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Detecting early winter open-water zones on Alaska rivers using dual-polarized C-band Sentinel-1 synthetic aperture radar (SAR) Remote Sens. Environ. (IF 13.5) Pub Date : 2024-03-13 Melanie Engram, Franz J. Meyer, Dana R.N. Brown, Sarah Clement, Allen C. Bondurant, Katie V. Spellman, Laura E. Oxtoby, Christopher D. Arp
Northern high-latitude river ice provides critical natural infrastructure for winter travel, commerce, hunting, fishing, and recreation in rural areas with little or no road access. Open water zones (OWZs) in river ice are dangerous for such travel and are most common during early winter. Changes in the occurrence and duration of OWZs may also indicate more widespread shifts in ice regimes across Alaska
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Enhanced observations from an optimized soil-canopy-photosynthesis and energy flux model revealed evapotranspiration-shading cooling dynamics of urban vegetation during extreme heat Remote Sens. Environ. (IF 13.5) Pub Date : 2024-03-11 Zhaowu Yu, Jiaqi Chen, Jike Chen, Wenfeng Zhan, Chenghao Wang, Wenjuan Ma, Xihan Yao, Siqi Zhou, Kai Zhu, Ranhao Sun
Previousstudies on the cooling of urban vegetation mainly focused on its transpiration or shading effect separately, neglecting to explore the combined evapotranspiration-shading cooling. Further, accurate quantification of evapotranspiration-shading cooling remains challenging due to heterogeneity of urban landscapes, which limits understanding of its high-resolution spatiotemporal patterns. Here
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Immediate and lagged vegetation responses to dry spells revealed by continuous solar-induced chlorophyll fluorescence observations in a tall-grass prairie Remote Sens. Environ. (IF 13.5) Pub Date : 2024-03-11 Yao Zhang, Mengyang Cai, Xiangming Xiao, Xi Yang, Mirco Migliavacca, Jeffrey Basara, Sha Zhou, Yuanzhizi Deng
Monitoring plants' responses to water deficit using remote sensing still faces large uncertainty, mostly due to the inaccurate characterization of plants' physiological responses. Solar induced chlorophyll fluorescence (SIF) contains information on plants' physiological processes which regulates the energy partitioning after solar radiation is absorbed by chlorophyll, providing new opportunities to
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Augmenting daily MODIS LST with AIRS surface temperature retrievals to estimate ground temperature and permafrost extent in High Mountain Asia Remote Sens. Environ. (IF 13.5) Pub Date : 2024-03-11 Kyung Y. Kim, Ryan Haagenson, Prakrut Kansara, Harihar Rajaram, Venkataraman Lakshmi
Permafrost in High Mountain Asia (HMA) is becoming increasingly vulnerable to thaw due to climate change. However, the lack of either ground surface or borehole temperature data beyond the Tibetan Plateau prevents comprehensive assessments of its impact on the regional hydrologic cycle and local cascading hazards. Although past studies have generated estimates of permafrost extent in Central Asia,
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Inferring global terrestrial carbon fluxes from the synergy of Sentinel 3 & 5P with Gaussian process hybrid models Remote Sens. Environ. (IF 13.5) Pub Date : 2024-03-11 Pablo Reyes-Muñoz, Dávid D.Kovács, Katja Berger, Luca Pipia, Santiago Belda, Juan Pablo Rivera-Caicedo, Jochem Verrelst
The ongoing monitoring of terrestrial carbon fluxes (TCF) goes hand in hand with progress in technical capacities, such as the next-generation Earth observation missions of the Copernicus initiative and advanced machine learning algorithms. Proceeding along this line, we present a physically-based data-driven workflow for quantifying gross primary productivity (GPP) and net primary productivity (NPP)
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Analyzing surface deformation throughout China's territory using multi-temporal InSAR processing of Sentinel-1 radar data Remote Sens. Environ. (IF 13.5) Pub Date : 2024-03-10 Guo Zhang, Zixing Xu, Zhenwei Chen, Shunyao Wang, Yutao Liu, Xuhui Gong
The damage caused by surface deformation is substantial and far-reaching. Although multi-temporal interferometric synthetic aperture radar (InSAR) technology is commonly used to monitor surface deformation, it remains challenging to rapidly extract surface deformation on a national scale, especially in China, which has an area of approximately 9.6 million km. We designed a set of robust parallel computing
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Nighttime light in China's coastal zone: The type classification approach using SDGSAT-1 Glimmer Imager Remote Sens. Environ. (IF 13.5) Pub Date : 2024-03-08 Mingming Jia, Haihang Zeng, Zuoqi Chen, Zongming Wang, Chunying Ren, Dehua Mao, Chuanpeng Zhao, Rong Zhang, Yeqiao Wang
Nighttime Light (NTL) is highly concentrated in China's coastal zone, leading to negative health impacts on both humans and wildlife. Particularly, in recent years, the widespread adoption of broad-spectrum Light-Emitting Diode (LED) light, a low-carbon technology providing substantial increases in luminosity, has led to certain ecological consequences. Thus, information regarding spatial distribution
