment of the wilderness conditions across the selected trails, providing insights into varying levels of human impact and identifying areas where conservation efforts are most urgently needed.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"316 ","pages":"Article 114499"},"PeriodicalIF":11.1,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142599133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-11DOI: 10.1016/j.rse.2024.114491
Beichen Zhang , Kazuhito Ichii , Wei Li , Yuhei Yamamoto , Wei Yang , Ram C. Sharma , Hiroki Yoshioka , Kenta Obata , Masayuki Matsuoka , Tomoaki Miura
Land-surface reflectance (LSR) is a basic physical retrieval in terrestrial monitoring. The potential for high-frequency surface product estimation was evident in third-generation Geostationary Earth Orbit (3rd-GEO) satellites, substantially improving spectral, spatial, and temporal resolutions. Intercomparisons with LSR products from Low Earth Orbit (LEO) satellites have been employed as a common way to evaluate the LSRs of GEO satellites. However, in mid-latitude regions, comparing the LSR between two satellites is challenging due to constraints in the sun–target–sensor geometries. In this study, we proposed a method to obtain observations with consistent viewing and illumination conditions aligned with those of the Himawari-8/Advanced Himawari Imager (AHI) at mid-latitudes, by utilizing forward and backward viewing cameras from LEO sensors, such as Terra/Multi-angle Imaging SpectroRadiometer (MISR). The reflectance intercomparison revealed that the estimated AHI LSR closely matched the LSR from MISR in the red and near-infrared (NIR) bands at latitudes higher than 30°N/S during 2018–2019, with correlation coefficient (r) greater than 0.8 and a relative root mean square error (RRMSE) below 25 %. The data accuracy in the NIR bands was higher than in the red band, as indicated by a lower RRMSE. The correlation was also stronger in non-forested regions compared to forested areas, with higher r values. Additionally, screening observation pairs based on the relative azimuth angle (RAA), which assumes rotational symmetry in LSR, was examined and proved effective for GEO–LEO intercomparisons. This RAA-matching criterion enables reflectance intercomparisons across a wide longitude range at mid-latitudes, including areas like mainland China and New Zealand, where ray-matching is not applicable. The reflectance consistency demonstrated by RAA matches was comparable to that of ray matches, although the RAA-matching is constrained by timing due to the solar location. The findings from this study have potential applications for other satellites.
{"title":"Evaluation of Himawari-8/AHI land surface reflectance at mid-latitudes using LEO sensors with off-nadir observation","authors":"Beichen Zhang , Kazuhito Ichii , Wei Li , Yuhei Yamamoto , Wei Yang , Ram C. Sharma , Hiroki Yoshioka , Kenta Obata , Masayuki Matsuoka , Tomoaki Miura","doi":"10.1016/j.rse.2024.114491","DOIUrl":"10.1016/j.rse.2024.114491","url":null,"abstract":"<div><div>Land-surface reflectance (LSR) is a basic physical retrieval in terrestrial monitoring. The potential for high-frequency surface product estimation was evident in third-generation Geostationary Earth Orbit (3rd-GEO) satellites, substantially improving spectral, spatial, and temporal resolutions. Intercomparisons with LSR products from Low Earth Orbit (LEO) satellites have been employed as a common way to evaluate the LSRs of GEO satellites. However, in mid-latitude regions, comparing the LSR between two satellites is challenging due to constraints in the sun–target–sensor geometries. In this study, we proposed a method to obtain observations with consistent viewing and illumination conditions aligned with those of the Himawari-8/Advanced Himawari Imager (AHI) at mid-latitudes, by utilizing forward and backward viewing cameras from LEO sensors, such as Terra/Multi-angle Imaging SpectroRadiometer (MISR). The reflectance intercomparison revealed that the estimated AHI LSR closely matched the LSR from MISR in the red and near-infrared (NIR) bands at latitudes higher than 30°N/S during 2018–2019, with correlation coefficient (<em>r</em>) greater than 0.8 and a relative root mean square error (RRMSE) below 25 %. The data accuracy in the NIR bands was higher than in the red band, as indicated by a lower RRMSE. The correlation was also stronger in non-forested regions compared to forested areas, with higher <em>r</em> values. Additionally, screening observation pairs based on the relative azimuth angle (RAA), which assumes rotational symmetry in LSR, was examined and proved effective for GEO–LEO intercomparisons. This RAA-matching criterion enables reflectance intercomparisons across a wide longitude range at mid-latitudes, including areas like mainland China and New Zealand, where ray-matching is not applicable. The reflectance consistency demonstrated by RAA matches was comparable to that of ray matches, although the RAA-matching is constrained by timing due to the solar location. The findings from this study have potential applications for other satellites.