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Use of hyperspectral sounders to retrieve daytime sea-surface temperature from mid-infrared radiances: Application to IASI Remote Sens. Environ. (IF 13.85) Pub Date : 2022-08-08 V. Capelle, J.-M. Hartmann
We propose a physically-based methodology for sea-surface skin-temperature (SST) retrievals from daytime spectra recorded by the hyperspectral Infrared Atmospheric Sounding Interferometer (IASI). The approach, which takes sun light into account, minimizes the differences between measured and computed radiances at numerous points within two windows centered near 3.7 and 4.0 μm. We demonstrate that,
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Non-destructive estimation of individual tree biomass: Allometric models, terrestrial and UAV laser scanning Remote Sens. Environ. (IF 13.85) Pub Date : 2022-08-05 Benjamin Brede, Louise Terryn, Nicolas Barbier, Harm M. Bartholomeus, Renée Bartolo, Kim Calders, Géraldine Derroire, Sruthi M. Krishna Moorthy, Alvaro Lau, Shaun R. Levick, Pasi Raumonen, Hans Verbeeck, Di Wang, Tim Whiteside, Jens van der Zee, Martin Herold
Calibration and validation of aboveground biomass (AGB) (AGB) products retrieved from satellite-borne sensors require accurate AGB estimates across hectare scales (1 to 100 ha). Recent studies recommend making use of non-destructive terrestrial laser scanning (TLS) based techniques for individual tree AGB estimation that provide unbiased AGB predictors. However, applying these techniques across large
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On the capacity of Sentinel-1 synthetic aperture radar in detecting floating macroalgae and other floating matters Remote Sens. Environ. (IF 13.85) Pub Date : 2022-08-03 Lin Qi, Menghua Wang, Chuanmin Hu, Benjamin Holt
Various types of floating macroalgae and other floating matters have been reported in the global oceans and inland waters, and their remote detection has relied primarily on passive optical sensors. These sensors provide multiple spectral bands and frequent revisits, yet they all suffer from clouds. Synthetic aperture radar (SAR) imagers are active sensors that overcome this obstacle, yet their capacity
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Multiparametric sea state fields from synthetic aperture radar for maritime situational awareness Remote Sens. Environ. (IF 13.85) Pub Date : 2022-08-05 Andrey Pleskachevsky, Björn Tings, Stefan Wiehle, James Imber, Sven Jacobsen
This paper introduces a method for estimating a series of sea state parameters from satellite-borne synthetic aperture radar (SAR). The method was realized in a near real time (NRT) application which allows for the processing of data from different satellites and modes. The algorithm estimates the total significant wave height Hs, dominant and secondary swell and windsea wave heights, first, and second
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Disentangling error structures of precipitation datasets using decision trees Remote Sens. Environ. (IF 13.85) Pub Date : 2022-08-02 Xinxin Sui, Zhi Li, Guoqiang Tang, Zong-Liang Yang, Dev Niyogi
Characterizing error structures in precipitation products not only facilitates their proper applications for scientific and practical purposes but also helps improve their retrieval algorithms and processing methods. Despite the fact that multiple precipitation products have been assessed in the literature, factors that affect their error structures remain inadequately addressed. By interpreting 60
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A new phenology-based method for mapping wheat and barley using time-series of Sentinel-2 images Remote Sens. Environ. (IF 13.85) Pub Date : 2022-08-04 Davoud Ashourloo, Hamed Nematollahi, Alfredo Huete, Hossein Aghighi, Mohsen Azadbakht, Hamid Salehi Shahrabi, Salman Goodarzdashti
In recent years, various techniques have been developed to generate crop-type maps based on remote sensing data. Wheat and barley are two major cereal crops cultivated as the first and fourth largest grain crops across the globe. The variations in spectral temporal profile of both crops are generally insignificant at small scales and therefore the two crops are phenologically fairly clearly separated;
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Confidence intervals for proportion of area estimated from a stratified random sample Remote Sens. Environ. (IF 13.85) Pub Date : 2022-08-04 Stephen V. Stehman, Dingfan Xing
Estimating proportion of area from a stratified random sample and reference class labels obtained by ground visit or interpretation of satellite imagery is a common strategy in land cover monitoring. Confidence intervals for the proportion of area are typically estimated using the Wald interval, a procedure that is known to yield less than nominal coverage (i.e., undercoverage) when the proportion
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Unsupervised domain adaptation for global urban extraction using Sentinel-1 SAR and Sentinel-2 MSI data Remote Sens. Environ. (IF 13.85) Pub Date : 2022-08-04 Sebastian Hafner, Yifang Ban, Andrea Nascetti