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Uncovering the rapid expansion of photovoltaic power plants in China from 2010 to 2022 using satellite data and deep learning Remote Sens. Environ. (IF 13.5) Pub Date : 2024-03-08 Yuehong Chen, Jiayue Zhou, Yong Ge, Jinwei Dong
China's rapid deployment of solar photovoltaic (PV) power plants has positioned it as the global leader in cumulative installed capacity. The expansion patterns of PV power plants in China play a crucial role in promoting PV diffusion in markets, shaping policies, and analyzing environmental and social impacts. However, the current geospatial datasets of PV power plants available for China cannot fully
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Mapping vegetation height and identifying the northern forest limit across Canada using ICESat-2, Landsat time series and topographic data Remote Sens. Environ. (IF 13.5) Pub Date : 2024-03-07 H. Travers-Smith, N.C. Coops, C. Mulverhill, M.A. Wulder, D. Ignace, T.C. Lantz
The northern forest-tundra ecotone is one of the fastest warming regions of the globe. Models of vegetation change generally predict a northward advance of boreal forests and corresponding retreat of the tundra. Previous satellite remote sensing analyses in this region have focused on mapping vegetation greenness and tree cover derived from optical multi-spectral sensors. Changes in vegetation structure
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Changes in glacier surface temperature across the Third Pole from 2000 to 2021 Remote Sens. Environ. (IF 13.5) Pub Date : 2024-03-06 Shaoting Ren, Tandong Yao, Wei Yang, Evan S. Miles, Huabiao Zhao, Meilin Zhu, Shenghai Li
Glacier surface temperature is not only an important indicator of climate change, but is also directly related to glacier physical processes and mass balance. Glaciers over the Third Pole have shown heterogeneous but accelerated mass loss over the past two decades. However, few studies have focused on changes of glacier surface temperature in this region. In this study, we investigate this change from
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Evaluation of light atmospheric plume inversion methods using synthetic XCO2 satellite images to compute Paris CO2 emissions Remote Sens. Environ. (IF 13.5) Pub Date : 2024-03-06 Alexandre Danjou, Grégoire Broquet, Jinghui Lian, François-Marie Bréon, Thomas Lauvaux
There is a growing interest in estimating urban CO emission from space-borne imagery of XCO. Here, we evaluate computationally-light methods (mass-balance approaches and inversions of Gaussian plume models) for estimating urban emissions with Paris, France, as an example. This evaluation is based on the application of those methods to synthetic high-resolution images of the XCO field in the Paris area
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Ocean-wave suppression for synthetic aperture radar images by depth counteraction method Remote Sens. Environ. (IF 13.5) Pub Date : 2024-03-05 Xiaopeng Chao, Qingsong Wang, Xiaoqing Wang, Jian Chen, Yuting Zhu
Surface waves are the most widely distributed texture in synthetic aperture radar (SAR) images acquired over the oceans, and long ocean waves are generally imaged in SAR images with a spatial resolution of 5 m as wave-looking structures. If these ocean-wave textures cause interference when detecting or extracting small-scale ocean features on the ocean surface, it is necessary to suppress them. However
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Soil moisture profile estimation by combining P-band SAR polarimetry with hydrological and multi-layer scattering models Remote Sens. Environ. (IF 13.5) Pub Date : 2024-03-05 Anke Fluhrer, Thomas Jagdhuber, Carsten Montzka, Maike Schumacher, Hamed Alemohammad, Alireza Tabatabaeenejad, Harald Kunstmann, Dara Entekhabi
An approach for estimating vertically continuous soil moisture profiles under varying vegetation covers by combining remote sensing with soil (hydrological) modeling is proposed. The approach uses decomposed soil scattering components, after the removal of the vegetation scattering components from fully polarimetric P-band SAR observations. By comparing these with hydrological simulations, soil moisture
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Spatiotemporal heterogeneity in global urban surface warming Remote Sens. Environ. (IF 13.5) Pub Date : 2024-03-01 Shuang Ge, Wenfeng Zhan, Shasha Wang, Huilin Du, Zihan Liu, Chenguang Wang, Chunli Wang, Sida Jiang, Pan Dong
The rapid urban warming in recent decades has posed significant risks to the health and well-being of urban residents. Previous studies have predominantly examined urban surface warming from an annual-mean and whole-city perspective. Spatiotemporal heterogeneity in surface warming trends within cities and throughout different periods within a yearly cycle remains largely unclear across global cities
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Sea ice detection using concurrent multispectral and synthetic aperture radar imagery Remote Sens. Environ. (IF 13.5) Pub Date : 2024-03-01 Martin S.J. Rogers, Maria Fox, Andrew Fleming, Louisa van Zeeland, Jeremy Wilkinson, J. Scott Hosking
