Pub Date : 2025-03-01DOI: 10.1016/j.rse.2025.114680
Peiqi Yang , Wout Verhoef , Hongliang Fang , Wenjie Fan , Christiaan van der Tol
<div><div>Radiative transfer (RT) theories formulate vegetation radiative transfer models (RTMs) that link the biophysical properties of vegetation with remote sensing signals. Compared to classical RT theories, the recollision probability theory (also known as p-theory) is distinctive as it predicts some optical properties of vegetation canopies using fewer spectral invariants and simpler mathematical functions. This theory commonly employs an effective recollision probability (<span><math><msub><mi>p</mi><mi>E</mi></msub></math></span>) that is assumed to spectrally independent for vegetation-photon interactions, to describe the absorptive and reflective properties of a vegetation canopy at any wavelength. Most p-theory studies approximate <span><math><msub><mi>p</mi><mi>E</mi></msub></math></span> using the canopy-average recollision probability at different locations within the canopy, enabling its estimation based on canopy structural properties. However, the canopy-average recollision probability and <span><math><msub><mi>p</mi><mi>E</mi></msub></math></span> different meanings. As an effective parameter, <span><math><msub><mi>p</mi><mi>E</mi></msub></math></span> should be obtained by fitting the p-theory formulations, as done in previous studies using simulated and measured canopy optical properties for specific canopies. These studies have empirically shown that <span><math><msub><mi>p</mi><mi>E</mi></msub></math></span> generally increases with canopy leaf area and exhibits some spectral variability. Building on this empirical evidence, we explore an analytical expression for <span><math><msub><mi>p</mi><mi>E</mi></msub></math></span> and its dependence on leaf optical and canopy structural properties.</div><div>In this study, we link the recollision probability theory with the classical Kubelka-Munk (KM) theory, a two-stream RT theory which predicts canopy optical properties by solving the corresponding differential equations. By using the KM theory as applied in the SAIL model, we derive the analytical expression for the absorptance of vegetation canopies illuminated by diffuse radiation. This absorptance is then used to derive <span><math><msub><mi>p</mi><mi>E</mi></msub></math></span> based on its relationship with absorptance in the p-theory. In this way, we express <span><math><msub><mi>p</mi><mi>E</mi></msub></math></span> as a function of leaf albedo (<span><math><msub><mi>ω</mi><mi>l</mi></msub></math></span>) and canopy leaf area index (LAI, <span><math><mi>L</mi></math></span>). Our findings demonstrate that, for a given canopy, <span><math><msub><mi>p</mi><mi>E</mi></msub></math></span> could be approximated as a function of LAI (<span><math><msub><mi>p</mi><mi>L</mi></msub></math></span>) by using Taylor series expansion. This approximation aligns with Stenberg's, 2007 canopy-average recollision probability, although the two have different meanings and are derived using different approaches. More importantly, we demonstrate
{"title":"Linking Kubelka-Munk and recollision probability theories for radiative transfer simulations in turbid canopy","authors":"Peiqi Yang , Wout Verhoef , Hongliang Fang , Wenjie Fan , Christiaan van der Tol","doi":"10.1016/j.rse.2025.114680","DOIUrl":"10.1016/j.rse.2025.114680","url":null,"abstract":"<div><div>Radiative transfer (RT) theories formulate vegetation radiative transfer models (RTMs) that link the biophysical properties of vegetation with remote sensing signals. Compared to classical RT theories, the recollision probability theory (also known as p-theory) is distinctive as it predicts some optical properties of vegetation canopies using fewer spectral invariants and simpler mathematical functions. This theory commonly employs an effective recollision probability (<span><math><msub><mi>p</mi><mi>E</mi></msub></math></span>) that is assumed to spectrally independent for vegetation-photon interactions, to describe the absorptive and reflective properties of a vegetation canopy at any wavelength. Most p-theory studies approximate <span><math><msub><mi>p</mi><mi>E</mi></msub></math></span> using the canopy-average recollision probability at different locations within the canopy, enabling its estimation based on canopy structural properties. However, the canopy-average recollision probability and <span><math><msub><mi>p</mi><mi>E</mi></msub></math></span> different meanings. As an effective parameter, <span><math><msub><mi>p</mi><mi>E</mi></msub></math></span> should be obtained by fitting the p-theory formulations, as done in previous studies using simulated and measured canopy optical properties for specific canopies. These studies have empirically shown that <span><math><msub><mi>p</mi><mi>E</mi></msub></math></span> generally increases with canopy leaf area and exhibits some spectral variability. Building on this empirical evidence, we explore an analytical expression for <span><math><msub><mi>p</mi><mi>E</mi></msub></math></span> and its dependence on leaf optical and canopy structural properties.</div><div>In this study, we link the recollision probability theory with the classical Kubelka-Munk (KM) theory, a two-stream RT theory which predicts canopy optical properties by solving the corresponding differential equations. By using the KM theory as applied in the SAIL model, we derive the analytical expression for the absorptance of vegetation canopies illuminated by diffuse radiation. This absorptance is then used to derive <span><math><msub><mi>p</mi><mi>E</mi></msub></math></span> based on its relationship with absorptance in the p-theory. In this way, we express <span><math><msub><mi>p</mi><mi>E</mi></msub></math></span> as a function of leaf albedo (<span><math><msub><mi>ω</mi><mi>l</mi></msub></math></span>) and canopy leaf area index (LAI, <span><math><mi>L</mi></math></span>). Our findings demonstrate that, for a given canopy, <span><math><msub><mi>p</mi><mi>E</mi></msub></math></span> could be approximated as a function of LAI (<span><math><msub><mi>p</mi><mi>L</mi></msub></math></span>) by using Taylor series expansion. This approximation aligns with Stenberg's, 2007 canopy-average recollision probability, although the two have different meanings and are derived using different approaches. More importantly, we demonstrate","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"321 ","pages":"Article 114680"},"PeriodicalIF":11.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143526340","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 : 2025-02-28DOI: 10.1016/j.rse.2025.114657