Accurate and up-to-date maps of built-up areas are crucial to support sustainable urban development. Earth Observation (EO) is a valuable data source to cover this demand. In particular, Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 MultiSpectral Instrument (MSI) missions offer new opportunities to map built-up areas on a global scale. Using Sentinel-2 images, recent urban mapping efforts
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Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review Remote Sens. Environ. (IF 13.85) Pub Date : 2022-08-04 Katja Berger, Miriam Machwitz, Marlena Kycko, Shawn C. Kefauver, Shari Van Wittenberghe, Max Gerhards, Jochem Verrelst, Clement Atzberger, Christiaan van der Tol, Alexander Damm, Uwe Rascher, Ittai Herrmann, Veronica Sobejano Paz, Sven Fahrner, Roland Pieruschka, Egor Prikaziuk, Ma. Luisa Buchaillot, Andrej Halabuk, Martin Schlerf
Remote detection and monitoring of the vegetation responses to stress became relevant for sustainable agriculture. Ongoing developments in optical remote sensing technologies have provided tools to increase our understanding of stress-related physiological processes. Therefore, this study aimed to provide an overview of the main spectral technologies and retrieval approaches for detecting crop stress
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Polarimetric decomposition of microwave-band freshwater ice SAR data: Review, analysis, and future directions Remote Sens. Environ. (IF 13.85) Pub Date : 2022-08-04 Jake E. Ferguson, Grant E. Gunn
The availability and quality of quad-pol synthetic aperture radar (SAR) datasets has increased substantially since the early 2000s, allowing for polarimetrically complete investigations of freshwater ice. These investigations have lead to improved ice classification methods, new understanding of microwave-ice scattering processes, and the potential for new methods to extract ice observables. Such analyses
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Universal quadratic soil spectral reflectance line and its deviation patterns' relationships with chemical and textural properties: A global data base analysis Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-31 Maxim Shoshany, Elena Roitberg, Naftaly Goldshleger, Fadi Kizel
Quantitative evidence for the fundamental spectral shape similarity existing between different soils is presented utilizing Pearson's correlation and SAM (Spectral Angle Mapper) analysis in-between signatures representing thousands of soil samples collected from different environments around the world. A universal quadratic soil line (UQSL) was found to highly fit these representative signatures as
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Evaluating global and regional land warming trends in the past decades with both MODIS and ERA5-Land land surface temperature data Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-28 You-Ren Wang, Dag O. Hessen, Bjørn H. Samset, Frode Stordal
Global surface temperature has been setting new record highs in the recent decades, imposing increasing environmental challenges for societies and ecosystems worldwide. Global warming rates of the 20th century have been documented by a number of studies, nevertheless, the warming rates in the most recent decades in the 21st century are of particular interest for understanding the ongoing climate change
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On the validity of using ground-based observations to validate geostationary-satellite-derived direct and diffuse surface solar irradiance: Quantifying the spatial mismatch and temporal averaging issues Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-28 Yi Qin, Tim R. McVicar, Jing Huang, Sam West, Andrew D.L. Steven
This paper discusses the differences, due to different measuring mechanisms, of satellite-derived and ground measured surface solar irradiance (SSI) direct and diffuse components, and the impacts of the differences when validating satellite-derived data using ground measurements, using SSI products derived from the Advanced Himawari Imager. The issue of satellite-ground mismatch, though previously
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Sugarcane abandonment mapping in Rio de Janeiro state Brazil Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-28 Pedro Ivo Bastos de Castro, He Yin, Paulo Domingos Teixera Junior, Eduardo Lacerda, Rui Pedroso, Sven Lautenbach, Raúl Sánchez Vicens
The mapping of sugarcane plantations and their changes is relevant to the economy and the environment, notably due to sugarcane's interface in the biofuel industry through ethanol. The necessary mapping of sugarcane crop changes is especially challenging when plantation occurs under smallholders' land ownership structures used for heterogeneous crop management. We evaluated two approaches to address
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Estimates of diurnal and daily net primary productivity using the Geostationary Ocean Color Imager (GOCI) data Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-28 Jinghui Wu, Joaquim I. Goes, Helga do Rosario Gomes, Zhongping Lee, Jae-Hoon Noh, Jianwei Wei, Zhehai Shang, Joseph Salisbury, Antonio Mannino, Wonkook Kim, Young-Je Park, Michael Ondrusek, Veronica P. Lance, Menghua Wang, Robert Frouin