Synthetic Aperture Radar (SAR) imagery is the primary data type used for sea ice mapping due to its spatiotemporal coverage and the ability to detect sea ice independent of cloud and lighting conditions. Automatic sea ice detection using SAR imagery remains problematic due to the presence of ambiguous signal and noise within the image. Conversely, ice and water are easily distinguishable using multispectral
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A river runs through it: Robust automated mapping of riparian woodlands and land surface phenology across dryland regions Remote Sens. Environ. (IF 13.5) Pub Date : 2024-03-01 Conor A. McMahon, Dar A. Roberts, John C. Stella, Anna T. Trugman, Michael B. Singer, Kelly K. Caylor
Riparian woodlands in drylands are critically important to human society, global biodiversity, and regional water and energy budgets. These sensitive ecosystems have experienced substantial degradation over the last several decades from climatic change and direct human activity. Nevertheless, quantifying long-term change in dryland riparian woodlands remains a major challenge, and much uncertainty
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Automated retrieval of internal wave phase speed and direction from pairs of SAR images with different look directions Remote Sens. Environ. (IF 13.5) Pub Date : 2024-03-01 Samantha Furtney, Roland Romeiser, Hans C. Graber
Synthetic aperture radar (SAR) is the premier instrument in satellite remote sensing for the detection of oceanic internal waves due to its sensitivity to changes in small-scale ocean surface roughness and relatively large spatial coverage. The satellite constellation COSMO-SkyMed offers the unique capability to acquire pairs of images of the same scene within 24 min, which is ideal for making internal
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Evidence of a bias-variance trade off when correcting for bias in Sentinel 2 forest LAI retrievals using radiative transfer models Remote Sens. Environ. (IF 13.5) Pub Date : 2024-03-01 Richard Fernandes, Najib Djamai, Kate Harvey, Gang Hong, Camryn MacDougall, Hemit Shah, Lixin Sun
Forest canopies exhibit spatial heterogeneity that impacts the relationship between essential climate variables such as leaf area index (LAI) or the fraction of absorbed photosynthetically active radiation (fAPAR) and bi-directional surface reflectance, and subsequently the estimation of these variables from satellite measurements. The Simplified Level 2 Prototype Processor (SL2P) allows global LAI
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Solar-induced chlorophyll fluorescence sheds light on global evapotranspiration Remote Sens. Environ. (IF 13.5) Pub Date : 2024-03-01 Quan Zhang, Xuanqi Liu, Kai Zhou, Yang Zhou, Pierre Gentine, Ming Pan, Gabriel G. Katul
The significance of large-scale evapotranspiration (ET) to climate science, water resources management, flood routing, irreversible desertification, and crop yield is not in dispute. Current large-scale ET models combine empirical formulations with a suite of remotely sensed data products that include meteorological variables, vegetation indices and/or soil moisture. In recent years, solar-induced
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Optimization of InSAR based coseismic slip modeling for moderate earthquakes accounting for fore–aftershock sequence Remote Sens. Environ. (IF 13.5) Pub Date : 2024-03-01 Lejun Lu, Yu Zhou
Determination of coseismic slip distribution for moderate (moment magnitude, 6.5) earthquakes is challenging as the commonly-used interferometric synthetic aperture radar (InSAR) technique is unable to separate mainshock and fore–aftershocks due to its limited temporal resolution. In this study, we propose a new method of optimizing coseismic slip modeling by removing fore–aftershock contributions
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Efficacy of the SDGSAT-1 glimmer imagery in measuring sustainable development goal indicators 7.1.1, 11.5.2, and target 7.3 Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-29 Shaoyang Liu, Congxiao Wang, Zuoqi Chen, Wei Li, Lingxian Zhang, Bin Wu, Yan Huang, Yangguang Li, Jingwen Ni, Jianping Wu, Bailang Yu
The Sustainable Development Goals Satellite 1 (SDGSAT-1), equipped with the Glimmer Imager (GLI), provides high-resolution nighttime light (NTL) data across multiple spectral bands, potentially facilitating the monitoring of sustainable development goals (SDGs). This study developed a denoising algorithm for the multispectral SDGSAT-1 GLI and demonstrated that its data capacity allows for the measurement
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A novel surface energy balance-based approach to land surface temperature downscaling Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-29 Mohammad Karimi Firozjaei, Naeim Mijani, Majid Kiavarz, Si-Bo Duan, Peter M. Atkinson, Seyed Kazem Alavipanah
Spatial downscaling satellite sensor-derived land surface temperature (LST) is of great importance for various environmental applications. However, the energy balance at the land surface is complex, especially in urban environments. As a result, the complexity of land surface thermal processes and the resulting LST cannot be accurately modeled using common downscaling methods. Here, we propose a new