Zhijun Zhen , Shengbo Chen , Nicolas Lauret , Abdelaziz Kallel , Eric Chavanon , Tiangang Yin , Jonathan León-Tavares , Biao Cao , Jordan Guilleux , Jean-Philippe Gastellu-Etchegorry
Unmixing optical properties (OP) of land covers from coarse spatial resolution images is crucial for microclimate and energy balance studies. We propose the Unmixing Spectral method using Discrete Anisotropic Radiative Transfer (DART) model (US-DART), a novel approach for unmixing endmember OP in the shortwave domain from mono- or multispectral remotely sensed images. US-DART comprises four modules: pure pixel selection, linear spectral mixture analysis, gradient iterations, and spectral correlation. US-DART requires a surface reflectance image, a 3D mock-up with facets’ group information, and standard DART parameters (e.g., spatial resolution and skylight ratio) as inputs, producing an OP map for each scene element. The accuracy of US-DART is evaluated using two types of scenes (vegetation and urban) and images (Sentinel-2 surface reflectance and DART-simulated pseudo-satellite images). Results demonstrate a median relative error of approximately 0.1 % for pixel reflectance, with higher accuracy for opaque surfaces compared to translucent materials. Excluding co-registration errors and sensor noise, the median relative error of OP is typically around 1 % for opaque elements and 1–5 % for translucent elements with an accurate a priori “reflectance-transmittance” ratio. US-DART enhances our ability to derive detailed OP from coarse-resolution imagery, potentially enabling more accurate modeling of spatial resolution conversions, and energy dynamics, including albedo and shortwave radiation balance, across diverse environments.
{"title":"A gradient-based 3D nonlinear spectral model for providing components optical properties of mixed pixels in shortwave urban images","authors":"Zhijun Zhen , Shengbo Chen , Nicolas Lauret , Abdelaziz Kallel , Eric Chavanon , Tiangang Yin , Jonathan León-Tavares , Biao Cao , Jordan Guilleux , Jean-Philippe Gastellu-Etchegorry","doi":"10.1016/j.rse.2025.114657","DOIUrl":"10.1016/j.rse.2025.114657","url":null,"abstract":"<div><div>Unmixing optical properties (OP) of land covers from coarse spatial resolution images is crucial for microclimate and energy balance studies. We propose the Unmixing Spectral method using Discrete Anisotropic Radiative Transfer (DART) model (US-DART), a novel approach for unmixing endmember OP in the shortwave domain from mono- or multispectral remotely sensed images. US-DART comprises four modules: pure pixel selection, linear spectral mixture analysis, gradient iterations, and spectral correlation. US-DART requires a surface reflectance image, a 3D mock-up with facets’ group information, and standard DART parameters (e.g., spatial resolution and skylight ratio) as inputs, producing an OP map for each scene element. The accuracy of US-DART is evaluated using two types of scenes (vegetation and urban) and images (Sentinel-2 surface reflectance and DART-simulated pseudo-satellite images). Results demonstrate a median relative error of approximately 0.1 % for pixel reflectance, with higher accuracy for opaque surfaces compared to translucent materials. Excluding co-registration errors and sensor noise, the median relative error of OP is typically around 1 % for opaque elements and 1–5 % for translucent elements with an accurate a priori “reflectance-transmittance” ratio. US-DART enhances our ability to derive detailed OP from coarse-resolution imagery, potentially enabling more accurate modeling of spatial resolution conversions, and energy dynamics, including albedo and shortwave radiation balance, across diverse environments.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"321 ","pages":"Article 114657"},"PeriodicalIF":11.1,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143511702","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 : 2025-02-28DOI: 10.1016/j.rse.2025.114686
Jinghong Xu , Qun Liu , Chong Liu , Yatong Chen , Peituo Xu , Yue Ma , Yifu Chen , Yudi Zhou , Han Zhang , Wenbo Sun , Suhui Yang , Weige Lv , Lan Wu , Dong Liu
Accurate retrieval of sea surface wind speed is crucial for ecological research and marine resource development. The advent of satellite technology provides a feasible approach for global wind speed retrieval. As a photon-counting lidar, ICESat-2 provides unparalleled details of the sea surface and has the potential for sea surface wind speed retrieval. To facilitate the retrieval of sea surface wind speed from ICESat-2, a vertical ocean signal distribution model of ICESat-2 was established, and then training samples were collected by changing the parameters and inputted into the back propagation neural network to fit the relationship between the ICESat-2 vertical distribution signal and the sea surface wind speed. The model considered both environmental factors (solar noise, atmospheric absorption, sea surface reflection, water backscattering, etc.) and hardware characteristics (the spatial and temporal distribution of laser energy, dead time, and dark noise of the detectors, etc.). The validation against MERRA-2 data revealed that the RMSE is 1.57 m/s for nighttime and 1.89 m/s for daytime, while buoy comparisons showed RMSE values of 1.53 m/s for nighttime and 1.82 m/s for daytime. Additionally, comparisons of global monthly mean results also agree well, underscoring the capability of ICESat-2 in sea surface wind speed retrieval.