For the past three decades, polar-orbiting ocean color satellites have provided local, regional to global scale estimates of oceanic net primary production that have greatly aided studies of ocean carbon cycling, food web dynamics and climate change. Despite considerable progress, accurate estimates of daily ocean productivity from space have not been realized because polar-orbiting satellites are
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Fifty years of Landsat science and impacts Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-28 Michael A. Wulder, David P. Roy, Volker C. Radeloff, Thomas R. Loveland, Martha C. Anderson, David M. Johnson, Sean Healey, Zhe Zhu, Theodore A. Scambos, Nima Pahlevan, Matthew Hansen, Noel Gorelick, Christopher J. Crawford, Jeffrey G. Masek, Txomin Hermosilla, Joanne C. White, Alan S. Belward, Crystal Schaaf, Bruce D. Cook
Since 1972, the Landsat program has been continually monitoring the Earth, to now provide 50 years of digital, multispectral, medium spatial resolution observations. Over this time, Landsat data were crucial for many scientific and technical advances. Prior to the Landsat program, detailed, synoptic depictions of the Earth's surface were rare, and the ability to acquire and work with large datasets
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IrriMap_CN: Annual irrigation maps across China in 2000–2019 based on satellite observations, environmental variables, and machine learning Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-27 Chao Zhang, Jinwei Dong, Quansheng Ge
Agricultural irrigation, as an important practice to protect crops from drought and promote grain yield, has a long history in China. A timely and precise dataset about the extent and dynamics of irrigated areas is necessary for water allocation and agricultural management but is scarce in China. Here we developed annual irrigated cropland maps across China (IrriMap_CN) at 500-m resolution from 2000
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On the effects of cloud water content on passive microwave snowfall retrievals Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-26 Sajad Vahedizade, Ardeshir Ebtehaj, Sagar Tamang, Yalei You, Giulia Panegrossi, Sarah Ringerud, F. Joseph Turk
The Bayesian passive microwave retrievals of snowfall often rely on mathematical matching of the observed vectors of brightness temperature with an a priori database of precipitation profiles and their corresponding brightness temperatures. Mathematical proximity does not necessarily lead to consistent retrievals due to limited information content of passive microwave observations. This paper defines
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Reconstructing GRACE-like time series of high mountain glacier mass anomalies Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-25 Bingshi Liu, Xiancai Zou, Shuang Yi, Nico Sneeuw, Jiancheng Li, Jianqiang Cai
High mountain glaciers (HMGs), called the water towers of the world, are vulnerable to the effects of climate change and thus are rapidly shrinking. Monitoring and evaluating large-scale glacier and snow (GS) mass changes are critical for humans and ecosystems. Although modern gravity satellites monitor GS on a global scale, the contemporary Gravity Recovery and Climate Experiment (GRACE) and GRACE
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How to consider the effects of time of day, beam strength, and snow cover in ICESat-2 based estimation of boreal forest biomass? Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-25 P. Varvia, L. Korhonen, A. Bruguière, J. Toivonen, P. Packalen, M. Maltamo, S. Saarela, S.C. Popescu
The objective of this study was to explore the effects of (1) the presence/absence of snow and snow depth, (2) solar noise, i.e., day/night and sun angle observations, and (3) strong/weak beam differences on ICESat-2 data in the context of data utility for forest AGB estimation. The framework of the study is multiphase modeling, where AGB field data and wall-to-wall airborne laser scanning (ALS) and
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Assessing and modeling diurnal temperature buffering and evapotranspiration dynamics in forest restoration using ECOSTRESS thermal imaging Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-23 L. Jonas Hamberg, Joshua B. Fisher, Jonathan L.W. Ruppert, Jessica Tureček, Dean H. Rosen, Patrick M.A. James
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Estimation of biomass burning emissions by integrating ICESat-2, Landsat 8, and Sentinel-1 data Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-21 Meng Liu, Sorin Popescu
Anthropogenic carbon emissions directly contribute to global warming, which has induced severe environmental concerns like extreme droughts and devastating fires. To evaluate the effects of fires on carbon cycling and climate change, it is crucial to accurately estimate the amount of carbon released during fires. The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) mission offers spaceborne light
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Observational evidence of elevated smoke layers during crop residue burning season over Delhi: Potential implications on associated heterogeneous PM2.5 enhancements Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-21 Alaa Mhawish, Chandan Sarangi, Priyadharshini Babu, Manish Kumar, Muhammad Bilal, Zhongfeng Qiu