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GABLE: A first fine-grained 3D building model of China on a national scale from very high resolution satellite imagery Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-27 Xian Sun, Xingliang Huang, Yongqiang Mao, Taowei Sheng, Jihao Li, Zhirui Wang, Xue Lu, Xiaoliang Ma, Deke Tang, Kaiqiang Chen
Three-dimensional (3D) building models provide horizontal and vertical information of urban development patterns, which are significant to urbanization analysis, solar energy planning, carbon reduction and sustainability. Despite that many popular products on a global or national scale are proposed, these products usually focus on building extraction and height estimation at fairly coarse resolutions
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Automated forest inventory: Analysis of high-density airborne LiDAR point clouds with 3D deep learning Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-27 Binbin Xiang, Maciej Wielgosz, Theodora Kontogianni, Torben Peters, Stefano Puliti, Rasmus Astrup, Konrad Schindler
Detailed forest inventories are critical for sustainable and flexible management of forest resources, to conserve various ecosystem services. Modern airborne laser scanners deliver high-density point clouds with great potential for fine-scale forest inventory and analysis, but automatically partitioning those point clouds into meaningful entities like individual trees or tree components remains a challenge
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Imaging spectroscopy investigations in wet carbon ecosystems: A review of the literature from 1995 to 2022 and future directions Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-27 Thomas C. Ingalls, Jiwei Li, Yvonne Sawall, Roberta E. Martin, David R. Thompson, Gregory P. Asner
Earth is experiencing unprecedented climate change driven by anthropogenic activities. The Paris Climate Agreement is the most recent international agreement pushing nations to curtail greenhouse gas emissions and balance carbon sources and sinks. To help meet the standards set forth in the Paris Climate Agreement, countries can incorporate ecosystems known to sequester and store large amounts of carbon
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A study of annual tree-wise LiDAR intensity patterns of boreal species observed using a hyper-temporal laser scanning time series Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-27 Anna Shcherbacheva, Mariana B. Campos, Yunsheng Wang, Xinlian Liang, Antero Kukko, Juha Hyyppä, Samuli Junttila, Anna Lintunen, Ilkka Korpela, Eetu Puttonen
This study introduces the annual tree-wise intensity patterns of three boreal tree species, silver birch ( Roth.), Scots pine ( L., and Norway spruce ( H. Karst.), observed from a long-term hyper-temporal point cloud dataset collected with a permanent laser scanning (LiDAR) station. An annual LiDAR intensity pattern refers to the trend of variations of tree-wise calibrated LiDAR intensity values over
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Comparison of wave spectrum assimilation and significant wave height assimilation based on Chinese-French oceanography satellite observations Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-26 Chunxiao Wang, Songlin Li, Huaming Yu, Kejian Wu, Shuyan Lang, Ying Xu
Assimilating observation data into wave models can significantly improve the numerical simulation accuracy of ocean waves. Traditionally, assimilation efforts have predominantly focused on significant wave height (SWH). However, the launch of the China-France Oceanography SATellite (CFOSAT)has facilitated the acquisition to obtain global-scale wave spectrum data, introducing a transformative dimension
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Multi-spectral surface emissivity as an indicator of soil water content and soil water content changes in arid soils Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-26 D. Kool, N. Agam
Surface emissivity () is used to characterize surfaces and to determine surface temperature from thermal radiation data. While in many applications it is treated as a constant, it is known to change with surface water content. Several ASTER/SEVERI based studies have speculated that diurnal changes in over deserts are linked to diurnal soil water content cycles resulting from water vapor adsorption
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Estimating volume of large slow-moving deep-seated landslides in northern Canada from DInSAR-derived 2D and constrained 3D deformation rates Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-26 Sergey V. Samsonov, Andrée Blais-Stevens
Large slow-moving deep-seated landslides are observed in two different regions of northern Canada with advanced Differential Synthetic Aperture Radar (DInSAR). Two-dimensional vertical and horizontal east-west deformation rates and time series are computed from ascending and descending Sentinel-1 imagery acquired during 2017–2022. The landslides' east-west deformation rate is significantly larger than
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Leveraging past information and machine learning to accelerate land disturbance monitoring Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-26 Su Ye, Zhe Zhu, Ji Won Suh