{"title":"Sea surface wind speed retrieval based on ICESat-2 ocean signal vertical distribution","authors":"Jinghong Xu , Qun Liu , Chong Liu , Yatong Chen , Peituo Xu , Yue Ma , Yifu Chen , Yudi Zhou , Han Zhang , Wenbo Sun , Suhui Yang , Weige Lv , Lan Wu , Dong Liu","doi":"10.1016/j.rse.2025.114686","DOIUrl":"10.1016/j.rse.2025.114686","url":null,"abstract":"<div><div>Accurate retrieval of sea surface wind speed is crucial for ecological research and marine resource development. The advent of satellite technology provides a feasible approach for global wind speed retrieval. As a photon-counting lidar, ICESat-2 provides unparalleled details of the sea surface and has the potential for sea surface wind speed retrieval. To facilitate the retrieval of sea surface wind speed from ICESat-2, a vertical ocean signal distribution model of ICESat-2 was established, and then training samples were collected by changing the parameters and inputted into the back propagation neural network to fit the relationship between the ICESat-2 vertical distribution signal and the sea surface wind speed. The model considered both environmental factors (solar noise, atmospheric absorption, sea surface reflection, water backscattering, etc.) and hardware characteristics (the spatial and temporal distribution of laser energy, dead time, and dark noise of the detectors, etc.). The validation against MERRA-2 data revealed that the RMSE is 1.57 m/s for nighttime and 1.89 m/s for daytime, while buoy comparisons showed RMSE values of 1.53 m/s for nighttime and 1.82 m/s for daytime. Additionally, comparisons of global monthly mean results also agree well, underscoring the capability of ICESat-2 in sea surface wind speed retrieval.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"321 ","pages":"Article 114686"},"PeriodicalIF":11.1,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143511703","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 : 2025-02-27DOI: 10.1016/j.rse.2025.114682
Artur Guzy , Adam Piasecki , Wojciech T. Witkowski
Climate change significantly compromises global water resources, particularly shallow aquifer systems, which are vulnerable to variations in precipitation and evapotranspiration. This study investigated the impacts of climate change on a shallow aquifer system in the Gniezno Lakeland, Poland, by analysing the relationship among ground motion, hydraulic head changes, surface water variations, and meteorological trends. We used EGMS-based InSAR ground motion products to detect subtle land surface displacements across the study area, combined with hydrogeological data, meteorological records, and surface water measurements. Our results revealed a slight but ongoing subsidence of −0.9 mm/year across the area, with variations observed across different land cover types and wetlands being the most affected. Seasonal oscillations in hydraulic head (8–50 cm) and ground motion (2–7 mm) highlighted the aquifer's elastic response to climate variability. Long-term meteorological data indicated a trend towards a drier climate, with annual increases in temperature (+0.5 °C), insolation (+6.8 h), and evaporation (+3.8 mm), coupled with decreasing humidity (−0.13 %/year). The annual negative vertical water exchange, exceeding the volume of groundwater extraction, suggests that climate-driven factors are the primary drivers of aquifer storage decline. The aquifer system exhibited greater resilience to climate change than surface water, as evidenced by its annual storage change (∼2 % of lake volume fluctuations). Localized subsidence patterns near the lake shoreline further underscored the interplay between surface water and groundwater in this region. Our findings provide insights into the impacts of climate change on shallow aquifer systems and highlight the importance of integrating multisource data for comprehensive hydrogeological assessments.
{"title":"Climate change and shallow aquifers - Unravelling local hydrogeological impacts and groundwater decline-induced subsidence","authors":"Artur Guzy , Adam Piasecki , Wojciech T. Witkowski","doi":"10.1016/j.rse.2025.114682","DOIUrl":"10.1016/j.rse.2025.114682","url":null,"abstract":"<div><div>Climate change significantly compromises global water resources, particularly shallow aquifer systems, which are vulnerable to variations in precipitation and evapotranspiration. This study investigated the impacts of climate change on a shallow aquifer system in the Gniezno Lakeland, Poland, by analysing the relationship among ground motion, hydraulic head changes, surface water variations, and meteorological trends. We used EGMS-based InSAR ground motion products to detect subtle land surface displacements across the study area, combined with hydrogeological data, meteorological records, and surface water measurements. Our results revealed a slight but ongoing subsidence of −0.9 mm/year across the area, with variations observed across different land cover types and wetlands being the most affected. Seasonal oscillations in hydraulic head (8–50 cm) and ground motion (2–7 mm) highlighted the aquifer's elastic response to climate variability. Long-term meteorological data indicated a trend towards a drier climate, with annual increases in temperature (+0.5 °C), insolation (+6.8 h), and evaporation (+3.8 mm), coupled with decreasing humidity (−0.13 %/year). The annual negative vertical water exchange, exceeding the volume of groundwater extraction, suggests that climate-driven factors are the primary drivers of aquifer storage decline. The aquifer system exhibited greater resilience to climate change than surface water, as evidenced by its annual storage change (∼2 % of lake volume fluctuations). Localized subsidence patterns near the lake shoreline further underscored the interplay between surface water and groundwater in this region. Our findings provide insights into the impacts of climate change on shallow aquifer systems and highlight the importance of integrating multisource data for comprehensive hydrogeological assessments.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"321 ","pages":"Article 114682"},"PeriodicalIF":11.1,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143509753","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 : 2025-02-27DOI: 10.1016/j.rse.2025.114684
Jie Li , Yingtao Wei , Liupeng Lin , Qiangqiang Yuan , Huanfeng Shen
Soil moisture (SM) is a key state variable in agricultural, hydrological, and ecological studies. Microwave remote sensing can retrieve soil moisture at regional or global scales, but is limited by coarse spatial resolution. In order to generate large-scale, spatiotemporally seamless soil moisture of high precision, we propose a two-stage downscaling and correction cascade learning framework by fusing multi-sourced remote sensing and in-situ data. Under the framework, the Hybrid Attention based residual dense Network for soil moisture Downscaling (HAND) is developed to downscale the Soil Moisture Active Passive (SMAP) SM products from 36 km to 1 km effectively. The Random Forest method is subsequently employed to correct the downscaled SM products by in-situ measurements and the 1 km seamless daily SM products of high precision are then generated. The soil moisture downscaling network adopts the Residual Dense connection Network (RDN) as the backbone and embeds a multi-factor interactive attention module, a cross-attention module, and the hybrid attention block with increased/ decreased receptive field, to comprehensively extract the complex relationships between geoscience parameters and soil moisture. The western continental of the United States is served as the study area of this paper, covering 2016–2020. The Pearson correlation (R, unitless) and the Unbiased Root-Mean-Square Error (UbRMSE, ) values of the HAND downscaled products with SMAP are 0.65 and 0.066 , showing the ability of HAND model to achieve satisfactory accuracy while maintaining consistency with original SMAP products, as well as restoring fine spatial details. After the in-situ correction, the R and UbRMSE values of ten-folder cross validation against the in-situ SM reach 0.92 and 0.033, while the metrics of SMAP SM against the in-situ SM are 0.46 and 0.083 , which demonstrates great potential of the proposed method in water resources management at regional scale.