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"316 ","pages":"Article 114491"},"PeriodicalIF":11.1,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142599135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sea state information is critical for a broad range of human activities (e.g. shipping, marine energy, marine engineering) most of them being concentrated along the coastal zone. Satellite altimeter records of significant wave heights (SWH) represent the largest source of sea state observations available to date. However, the quality of altimeter observations is reduced in the coastal zone due to surface heterogeneity within the radar signal footprint. Major difficulties to assess the performance of coastal altimetry in the coastal zone are the reduced number of valid altimeter records and the increased sea state variability, which have recently fostered the development of new methods to pair and compare nearby altimeter and buoy data. In this study, we use a high-resolution numerical wave model implemented over the European coastal waters in order to characterize the spatial variability of sea states in the proximity of coastal in situ buoys, we explore different model-based data-pairing methods to account for coastal sea state variability and we assess their impact on the validation of Sentinel-3A 20Hz SWH measurements. Three Sentinel-3A processing modes are considered: the pseudo low rate mode processing, the SAR processing and the Low Resolution with Range Migration Correction (LR-RMC) processing. Our results indicate major impacts of data-pairing methods on the Sentinel-3A coastal validation and reveals the contribution of more frequent low SWH conditions, poorly resolved by radar altimeters, in the coastal zone as an additional source of errors in coastal altimetry.
{"title":"Impact of altimeter-buoy data-pairing methods on the validation of Sentinel-3A coastal significant wave heights","authors":"Guillaume Dodet , Grégoire Mureau , Mickaël Accensi , Jean-François Piollé","doi":"10.1016/j.rse.2024.114483","DOIUrl":"10.1016/j.rse.2024.114483","url":null,"abstract":"<div><div>Sea state information is critical for a broad range of human activities (e.g. shipping, marine energy, marine engineering) most of them being concentrated along the coastal zone. Satellite altimeter records of significant wave heights (SWH) represent the largest source of sea state observations available to date. However, the quality of altimeter observations is reduced in the coastal zone due to surface heterogeneity within the radar signal footprint. Major difficulties to assess the performance of coastal altimetry in the coastal zone are the reduced number of valid altimeter records and the increased sea state variability, which have recently fostered the development of new methods to pair and compare nearby altimeter and buoy data. In this study, we use a high-resolution numerical wave model implemented over the European coastal waters in order to characterize the spatial variability of sea states in the proximity of coastal in situ buoys, we explore different model-based data-pairing methods to account for coastal sea state variability and we assess their impact on the validation of Sentinel-3A 20Hz SWH measurements. Three Sentinel-3A processing modes are considered: the pseudo low rate mode processing, the SAR processing and the Low Resolution with Range Migration Correction (LR-RMC) processing. Our results indicate major impacts of data-pairing methods on the Sentinel-3A coastal validation and reveals the contribution of more frequent low SWH conditions, poorly resolved by radar altimeters, in the coastal zone as an additional source of errors in coastal altimetry.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"316 ","pages":"Article 114483"},"PeriodicalIF":11.1,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142588930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-06DOI: 10.1016/j.rse.2024.114477