Post monsoonal agricultural Crop Residue Burning (CRB) over northwestern India is believed to severely affect the air quality of the megacity of Delhi. However, the mechanistic understanding remains elusive. Long-term satellite observations (2007–2020) of aerosol properties during CRB season (Oct 20th to Nov 20th) indicate a distinct airshed of CRB plume transport from Northwestern India (source region)
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Validation of ocean color remote sensing reflectance data: Analysis of results at European coastal sites Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-20 F. Mélin
From its initial measurements 20 years ago, the Ocean Color component of the Aerosol Robotic Network (AERONET-OC) has produced large validation data sets to assess the ocean color satellite data records. This study, applied to the standard atmospheric correction algorithm l2gen of the National Aeronautics and Space Administration, analyses the populations of residuals (differences between matching
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An advanced soil organic carbon content prediction model via fused temporal-spatial-spectral (TSS) information based on machine learning and deep learning algorithms Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-20 Xiangtian Meng, Yilin Bao, Yiang Wang, Xinle Zhang, Huanjun Liu
Knowledge of the soil organic carbon (SOC) content is critical for environmental sustainability and carbon neutrality. With the development of remote sensing data and prediction models, the comprehensive utilization of multisource remote sensing data based on a fusion approach and testing its effectiveness in SOC content prediction is an interesting and challenging topic. However, there is no evidence
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Direct use of large-footprint lidar waveforms to estimate aboveground biomass Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-18 Wenge Ni-Meister, Alejandro Rojas, Shihyan Lee
Many studies have established the strong connections between aboveground biomass and lidar height metrics; however, these relationships are site-specific. Field data required to derive these relationships are not readily available in many cases. We developed a model to estimate plot-level aboveground biomass density (AGBD) directly from large-footprint lidar waveform measurements. An individual tree-based
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Improving soil moisture assimilation efficiency via model calibration using SMAP surface soil moisture climatology information Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-18 Jianhong Zhou, Wade T. Crow, Zhiyong Wu, Jianzhi Dong, Hai He, Huihui Feng
To minimize systematic differences between soil moisture (SM) time series derived from remote sensing (RS) and land surface model (LSM), RS-based SM climatology information is typically discarded during land data assimilation (DA). However, recent studies have demonstrated that SM climatology estimates provided by L-band microwave RS retrievals can significantly outperform comparable estimates derived
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Challenging the link between functional and spectral diversity with radiative transfer modeling and data Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-18 Javier Pacheco-Labrador, Mirco Migliavacca, Xuanlong Ma, Miguel Mahecha, Nuno Carvalhais, Ulrich Weber, Raquel Benavides, Olivier Bouriaud, Ionut Barnoaiea, David A. Coomes, Friedrich J. Bohn, Guido Kraemer, Uta Heiden, Andreas Huth, Christian Wirth
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Seasonal development and radiative forcing of red snow algal blooms on two glaciers in British Columbia, Canada, summer 2020 Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-17 Casey B. Engstrom, Scott N. Williamson, John A. Gamon, Lynne M. Quarmby
Red snow algal blooms reduce albedo and increase snowmelt, but little is known of their extent, duration, and radiative forcing. We calibrated an established index by comparing snow algal field spectroradiometer measurements with direct counts of algal cell abundance in British Columbia, Canada. We applied the field calibrated index to Sentinel-2, Landsat-8, and MODIS/Terra images to monitor snow algae
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Seasonal patterns of spectral diversity at leaf and canopy scales in the Cedar Creek prairie biodiversity experiment Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-16 Ran Wang, John A. Gamon, Jeannine Cavender-Bares
The relationship between biodiversity and spectral diversity is highly scale-dependent, and temporal variation in leaf morphological, biochemical traits and canopy structure can alter this relationship. However, the temporal dependence of the spectral diversity – biodiversity relationship is poorly understood, in part due to the difficulties of obtaining consistent measurements across space and time