Near real-time (NRT) monitoring of land disturbances holds great importance for delivering emergency aid, mitigating negative social and ecological impacts, and distributing resources for disaster recovery. Many past NRT techniques were built upon examining the overall change magnitude of a spectral anomaly with a predefined threshold, namely the unsupervised approach. However, their lack of fully
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Spectra-phenology integration for high-resolution, accurate, and scalable mapping of foliar functional traits using time-series Sentinel-2 data Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-26 Shuwen Liu, Zhihui Wang, Ziyu Lin, Yingyi Zhao, Zhengbing Yan, Kun Zhang, Marco Visser, Philip A. Townsend, Jin Wu
Foliar functional traits are essential for understanding plant adaptation strategies and ecosystem function. Due to limited observational data, there is a growing interest in upscaling these traits from field sites to regional and global levels. However, limitations persist: (1) global/national scale upscaling that relies on plant functional type (PFT) maps, environmental variables or coarse resolution
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Seasonal dynamics of fallow and cropping lands in the broadacre cropping region of Australia Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-26 Zunyi Xie, Yan Zhao, Ruizhu Jiang, Miao Zhang, Graeme Hammer, Scott Chapman, Jason Brider, Andries B. Potgieter
Fallowing is an important strategy for enhancing soil health, water harvesting and crop yields, thus improving sustainability and reducing production risks in dryland farming systems in Australia. However, accurate data regarding the location, frequency, extent, and duration of fallow land is not readily available at high spatio-temporal resolutions before and during a cropping season. As a result
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National tree species mapping using Sentinel-1/2 time series and German National Forest Inventory data Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-24 Lukas Blickensdörfer, Katja Oehmichen, Dirk Pflugmacher, Birgit Kleinschmit, Patrick Hostert
Spatially explicit and detailed information on tree species composition is critical for forest management, nature conservation and the assessment of forest ecosystem services. In many countries, forest attributes are monitored regularly through sample-based forest inventories. In combination with satellite imagery, data from such forest inventories have a great potential for developing large-area tree
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A self-adjusting method to generate daily consistent nighttime light data for the detection of short-term rapid human activities Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-24 Yang Hu, Xudong Zhou, Dai Yamazaki, Jin Chen
Nighttime light (NTL) has become an emerging indicator of the magnitude and changes in human settlement and activities. A recently released Lunar-BRDF-corrected NTL product, Black Marble VNP46A2, with enhanced temporal (daily) and spatial (15 arc-second) resolutions, has the potential to monitor human reactions to short-term events with rapid light intensity variations. However, the VNP46A2 NTL exhibits
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Mapping icebergs in sea ice: An analysis of seasonal SAR backscatter at C- and L-band Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-24 Laust Færch, Wolfgang Dierking, Nick Hughes, Anthony P. Doulgeris
Icebergs in the Arctic can pose a threat to maritime traffic and offshore installations and influence the properties of the upper ocean layer. While icebergs in open water are regularly monitored using C-band SAR satellites, less attention has been paid to icebergs in regions with a high areal fraction of sea ice, where detection using traditional methods is more difficult. In this study, we compare
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Spatial-temporal patterns of land surface evapotranspiration from global products Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-24 Ronglin Tang, Zhong Peng, Meng Liu, Zhao-Liang Li, Yazhen Jiang, Yongxin Hu, Lingxiao Huang, Yizhe Wang, Junrui Wang, Li Jia, Chaolei Zheng, Yongqiang Zhang, Ke Zhang, Yunjun Yao, Xuelong Chen, Yujiu Xiong, Zhenzhong Zeng, Joshua B. Fisher
Knowledge of spatio-temporal patterns of global land surface evapotranspiration (ET) is essential for understanding the exchanges of energy, water and carbon between the earth surface and atmosphere and responses to human activities, climate changes, and extreme weather events. This paper comprehensively reviewed accuracies and spatio-temporal patterns of 25 state-of-the-art global datasets of land
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Research on automatic recognition of active landslides using InSAR deformation under digital morphology: A case study of the Baihetan reservoir, China Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-24 Yang Liu, Xin Yao, Zhenkui Gu, Renjiang Li, Zhenkai Zhou, Xinghong Liu, Shu Jiang, Chuangchuang Yao, Shangfei Wei
Optical remote sensing and field investigations cannot satisfy the accuracy and timeliness requirements of active landslide detection. Interferometric synthetic aperture radar (InSAR) technology has become the mainstream method for observing active landslides in recent years, due to its advantages of a large detection range and high sensitivity to surface deformation. However, quickly and accurately