{"title":"Two-stage downscaling and correction cascade learning framework for generating long-time series seamless soil moisture","authors":"Jie Li , Yingtao Wei , Liupeng Lin , Qiangqiang Yuan , Huanfeng Shen","doi":"10.1016/j.rse.2025.114684","DOIUrl":"10.1016/j.rse.2025.114684","url":null,"abstract":"<div><div>Soil moisture (SM) is a key state variable in agricultural, hydrological, and ecological studies. Microwave remote sensing can retrieve soil moisture at regional or global scales, but is limited by coarse spatial resolution. In order to generate large-scale, spatiotemporally seamless soil moisture of high precision, we propose a two-stage downscaling and correction cascade learning framework by fusing multi-sourced remote sensing and in-situ data. Under the framework, the Hybrid Attention based residual dense Network for soil moisture Downscaling (HAND) is developed to downscale the Soil Moisture Active Passive (SMAP) SM products from 36 km to 1 km effectively. The Random Forest method is subsequently employed to correct the downscaled SM products by in-situ measurements and the 1 km seamless daily SM products of high precision are then generated. The soil moisture downscaling network adopts the Residual Dense connection Network (RDN) as the backbone and embeds a multi-factor interactive attention module, a cross-attention module, and the hybrid attention block with increased/ decreased receptive field, to comprehensively extract the complex relationships between geoscience parameters and soil moisture. The western continental of the United States is served as the study area of this paper, covering 2016–2020. The Pearson correlation (R, unitless) and the Unbiased Root-Mean-Square Error (UbRMSE, <span><math><msup><mi>m</mi><mn>3</mn></msup><mo>/</mo><msup><mi>m</mi><mn>3</mn></msup></math></span>) values of the HAND downscaled products with SMAP are 0.65 and 0.066 <span><math><msup><mi>m</mi><mn>3</mn></msup><mo>/</mo><msup><mi>m</mi><mn>3</mn></msup></math></span>, showing the ability of HAND model to achieve satisfactory accuracy while maintaining consistency with original SMAP products, as well as restoring fine spatial details. After the in-situ correction, the R and UbRMSE values of ten-folder cross validation against the in-situ SM reach 0.92 and 0.033<span><math><msup><mi>m</mi><mn>3</mn></msup><mo>/</mo><msup><mi>m</mi><mn>3</mn></msup></math></span>, while the metrics of SMAP SM against the in-situ SM are 0.46 and 0.083 <span><math><msup><mi>m</mi><mn>3</mn></msup><mo>/</mo><msup><mi>m</mi><mn>3</mn></msup></math></span>, which demonstrates great potential of the proposed method in water resources management at regional scale.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"321 ","pages":"Article 114684"},"PeriodicalIF":11.1,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143510103","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 : 2025-02-27DOI: 10.1016/j.rse.2025.114683
Wenkai Li , Shilin Tang , Liqiao Tian , Hongmei Zhao , Haibin Ye , Wendi Zheng , Yupeng Liu , Ling Sun
<div><div>The Sustainable Development Science Satellite 1 (SDGSAT-1) is the first satellite developed specifically for implementing the UN 2030 Agenda for Sustainable Development. The multispectral imager (MII) onboard SDGSAT-1 provides advanced capabilities for coastal and inland water environment analysis but requires comprehensive radiometric performance evaluation for effective water monitoring. In this study, the radiometric performance of SDGSAT-1 MII was evaluated for water quality monitoring by assessing its signal-to-noise ratio (SNR) and radiometric sensitivity to variations in suspended particulate matter (SPM). The SNR was statistically estimated from homogeneous waters over the South China Sea (SCS), and radiometric sensitivity was simulated using the Hydrolight software under varied SPM conditions. Results indicated that SDGSAT-1 MII exhibits significantly improved SNR and radiometric sensitivity compared to commonly used satellite sensors (Landsat-8 OLI and Sentinel-2B MSI), extensively applied in turbid water monitoring. Preliminary validation of SDGSAT-1 MII remote sensing reflectance (<span><math><msub><mi>R</mi><mi>rs</mi></msub></math></span>) derived from Acolite DSF against Aeronet-OC measurements demonstrated strong agreement at 438 nm (<span><math><msup><mi>r</mi><mn>2</mn></msup></math></span>=0.98 and <em>NRMSE</em> = 9.04 %), 495 nm (<span><math><msup><mi>r</mi><mn>2</mn></msup></math></span>=0.94 and <em>NRMSE</em> = 16.39 %), 553 nm (<span><math><msup><mi>r</mi><mn>2</mn></msup></math></span>=0.99 and <em>NRMSE</em> = 7.97 %) and 657 nm (<span><math><msup><mi>r</mi><mn>2</mn></msup></math></span>=0.77 and <em>NRMSE</em> = 35.85 %). In addition, retrieved <span><math><msub><mi>R</mi><mi>rs</mi></msub></math></span> from SDGSAT-1 MII showed good consistency with Sentinel-3B OLCI at 438 nm (<span><math><msup><mi>r</mi><mn>2</mn></msup></math></span>=0.7 and <em>NRMSE</em> = 23.32 %), 495 nm (<span><math><msup><mi>r</mi><mn>2</mn></msup></math></span>=0.8 and <em>NRMSE</em> = 19.55 %), 553 nm (<span><math><msup><mi>r</mi><mn>2</mn></msup></math></span>=0.96 and <em>NRMSE</em> = 11.07 %) and 657 nm (<span><math><msup><mi>r</mi><mn>2</mn></msup></math></span>=0.93 and <em>NRMSE</em> = 31.30 %). However, the consistency of <span><math><msub><mi>R</mi><mi>rs</mi></msub></math></span> at the 401 nm and near-infrared bands (776 nm and 854 nm) was substantially lower relative to other bands. Regarding SPM mapping in the PRE, spatial consistency between the SDGSAT-1 MII and reference sensors remained high (Landsat-8 OLI: <span><math><msup><mi>r</mi><mn>2</mn></msup></math></span>=0.78 and <em>NRMSE</em> = 19.96 %, Sentinel-3B OLCI: <span><math><msup><mi>r</mi><mn>2</mn></msup></math></span>=0.78 and <em>NRMSE</em> = 19.96 %). Overall, these findings highlight the strong potential of SDGSAT-1 MII for monitoring coastal turbid waters, while also noting certain spectral limitations, especially for the shorter (401 nm) and near-infra