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Continuous measurement of sea ice freeboard with tide gauges and GNSS interferometric reflectometry Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-13 Surui Xie
Sea ice thickness is an important climate indicator and is often monitored in the form of freeboard or total freeboard (with snow cover) using satellite altimetry. However, satellites often have a long revisit interval and freeboard measurements in coastal areas can be challenged by land, deformed ice and limited leads. Using a combination of tide gauge for sea level measurements and a coastal GNSS
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Properties of aerosol and surface derived from OLCI/Sentinel-3A using GRASP approach: Retrieval development and preliminary validation Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-09 Cheng Chen, Oleg Dubovik, Pavel Litvinov, David Fuertes, Anton Lopatin, Tatyana Lapyonok, Christian Matar, Yana Karol, Juergen Fischer, Rene Preusker, Andreas Hangler, Michael Aspetsberger, Lukas Bindreiter, Daniel Marth, Julien Chimot, Bertrand Fougnie, Thierry Marbach, Bojan Bojkov
The Ocean and Land Color Instrument (OLCI) onboard the Copernicus Sentinel-3A satellite is a medium-resolution and multi-spectral push-broom imager acquiring radiance in 21 spectral bands covering from the visible to the far near-infrared. These measurements are primary dedicated to land & ocean color applications, but actually include also reliable information for atmospheric aerosol and surface brightness
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Estimating monthly global ground-level NO2 concentrations using geographically weighted panel regression Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-08 Chao Li, Shunsuke Managi
Predicting long-term ground-level nitrogen dioxide (NO2) is important globally to support environmental and public health research and to provide information to governments and society for air pollution control policies. The ozone monitoring instrument (OMI), onboard Aura Satellite, detects monthly global tropospheric column amounts (TrCA) of NO2 molecules. However, the relationship between the ground-level
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Millimeter slope ratcheting from multitemporal SAR interferometry with a correction of coastal tropospheric delay: A case study in Hong Kong Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-07 Guoqiang Shi, Bo Huang, Anthony Kwan Leung, Charles W.W. Ng, Zhilu Wu, Hui Lin
Tropospheric delays (TDs) limit the accurate detection of slow slope motion using interferometric synthetic aperture radar (InSAR), especially in subtropical coastal regions prone to frequent changes in humidity. Although TDs can be estimated through external weather data, their spatiotemporal resolution and data availability are greatly limited, which is not applicable for individual slopes. This
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Error and uncertainty characterization of soil moisture and VOD retrievals obtained from L-band SMAP radiometer Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-06 P. Konkathi, L. Karthikeyan
L-band passive microwave remote sensing has evolved over the past decade to estimate soil moisture (SM) and Vegetation Optical Depth (VOD). Novel Radiative Transfer Model (RTM) schemes and model parameterizations are proposed to achieve this goal. In this work, we attempt to characterize errors and uncertainties that propagate from RTMs and their parameters while retrieving SM and VOD from Soil Moisture
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Individual tree segmentation and tree species classification in subtropical broadleaf forests using UAV-based LiDAR, hyperspectral, and ultrahigh-resolution RGB data Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-06 Haiming Qin, Weiqi Zhou, Yang Yao, Weimin Wang
Accurate classification of individual tree species is essential for inventorying, managing, and protecting forest resources. Individual tree species classification in subtropical forests remains challenging as existing individual tree segmentation algorithms typically result in over-segmentation in subtropical broadleaf forests, in which tree crowns often have multiple peaks. In this study, we proposed
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The post-fire stability index; a new approach to monitoring post-fire recovery by satellite imagery Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-06 Rebecca K. Gibson, Laura A. White, Samuel Hislop, Rachael H. Nolan, Josh Dorrough
Ecological resilience is the capacity of a system to maintain function following disturbance. With the frequency and severity of wildfire activity increasing due to warmer and drier global climate conditions, there are increasing reports of declines in ecological resilience and ecosystems at risk of collapse due to post-fire recovery failure. Observational monitoring of post-fire recovery at the landscape
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Accurate mean wave period from SWIM instrument on-board CFOSAT Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-04 Haoyu Jiang, Yuhao Song, Alexey Mironov, Zheng Yang, Ying Xu, Jianqiang Liu