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Retrieval of temperature profiles in tropical cyclone Nanmadol from resampled advanced technology microwave sounder observations Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-22 Wenyu Li, Fuzhong Weng
In the past, satellite microwave sounding data are often utilized for retrieving the thermal structure of tropical cyclones (TCs). However, the spatial resolutions and scan pattern of the instruments vary from one to another and can affect the retrievals of TC structures. In this study, Backus-Gilbert Inversion (BGI), ATOVS and AVHRR Pre-processing Package (AAPP) filter and N × N field-of-views (FOVs)
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Temporal decorrelation of C-band radar data over wheat in a semi-arid area using sub-daily tower-based observations Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-22 Nadia Ouaadi, Lionel Jarlan, Ludovic Villard, Adnane Chakir, Saïd Khabba, Pascal Fanise, Mohamed Kasbani, Zoubair Rafi, Valerie Le Dantec, Jamal Ezzahar, Pierre-Louis Frison
Recent studies have shown that radar temporal coherence over tropical and boreal forests undergoes a diurnal cycle as a result of a combined effect of the wind-induced motion of scatterers and of the change and displacement of water within the plant in response to the transpiration process. Within this context, the objective of this paper is to investigate, for the first time, the diurnal cycle of
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Pakistan's 2022 floods: Spatial distribution, causes and future trends from Sentinel-1 SAR observations Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-21 Fang Chen, Meimei Zhang, Hang Zhao, Weigui Guan, Aqiang Yang
Floods are a great threat to Pakistan with increasing concern. As the consequences of increased extreme weather related to climate change, Pakistan experiences severe floods almost every year. This study aims to explore and analysis the actual inundated situation, magnitude, the possible causes of the 2022 devastating floods, and future trends. We presented an enhanced nationwide flood mapping method
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Sensitivity of spectral communities to shifts in benthic composition in Hawaiʻi Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-21 Dominica E. Harrison, Gregory P. Asner
Coral reef benthic communities have been mapped in broad categories, such as total coral cover, using remote sensing, yet we lack important details on how changes in benthic community composition translate to spectral changes observed in airborne and spaceborne data. Here, we carry out a spectral sensitivity analysis to enhance our quantitative understanding of benthic community reflectance spectra
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Mapping high-resolution surface current by incorporating geostrophic equilibrium with surface quasigeostrophic theory using multi-source satellite observations Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-20 Zhiqiang Chen, Xidong Wang, Haijin Cao, Xiangzhou Song
In the past three decades, altimeter-based remote sensing has been a widely used system to estimate ocean surface currents. However, it remains a great challenge to effectively resolve scales below ∼100 km at high latitudes and ∼ 300 km at mid-latitudes. In this study, we propose a scheme that utilizes geostrophic equilibrium and surface quasigeostrophy theory (SQG) to improve surface current resolution
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Co-seismic and post-seismic deformation associated with the 2018 Lombok, Indonesia, earthquake sequence, inferred from InSAR and seismic data analysis Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-20 Siyuan Zhao, Simon McClusky, Phil R. Cummins, Meghan S. Miller
In 2018, four deadly (Mw 6.2–6.9) earthquakes struck the north coast of Lombok Island on 28 July, 5 August, and 19 August. The slip distributions of the three mainshocks are modeled in this study by inverting the co-seismic deformation imaged using an interferometric analysis of Sentinel-1 synthetic aperture radar measurements (InSAR), based on rectangular dislocations embedded in a multi-layered elastic
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First TanSat CO2 retrieval over land and ocean using both nadir and glint spectroscopy Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-19 Xinhua Hong, Chengxin Zhang, Yuan Tian, Yizhi Zhu, Yin Hao, Cheng Liu
The world is facing a serious warming crisis, highlighting the need for monitoring greenhouse gases such as carbon dioxide (CO). In 2016, China launched its first satellite mission for measuring atmospheric CO, i.e., TanSat. Previous TanSat retrievals of the column-averaged dry air mole fraction of CO (X) have a moderate precision of 1.47–2.45 ppm, with only limited spatial coverage over the land surface
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Developing unbiased estimation of atmospheric methane via machine learning and multiobjective programming based on TROPOMI and GOSAT data Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-17 Ke Li, Kaixu Bai, Penglong Jiao, He Chen, Huiqun He, Liuqing Shao, Yibing Sun, Zhe Zheng, Ruijie Li, Ni-Bin Chang