{"title":"Assessing on-orbit radiometric performance of SDGSAT-1 MII for turbid water remote sensing","authors":"Wenkai Li , Shilin Tang , Liqiao Tian , Hongmei Zhao , Haibin Ye , Wendi Zheng , Yupeng Liu , Ling Sun","doi":"10.1016/j.rse.2025.114683","DOIUrl":"10.1016/j.rse.2025.114683","url":null,"abstract":"<div><div>The Sustainable Development Science Satellite 1 (SDGSAT-1) is the first satellite developed specifically for implementing the UN 2030 Agenda for Sustainable Development. The multispectral imager (MII) onboard SDGSAT-1 provides advanced capabilities for coastal and inland water environment analysis but requires comprehensive radiometric performance evaluation for effective water monitoring. In this study, the radiometric performance of SDGSAT-1 MII was evaluated for water quality monitoring by assessing its signal-to-noise ratio (SNR) and radiometric sensitivity to variations in suspended particulate matter (SPM). The SNR was statistically estimated from homogeneous waters over the South China Sea (SCS), and radiometric sensitivity was simulated using the Hydrolight software under varied SPM conditions. Results indicated that SDGSAT-1 MII exhibits significantly improved SNR and radiometric sensitivity compared to commonly used satellite sensors (Landsat-8 OLI and Sentinel-2B MSI), extensively applied in turbid water monitoring. Preliminary validation of SDGSAT-1 MII remote sensing reflectance (<span><math><msub><mi>R</mi><mi>rs</mi></msub></math></span>) derived from Acolite DSF against Aeronet-OC measurements demonstrated strong agreement at 438 nm (<span><math><msup><mi>r</mi><mn>2</mn></msup></math></span>=0.98 and <em>NRMSE</em> = 9.04 %), 495 nm (<span><math><msup><mi>r</mi><mn>2</mn></msup></math></span>=0.94 and <em>NRMSE</em> = 16.39 %), 553 nm (<span><math><msup><mi>r</mi><mn>2</mn></msup></math></span>=0.99 and <em>NRMSE</em> = 7.97 %) and 657 nm (<span><math><msup><mi>r</mi><mn>2</mn></msup></math></span>=0.77 and <em>NRMSE</em> = 35.85 %). In addition, retrieved <span><math><msub><mi>R</mi><mi>rs</mi></msub></math></span> from SDGSAT-1 MII showed good consistency with Sentinel-3B OLCI at 438 nm (<span><math><msup><mi>r</mi><mn>2</mn></msup></math></span>=0.7 and <em>NRMSE</em> = 23.32 %), 495 nm (<span><math><msup><mi>r</mi><mn>2</mn></msup></math></span>=0.8 and <em>NRMSE</em> = 19.55 %), 553 nm (<span><math><msup><mi>r</mi><mn>2</mn></msup></math></span>=0.96 and <em>NRMSE</em> = 11.07 %) and 657 nm (<span><math><msup><mi>r</mi><mn>2</mn></msup></math></span>=0.93 and <em>NRMSE</em> = 31.30 %). However, the consistency of <span><math><msub><mi>R</mi><mi>rs</mi></msub></math></span> at the 401 nm and near-infrared bands (776 nm and 854 nm) was substantially lower relative to other bands. Regarding SPM mapping in the PRE, spatial consistency between the SDGSAT-1 MII and reference sensors remained high (Landsat-8 OLI: <span><math><msup><mi>r</mi><mn>2</mn></msup></math></span>=0.78 and <em>NRMSE</em> = 19.96 %, Sentinel-3B OLCI: <span><math><msup><mi>r</mi><mn>2</mn></msup></math></span>=0.78 and <em>NRMSE</em> = 19.96 %). Overall, these findings highlight the strong potential of SDGSAT-1 MII for monitoring coastal turbid waters, while also noting certain spectral limitations, especially for the shorter (401 nm) and near-infra","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"321 ","pages":"Article 114683"},"PeriodicalIF":11.1,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143509754","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}
New advancements in satellite technology enable more accurate observation of woody population dynamics, providing greater insights into the underlying processes that influence their change. In this study, we evaluate the use of PlanetScope NDVI time series to track the phenology of individual trees in the Sahel, where ground-based environmental surveys are scarce. Five-year NDVI time series were produced for 398 trees with known species recorded in Mali, Senegal, and Niger. Clouds and high aerosol contamination were filtered using MODIS products and focused on the dry season to minimize the influence of background NDVI directly (through crown influence) or indirectly (through adjacency effects). Each NDVI time series profile was fitted with a spline model to obtain the minimum NDVI day of year during the dry season. PlanetScope NDVI time series accurately captured the photosynthetic phenology of individual tree crowns in the Sahel, with discernable differences between individuals and species. When species were grouped based on four phenology types, deciduous and inverse deciduous species exhibited a relatively consistent phenological pattern across all sites. The phenology of semi-evergreen species and evergreen species, which include species with few leaves, was more heterogeneous. Intra-species variation was relatively modest between sites, and most species maintained a similar NDVI profile, with shifts in leaf phenology events correlating with the timing of the wet season in each site. Overlap between the different phenology groups indicates that transitions between phenology types and species are not