Jonas-Frederik Jans , Ezra Beernaert , Morgane De Breuck , Isis Brangers , Devon Dunmire , Gabrielle De Lannoy , Hans Lievens
The physical drivers of Sentinel-1 C-band backscatter observations during snow accumulation are still uncertain. To investigate these, backscatter fluctuations (in co-polarization VV, cross-polarization VH, and cross-polarization ratio VH-VV) were temporally and spatially linked to modeled surface (0–10 cm) soil moisture (SM) and soil temperature (T) (here referred to as soil dynamics) and modeled snow depth (SD) and snow water equivalent (SWE) (snow dynamics) in the bare and herbaceous regions of the Alps at a spatial resolution of 1 km. Results demonstrate that, during snow accumulation and at a regional scale, VH and VH-VV variability is primarily influenced by SD and SWE, whereas VV fluctuations are driven by a combination of soil and snow dynamics. At low local incidence angles, VV is driven by snow dynamics rather than by soil dynamics, which results in a decreased sensitivity of VH-VV to snow accumulation, potentially degrading VH-VV based SD retrieval. Additionally, polarimetric and interferometric Sentinel-1 observations are generated to assess their sensitivity to snow dynamics. Results show that polarimetric (from entropy- dual-pol decomposition) and the first Stokes parameter are more sensitive to SD than VH-VV and VV, respectively, suggesting the potential for improved SD retrievals. Finally, results show that interferometric 6-day coherence observations respond to modeled SWE accumulation, with low coherence values after significant SWE accumulation and higher values in case of minor SWE changes.
{"title":"Sensitivity of Sentinel-1 C-band SAR backscatter, polarimetry and interferometry to snow accumulation in the Alps","authors":"Jonas-Frederik Jans , Ezra Beernaert , Morgane De Breuck , Isis Brangers , Devon Dunmire , Gabrielle De Lannoy , Hans Lievens","doi":"10.1016/j.rse.2024.114477","DOIUrl":"10.1016/j.rse.2024.114477","url":null,"abstract":"<div><div>The physical drivers of Sentinel-1 C-band backscatter observations during snow accumulation are still uncertain. To investigate these, backscatter fluctuations (in co-polarization VV, cross-polarization VH, and cross-polarization ratio VH-VV) were temporally and spatially linked to modeled surface (0–10 cm) soil moisture (SM) and soil temperature (T) (here referred to as soil dynamics) and modeled snow depth (SD) and snow water equivalent (SWE) (snow dynamics) in the bare and herbaceous regions of the Alps at a spatial resolution of 1 km. Results demonstrate that, during snow accumulation and at a regional scale, VH and VH-VV variability is primarily influenced by SD and SWE, whereas VV fluctuations are driven by a combination of soil and snow dynamics. At low local incidence angles, VV is driven by snow dynamics rather than by soil dynamics, which results in a decreased sensitivity of VH-VV to snow accumulation, potentially degrading VH-VV based SD retrieval. Additionally, polarimetric and interferometric Sentinel-1 observations are generated to assess their sensitivity to snow dynamics. Results show that polarimetric <span><math><mi>α</mi></math></span> (from entropy-<span><math><mi>α</mi></math></span> dual-pol decomposition) and the first Stokes parameter are more sensitive to SD than VH-VV and VV, respectively, suggesting the potential for improved SD retrievals. Finally, results show that interferometric 6-day coherence observations respond to modeled SWE accumulation, with low coherence values after significant SWE accumulation and higher values in case of minor SWE changes.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"316 ","pages":"Article 114477"},"PeriodicalIF":11.1,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142588308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-06DOI: 10.1016/j.rse.2024.114490
Weiwei Liu , Matti Mõttus , Zbyněk Malenovský , Shengwei Shi , Luis Alonso , Jon Atherton , Albert Porcar-Castell