Accurate monitoring of atmospheric methane concentration (XCH) is relevant to improving carbon accounting and climate change attribution. Nevertheless, the commonly used full-physics carbon retrieval algorithm suffers from intensive computing burden and many algorithmic constraints. Aiming at providing a more efficient solution to advance global methane mapping, a novel XCH retrieval algorithm for
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Improving retrieval of leaf chlorophyll content from Sentinel-2 and Landsat-7/8 imagery by correcting for canopy structural effects Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-16 Liang Wan, Youngryel Ryu, Benjamin Dechant, Jeongho Lee, Zilong Zhong, Huaize Feng
Accurately estimating leaf chlorophyll content (Chl) at large spatial scales is crucial for monitoring agricultural production and plant photosynthesis. Sentinel-2 and Landsat-7/8 offer the potential to assess Chl with high spatial resolutions using various physically-based, empirical, and hybrid methods, but they still present challenges due to the confounding effects of canopy structure and soil
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Observing glacial isostatic adjustment by PSInSAR in southern Hudson Bay Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-16 Chong-You Wang, Yunung Nina Lin, Cheinway Hwang, C K Shum
Glacial isostatic adjustment (GIA) is the solid Earth's viscoelastic response to ice sheet deglaciations. Studies of GIA provide insights into crustal and mantle rheology, mass redistribution, relative paleo sea-level variations, and polar wander. In North America, GIA causes large-scale and low-gradient vertical displacement, but limited ground-based measurements in some places hinder accurate detection
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A knowledge-based data-driven (KBDD) framework for all-day identification of cloud types using satellite remote sensing Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-16 Longfeng Nie, Yuntian Chen, Mengge Du, Changqi Sun, Dongxiao Zhang
Cloud types, as a type of meteorological data, are of particular significance for evaluating changes in rainfall, heatwaves, water resources, floods and droughts, food security and vegetation cover, as well as land use. In order to effectively utilize high-resolution geostationary observations, a knowledge-based data-driven (KBDD) framework for all-day identification of cloud types based on spectral
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Benthic habitat sediments mapping in coral reef area using amalgamation of multi-source and multi-modal remote sensing data Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-15 Xue Ji, Bisheng Yang, Zheng Wei, Mingchang Wang, Qiuhua Tang, Wenxue Xu, Yanhong Wang, Jingyu Zhang, Lin Zhang
Scientific management of coral reefs is a global research topic due to their latent economic value and ecological significance. This research benefits from optical and acoustic remote sensing technology with high spatial resolution, sufficient coverage, and stable repeatability. However, each sensor with its own set of limitations, such as insufficient penetration ability, limited sensor resolution
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Arctic ice-wedge landscape mapping by CNN using a fusion of Radarsat constellation Mission and ArcticDEM Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-15 Michael Merchant, Laura Bourgeau-Chavez, Masoud Mahdianpari, Brian Brisco, Mayah Obadia, Ben DeVries, Aaron Berg
In Canada's Arctic tundra region, permafrost is continuous, and the landscape is rich in patterned features. Polygonal terrain, which includes both high- and low-centered features and their wet trenches below, is considered to be high-latitude wetlands in the continuous permafrost region. These prominent hydrological features retain and transport water within widespread ice-wedge networks and govern
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OBSUM: An object-based spatial unmixing model for spatiotemporal fusion of remote sensing images Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-13 Houcai Guo, Dingqi Ye, Hanzeyu Xu, Lorenzo Bruzzone
Spatiotemporal fusion aims to improve both the spatial and temporal resolution of remote sensing images, thus facilitating time-series analysis at a fine spatial scale. However, there are several important issues that limit the application of current spatiotemporal fusion methods. First, most spatiotemporal fusion methods are based on pixel-level computation, which neglects the valuable shape information
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Advancing our understanding of plant diversity-biological invasion relationships using imaging spectroscopy Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-13 Hamed Gholizadeh, M. Ny Aina Rakotoarivony, Kianoosh Hassani, Kayla G. Johnson, Robert G. Hamilton, Samuel D. Fuhlendorf, Fabian D. Schneider, Benedicte Bachelot
Invasive plants can alter ecosystem composition, structure and function, which in turn may have significant impacts on plant diversity. Although the impacts of biological invasions on plant diversity have been studied in previous literature, results have been inconsistent and occasionally counterintuitive. The crux of the matter is that most of these studies have been fine- or local-scale experiments