clear-cut, and even individuals of the same species can demonstrate plasticity. Furthermore, NDVI profiles were extracted for 500 randomly selected tree samples within eight 10 km2 clip boxes distributed along the West African rainfall gradient from 9.9° to 16.6° latitude at −1.6° longitude. This analysis showed a strong relationship between the phenology of woody plants and the timing and distribution of rainfall at each latitude. Green-up of woody vegetation before herbaceous vegetation was marked in the more southern Sahelo-Sudanian latitudes. Additionally, despite the prolonged dry season in the more northern semi-arid latitudes, trees retained their greenness remarkably late into the dry season. Increased air temperature and dryness as a result of climate change could impact tree function in this region and needs individual-based monitoring.
{"title":"Using PlanetScope NDVI time series to detect the phenology of individual trees in the Sahel","authors":"Yasmin Fitts , Compton Tucker , Pierre Hiernaux , Yves Auda , Laurent Kergoat","doi":"10.1016/j.rse.2025.114650","DOIUrl":"10.1016/j.rse.2025.114650","url":null,"abstract":"<div><div>New advancements in satellite technology enable more accurate observation of woody population dynamics, providing greater insights into the underlying processes that influence their change. In this study, we evaluate the use of PlanetScope NDVI time series to track the phenology of individual trees in the Sahel, where ground-based environmental surveys are scarce. Five-year NDVI time series were produced for 398 trees with known species recorded in Mali, Senegal, and Niger. Clouds and high aerosol contamination were filtered using MODIS products and focused on the dry season to minimize the influence of background NDVI directly (through crown influence) or indirectly (through adjacency effects). Each NDVI time series profile was fitted with a spline model to obtain the minimum NDVI day of year during the dry season. PlanetScope NDVI time series accurately captured the photosynthetic phenology of individual tree crowns in the Sahel, with discernable differences between individuals and species. When species were grouped based on four phenology types, deciduous and inverse deciduous species exhibited a relatively consistent phenological pattern across all sites. The phenology of semi-evergreen species and evergreen species, which include species with few leaves, was more heterogeneous. Intra-species variation was relatively modest between sites, and most species maintained a similar NDVI profile, with shifts in leaf phenology events correlating with the timing of the wet season in each site. Overlap between the different phenology groups indicates that transitions between phenology types and species are not clear-cut, and even individuals of the same species can demonstrate plasticity. Furthermore, NDVI profiles were extracted for 500 randomly selected tree samples within eight 10 km<sup>2</sup> clip boxes distributed along the West African rainfall gradient from 9.9° to 16.6° latitude at −1.6° longitude. This analysis showed a strong relationship between the phenology of woody plants and the timing and distribution of rainfall at each latitude. Green-up of woody vegetation before herbaceous vegetation was marked in the more southern Sahelo-Sudanian latitudes. Additionally, despite the prolonged dry season in the more northern semi-arid latitudes, trees retained their greenness remarkably late into the dry season. Increased air temperature and dryness as a result of climate change could impact tree function in this region and needs individual-based monitoring.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"321 ","pages":"Article 114650"},"PeriodicalIF":11.1,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143509752","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 : 2025-02-26DOI: 10.1016/j.rse.2025.114679
L. Yan , D.P. Roy
The Landsat 1–5 Multispectral Scanner (MSS) acquired images in 1972–1992, but their usage is limited, particularly by low geometric accuracy. In the latest USGS Landsat Collection 2 processing, <1 % MSS archive could be geometrically processed to the highest-level Tier 1 category. We present a novel methodology to characterize and correct MSS geometric distortions using Landsat 8 and 9 OLI L1TP images as references, and using a new many-to-many matching strategy applied to MSS and OLI time series to provide large quantities of tie-points needed for effective MSS image geometric characterization and correction. The method is demonstrated at four U.S. sites (Landsat path/rows), including a site over Las Vegas that had significant surface change, and considering 182 MSS and 38 OLI Collection 2 images. Significant and spatially-variable MSS geometric distortions were found, with mean RMSE distortions of 43.2, 25.2, 24.0, 22.2, and 21.0 m for Landsat 1, 2, 3, 4, and 5 MSS L1TP images, respectively, and 327.0 m for Landsat 1 MSS L1GS images. After geometric correction, these mean RMSE values were reduced to 12.0, 12.0, 13.8, 12.0 and 11.4 m for the Landsat 1–5 MSS L1TP images, and 15.0 m for the Landsat 1 MSS L1GS images. The geometrically corrected MSS L1TP images acquired over each site were mutually well registered with site mean RMSE values from 9.6 to 20.4 m. The results indicate the methodology can be applied to the MSS archive in support of Landsat time series applications extending back to the 1970s, and to include a greater proportion of the MSS archive in the USGS Landsat analysis ready data (ARD) data suite that requires Tier 1 processing.