The intensity and spectral properties of solar-induced chlorophyll fluorescence (SIF) carry valuable information on plant photosynthesis and productivity, but are also influenced by leaf and canopy structure. Physically based models provide a quantitative means to investigate how SIF intensity and spectra propagate and scale from the photosystem to the leaf and to the canopy levels. However, the validation of canopy SIF models is limited by the lack of methods that combine direct, independent, and complementary measurements of the full fluorescence spectrum at the leaf and canopy levels. Here, we propose a novel validation approach that combines in situ measurements of leaf and canopy fluorescence spectra. The approach is demonstrated with measurements in a rice crop at two contrasting stages of canopy development. We measured leaf reflectance, transmittance, and fluorescence spectra in situ, and subsequently inverted leaf structural and biochemical parameters and determined the leaf fluorescence quantum efficiency (FQE) using the Fluspect-Cx model. Two FQE inversion methods (Inversion-IIA and Inversion-IIB) were tested for the forward simulation of leaf fluorescence spectra. Leaf fluorescence spectra were then scaled up to the canopy level using 1D, 2D, and 3D radiative transfer schemes (SCOPE, mSCOPE, and DART), and compared with the direct canopy fluorescence spectral observations measured under red, green, blue, and white illumination. The validation results demonstrate that accounting for 3D canopy structure, as in the DART model, is critical to successfully scale the fluorescence spectrum from the leaf to the canopy level, whereas 1D SCOPE or even 2D mSCOPE were unable to fully reproduce the canopy fluorescence spectra. The results also demonstrate that the Inversion-IIB method matches relatively well the measurements with mean relative absolute errors (MRAE) of 20 %, 37 %, and 43 % versus Inversion-IIA with mean relative absolute errors (MRAE) of 62 %, 100 %, and 108 % for DART, mSCOPE, and SCOPE, respectively. We suggest that our validation approach is transferable to other plant species and canopy geometries, providing a means to standardize and evaluate the performance of canopy SIF models and improve our understanding of canopy SIF observations.
{"title":"An in situ approach for validation of canopy chlorophyll fluorescence radiative transfer models using the full emission spectrum","authors":"Weiwei Liu , Matti Mõttus , Zbyněk Malenovský , Shengwei Shi , Luis Alonso , Jon Atherton , Albert Porcar-Castell","doi":"10.1016/j.rse.2024.114490","DOIUrl":"10.1016/j.rse.2024.114490","url":null,"abstract":"<div><div>The intensity and spectral properties of solar-induced chlorophyll fluorescence (SIF) carry valuable information on plant photosynthesis and productivity, but are also influenced by leaf and canopy structure. Physically based models provide a quantitative means to investigate how SIF intensity and spectra propagate and scale from the photosystem to the leaf and to the canopy levels. However, the validation of canopy SIF models is limited by the lack of methods that combine direct, independent, and complementary measurements of the full fluorescence spectrum at the leaf and canopy levels. Here, we propose a novel validation approach that combines in situ measurements of leaf and canopy fluorescence spectra. The approach is demonstrated with measurements in a rice crop at two contrasting stages of canopy development. We measured leaf reflectance, transmittance, and fluorescence spectra in situ, and subsequently inverted leaf structural and biochemical parameters and determined the leaf fluorescence quantum efficiency (FQE) using the Fluspect-Cx model. Two FQE inversion methods (Inversion-IIA and Inversion-IIB) were tested for the forward simulation of leaf fluorescence spectra. Leaf fluorescence spectra were then scaled up to the canopy level using 1D, 2D, and 3D radiative transfer schemes (SCOPE, mSCOPE, and DART), and compared with the direct canopy fluorescence spectral observations measured under red, green, blue, and white illumination. The validation results demonstrate that accounting for 3D canopy structure, as in the DART model, is critical to successfully scale the fluorescence spectrum from the leaf to the canopy level, whereas 1D SCOPE or even 2D mSCOPE were unable to fully reproduce the canopy fluorescence spectra. The results also demonstrate that the Inversion-IIB method matches relatively well the measurements with mean relative absolute errors (MRAE) of 20 %, 37 %, and 43 % versus Inversion-IIA with mean relative absolute errors (MRAE) of 62 %, 100 %, and 108 % for DART, mSCOPE, and SCOPE, respectively. We suggest that our validation approach is transferable to other plant species and canopy geometries, providing a means to standardize and evaluate the performance of canopy SIF models and improve our understanding of canopy SIF observations.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"316 ","pages":"Article 114490"},"PeriodicalIF":11.1,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142592604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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