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A trained Mask R-CNN model over PlanetScope imagery for very-high resolution surface water mapping in boreal forest-tundra Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-13 Pedro Freitas, Gonçalo Vieira, João Canário, Warwick F. Vincent, Pedro Pina, Carla Mora
Small water bodies (< 0.01 km) showing diverse limnological properties occur in great abundance across the boreal forest and tundra landscapes of the Arctic and Subarctic. However, their classification, geographical distribution and collective importance for water, heat, nutrient, contaminant and carbon cycles are still poorly constrained. One important step for better understanding the role and evolution
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Automatic mapping of 500 m daily open water body fraction in the American continent using GOES-16 ABI imagery Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-13 Xia Wang, Peter M. Atkinson, Yihang Zhang, Xiaodong Li, Kerong Zhang
Timely and large-area monitoring of terrestrial water bodies using remote sensing data is essential to protect water resource security for humans and ecosystems. Although efforts have been made to monitor inter-monthly water bodies at the regional, continental and global scales, surface open water bodies may experience rapid changes within a short duration. At the same time, the data gaps caused by
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Interannual variations and trends of gross primary production and transpiration of four mature deciduous broadleaf forest sites during 2000–2020 Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-10 Li Pan, Xiangming Xiao, Baihong Pan, Cheng Meng, Ralf M. Staebler, Chenchen Zhang, Yuanwei Qin
The interannual variations of gross primary production (GPP) and transpiration (T) in deciduous broadleaf forests reflect how the forest responds to climate change. However, our knowledge remains limited due to lack of multi-decadal data. In this study, we selected four mature deciduous broadleaf forest sites in the United States of America and Canada from 2000 to 2020 to investigate decadal trends
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Deriving photosystem-level red chlorophyll fluorescence emission by combining leaf chlorophyll content and canopy far-red solar-induced fluorescence: Possibilities and challenges Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-10 Linsheng Wu, Yongguang Zhang, Zhaoying Zhang, Xiaokang Zhang, Yunfei Wu, Jing M. Chen
Solar-induced chlorophyll fluorescence (SIF) emitted from photosystem I (PSI) and photosystem II (PSII) is characterized by two peaks centered in the red and far-red spectral regions. SIF provides a unique remotely sensible signal to track plant photosynthetic dynamics. Compared with far-red SIF, red SIF (RSIF) is more strongly linked to PSII and thus with plant photosynthetic activity, but is subject
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Multi-Dimensional matrix MAPping (MDMAP): A new algorithm framework to derive top-of-atmosphere outgoing longwave radiation from space Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-09 Dahui Li, Tianxing Wang, Xiaopo Zheng, Peng Zhang, Lilin Zheng, Wanchun Leng, Yihan Du, Lin Chen, Wanchun Zhang
Outgoing Longwave Radiation (OLR) is an important component of the Earth's radiation budget and a key parameter for coupled models of the atmosphere, ocean, land, and other systems. It is of significant importance in studies related to Earth sciences such as weather forecasting, climate research, and disaster monitoring. Since narrowband sensors are more widely available and have higher spatial resolutions
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Sensitivity analysis for the detection of NO2 plumes from seagoing ships using TROPOMI data Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-08 Solomiia Kurchaba, Artur Sokolovsky, Jasper van Vliet, Fons J. Verbeek, Cor J. Veenman
The marine shipping industry is among the strong emitters of nitrogen oxides (NO) – a substance harmful to ecology and human health. Monitoring of emissions from shipping is a significant societal task. Currently, the only technical possibility to observe NO emission from seagoing ships on a global scale is using TROPOMI data. A range of studies reported that NO plumes from some individual ships can
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Cross-scale mapping of above-ground biomass and shrub dominance by integrating UAV and satellite data in temperate grassland Remote Sens. Environ. (IF 13.5) Pub Date : 2024-02-08 Ang Chen, Cong Xu, Min Zhang, Jian Guo, Xiaoyu Xing, Dong Yang, Bin Xu, Xiuchun Yang
Shrub encroachment, characterized by the proliferation of shrubs into grasslands, is a challenge faced by grasslands worldwide that significantly impacts livestock production and ecosystem functions. Rapid and accurate estimation of shrub dominance is important for understanding changes in plant community structures and formulating grassland management policies. However, the limited spatial resolution