{"title":"Using Landsat 8 and 9 operational land imager (OLI) data to characterize geometric distortion and improve geometric correction of Landsat Multispectral Scanner (MSS) imagery","authors":"L. Yan , D.P. Roy","doi":"10.1016/j.rse.2025.114679","DOIUrl":"10.1016/j.rse.2025.114679","url":null,"abstract":"<div><div>The Landsat 1–5 Multispectral Scanner (MSS) acquired images in 1972–1992, but their usage is limited, particularly by low geometric accuracy. In the latest USGS Landsat Collection 2 processing, <1 % MSS archive could be geometrically processed to the highest-level Tier 1 category. We present a novel methodology to characterize and correct MSS geometric distortions using Landsat 8 and 9 OLI L1TP images as references, and using a new many-to-many matching strategy applied to MSS and OLI time series to provide large quantities of tie-points needed for effective MSS image geometric characterization and correction. The method is demonstrated at four U.S. sites (Landsat path/rows), including a site over Las Vegas that had significant surface change, and considering 182 MSS and 38 OLI Collection 2 images. Significant and spatially-variable MSS geometric distortions were found, with mean RMSE distortions of 43.2, 25.2, 24.0, 22.2, and 21.0 m for Landsat 1, 2, 3, 4, and 5 MSS L1TP images, respectively, and 327.0 m for Landsat 1 MSS L1GS images. After geometric correction, these mean RMSE values were reduced to 12.0, 12.0, 13.8, 12.0 and 11.4 m for the Landsat 1–5 MSS L1TP images, and 15.0 m for the Landsat 1 MSS L1GS images. The geometrically corrected MSS L1TP images acquired over each site were mutually well registered with site mean RMSE values from 9.6 to 20.4 m. The results indicate the methodology can be applied to the MSS archive in support of Landsat time series applications extending back to the 1970s, and to include a greater proportion of the MSS archive in the USGS Landsat analysis ready data (ARD) data suite that requires Tier 1 processing.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"321 ","pages":"Article 114679"},"PeriodicalIF":11.1,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143487796","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 : 2025-02-26DOI: 10.1016/j.rse.2025.114667
Juan Li , Atsushi Matsuoka , Emmanuel Devred , Stanford B. Hooker , Xiaoping Pang , Marcel Babin
Standard ocean colour algorithms exploiting only shorter visible wavelengths (less than 560 nm) perform poorly in the Arctic Ocean (AO) due to the interference from colored detrital material (CDM). The incorporation of longer wavelengths, which are less susceptible to interference from CDM, could prove beneficial in retrieving water properties, particularly in Arctic waters with high CDM content. Similarly, algorithms that exploit only the red region of the spectrum, such as fluorescence-based approaches, are also unsuitable for these waters. This is due to the difficulty in accurately describing the background elastic scattering signal. In this study, we propose an algorithm that accounts for elastic scattering and fluorescence of phytoplankton in the full visible spectral domain by coupling a tuned version of the Garver-Siegel-Maritorena (GSM) algorithm (GSMA) for the AO with an optimized fluorescence emission model. Our novel algorithm, FGSM, demonstrate comparable overall performance to an empirical algorithm derived for chlorophyll concentration (Chl) estimates in the AO (AO.emp), with a mean absolute difference (MAD) of 1.83. In addition, FGSM outperforms both the GSMA and the fluorescence line height (FLH) algorithms, with an improvement in the MAD of Chl estimates up to 41 %. Assessments conducted using both in situ datasets and satellite data at the Lena River Delta, a region characterized by high productivity and the presence of coastal CDM, revealed that for eutrophic waters where Chl is generally high, FGSM significantly mitigate the underestimation of Chl by AO.emp and GSMA, and exhibit enhanced robustness to produce more retrievals than the other semi-analytical algorithms. FGSM also demonstrates superior performance compared to the other algorithms assessed in this study for waters with high suspended particulate matter (SPM). Further validations for Arctic waters, particularly turbid coastal waters, are still expected in the future.
{"title":"A novel GSM and fluorescence coupled full-spectral chlorophyll a algorithm for waters with high CDM content","authors":"Juan Li , Atsushi Matsuoka , Emmanuel Devred , Stanford B. Hooker , Xiaoping Pang , Marcel Babin","doi":"10.1016/j.rse.2025.114667","DOIUrl":"10.1016/j.rse.2025.114667","url":null,"abstract":"<div><div>Standard ocean colour algorithms exploiting only shorter visible wavelengths (less than 560 nm) perform poorly in the Arctic Ocean (AO) due to the interference from colored detrital material (CDM). The incorporation of longer wavelengths, which are less susceptible to interference from CDM, could prove beneficial in retrieving water properties, particularly in Arctic waters with high CDM content. Similarly, algorithms that exploit only the red region of the spectrum, such as fluorescence-based approaches, are also unsuitable for these waters. This is due to the difficulty in accurately describing the background elastic scattering signal. In this study, we propose an algorithm that accounts for elastic scattering and fluorescence of phytoplankton in the full visible spectral domain by coupling a tuned version of the Garver-Siegel-Maritorena (GSM) algorithm (GSMA) for the AO with an optimized fluorescence emission model. Our novel algorithm, FGSM, demonstrate comparable overall performance to an empirical algorithm derived for chlorophyll <span><math><mi>a</mi></math></span> concentration (Chl) estimates in the AO (AO.emp), with a mean absolute difference (MAD) of 1.83. In addition, FGSM outperforms both the GSMA and the fluorescence line height (FLH) algorithms, with an improvement in the MAD of Chl estimates up to 41 %. Assessments conducted using both in situ datasets and satellite data at the Lena River Delta, a region characterized by high productivity and the presence of coastal CDM, revealed that for eutrophic waters where Chl is generally high, FGSM significantly mitigate the underestimation of Chl by AO.emp and GSMA, and exhibit enhanced robustness to produce more retrievals than the other semi-analytical algorithms. FGSM also demonstrates superior performance compared to the other algorithms assessed in this study for waters with high suspended particulate matter (SPM). Further validations for Arctic waters, particularly turbid coastal waters, are still expected in the future.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"321 ","pages":"Article 114667"},"PeriodicalIF":11.1,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143487874","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 : 2025-02-20DOI: 10.1016/j.rse.2025.114606
Davide D'Alimonte , Tamito Kajiyama , Jaime Pitarch , Vittorio Ernesto Brando , Marco Talone , Constant Mazeran , Michael Twardowski , Srinivas Kolluru , Alberto Tonizzo , Ewa Kwiatkowska , David Dessailly , Juan Ignacio Gossn
Several methods were developed in Ocean Colour remote sensing over the last 25 years to model the anisotropy of the upwelling radiant field with respect to observation and solar-illumination geometries, also denoted as bidirectional reflectance distribution function (BRDF). These methods are necessary to produce normalized, or “BRDF-corrected,” marine reflectance representative of the seawater's inherent optical properties (IOPs) independently of the measurement conditions. Each scheme relies on specific modeling assumptions and implementation solutions, which can lead to different results depending on the actual combination of the seawater IOPs with the illumination and viewing geometry. The first aim of this study is to analyze the principles and methods of the reference BRDF schemes presented by Morel et al. (denoted as M02), Park and Ruddick (P05), Lee et al. (L11), He et al. (H17), and Twardowski and Tonizzo (T18). Acknowledging the direct applicability of M02, P05, and L11, their performance has been verified under a variety of conditions, including in situ measurements, matchup observations, and space-borne images. Comparisons between non-corrected and normalized data clearly confirm the need to account for the BRDF effect. In particular, the analysis of the results indicates 1) a substantial equivalence of M02, P05, and L11 in clear waters and 2) the tendency to obtain better results with M02 and L11 as the optical complexity increases. Although M02 was conceived for Case 1 waters, the underlying Chlorophyll-a overestimation tendency in some optically complex conditions is likely the reason for its extended applicability. Since L11 is based on a more comprehensive and flexible framework for all water types, the design of this method is suggested for revisions and BRDF correction improvements.
{"title":"Comparison of correction methods for bidirectional effects in ocean colour remote sensing","authors":"Davide D'Alimonte , Tamito Kajiyama , Jaime Pitarch , Vittorio Ernesto Brando , Marco Talone , Constant Mazeran , Michael Twardowski , Srinivas Kolluru , Alberto Tonizzo , Ewa Kwiatkowska , David Dessailly , Juan Ignacio Gossn","doi":"10.1016/j.rse.2025.114606","DOIUrl":"10.1016/j.rse.2025.114606","url":null,"abstract":"<div><div>Several methods were developed in Ocean Colour remote sensing over the last 25 years to model the anisotropy of the upwelling radiant field with respect to observation and solar-illumination geometries, also denoted as bidirectional reflectance distribution function (BRDF). These methods are necessary to produce normalized, or “BRDF-corrected,” marine reflectance representative of the seawater's inherent optical properties (IOPs) independently of the measurement conditions. Each scheme relies on specific modeling assumptions and implementation solutions, which can lead to different results depending on the actual combination of the seawater IOPs with the illumination and viewing geometry. The first aim of this study is to analyze the principles and methods of the reference BRDF schemes presented by Morel et al. (denoted as M02), Park and Ruddick (P05), Lee et al. (L11), He et al. (H17), and Twardowski and Tonizzo (T18). Acknowledging the direct applicability of M02, P05, and L11, their performance has been verified under a variety of conditions, including in situ measurements, matchup observations, and space-borne images. Comparisons between non-corrected and normalized data clearly confirm the need to account for the BRDF effect. In particular, the analysis of the results indicates 1) a substantial equivalence of M02, P05, and L11 in clear waters and 2) the tendency to obtain better results with M02 and L11 as the optical complexity increases. Although M02 was conceived for Case 1 waters, the underlying Chlorophyll-<em>a</em> overestimation tendency in some optically complex conditions is likely the reason for its extended applicability. Since L11 is based on a more comprehensive and flexible framework for all water types, the design of this method is suggested for revisions and BRDF correction improvements.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"321 ","pages":"Article 114606"},"PeriodicalIF":11.1,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143444813","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}
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