The Surface Waves Investigation and Monitoring (SWIM) instrument onboard the China–France Oceanography Satellite (CFOSAT) can provide wave spectra using its off-nadir beams. Although SWIM shows a reasonable performance for capturing spectral peak, the accuracy of mean wave periods (MWPs) computed directly from the SWIM spectra is not satisfying due to the high noise level of the spectra. SWIM can also
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A PSI targets characterization approach to interpreting surface displacement signals: A case study of the Shanghai metro tunnels Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-04 Mengshi Yang, Ru Wang, Menghua Li, Mingsheng Liao
Persistent Scatterer Interferometry (PSI) is a multi-epoch InSAR method for measuring displacements of Earth's surface over time by exploring the interferometric phase of constantly coherent points, named Persistent Scatterer (PS). PSI has shown its superior capability to monitor linear features with long-distance and large-span characteristics. Nevertheless, the interpretation of estimated displacements
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A new object-class based gap-filling method for PlanetScope satellite image time series Remote Sens. Environ. (IF 13.85) Pub Date : 2022-07-01 Jing Wang, Calvin K.F. Lee, Xiaolin Zhu, Ruyin Cao, Yating Gu, Shengbiao Wu, Jin Wu
PlanetScope CubeSats data with a 3-m resolution, frequent revisits, and global coverage have provided an unprecedented opportunity to advance land surface monitoring over the recent years. Similar to other optical satellites, cloud-induced data missing in PlanetScope satellites substantially hinders its use for broad applications. However, effective gap-filling in PlanetScope image time series remains
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Mowing detection using Sentinel-1 and Sentinel-2 time series for large scale grassland monitoring Remote Sens. Environ. (IF 13.85) Pub Date : 2022-06-30 Mathilde De Vroey, Laura de Vendictis, Massimo Zavagli, Sophie Bontemps, Diane Heymans, Julien Radoux, Benjamin Koetz, Pierre Defourny
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Evaluating the role of solar-induced fluorescence (SIF) and plant physiological traits for leaf nitrogen assessment in almond using airborne hyperspectral imagery Remote Sens. Environ. (IF 13.85) Pub Date : 2022-06-29 Y. Wang, L. Suarez, T. Poblete, V. Gonzalez-Dugo, D. Ryu, P.J. Zarco-Tejada
Accurate, spatially extensive, and frequent assessments of plant nitrogen (N) enabled by remote sensing allow growers to optimize fertilizer applications and reduce environmental impacts. Standard remote sensing methods for N assessment typically involve the use of chlorophyll-sensitive vegetation indices calculated from multispectral or hyperspectral reflectance data. However, the chlorophyll a + b
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C- and L-band SAR signatures of Arctic sea ice during freeze-up Remote Sens. Environ. (IF 13.85) Pub Date : 2022-06-28 Mallik S. Mahmud, Vishnu Nandan, Suman Singha, Stephen E.L. Howell, Torsten Geldsetzer, John Yackel, Benoit Montpetit
Identifying sea ice types in the early stages of development from L-band SAR imagery remains an active research area during the Arctic freeze-up period. We used ScanSAR C- and L-band imagery from RADARSAT-2, ALOS PALSAR and ALOS-2 PALSAR-2, to identify ice types in the North Water Polynya (NOW) and Victoria Strait (VS) region of the Canadian Arctic. We investigated the HH-polarized microwave backscatter
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A machine learning method trained by radiative transfer model inversion for generating seven global land and atmospheric estimates from VIIRS top-of-atmosphere observations Remote Sens. Environ. (IF 13.85) Pub Date : 2022-06-28 Guodong Zhang, Han Ma, Shunlin Liang, Aolin Jia, Tao He, Dongdong Wang
The Visible Infrared Imaging Radiometer Suite (VIIRS) has observed the Earth since 2011 and will continue for several decades. Unfortunately, few high-level land surface products have been produced and publicly released. The numerical inversion of radiative transfer model (RTM) has long been used for the retrieval of land surface and atmospheric variables from satellite data; however, it is computationally
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Sun-induced chlorophyll fluorescence is more strongly related to photosynthesis with hemispherical than nadir measurements: Evidence from field observations and model simulations Remote Sens. Environ. (IF 13.85) Pub Date : 2022-06-28 Zhaoying Zhang, Xiaokang Zhang, Albert Porcar-Castell, Jing M. Chen, Weimin Ju, Linsheng Wu, Yunfei Wu, Yongguang Zhang
Solar-induced chlorophyll fluorescence (SIF) has been shown to be a novel proxy for terrestrial gross primary production (GPP). A growing number of ground-based automatic SIF observation systems equipped with hemispherical-conical and bi-hemispherical observation configurations have been developed in synergy with EC flux measurements across different ecosystems. However, the difference in the canopy
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Forest canopy stratification based on fused, imbalanced and collinear LiDAR and Sentinel-2 metrics Remote Sens. Environ. (IF 13.85) Pub Date : 2022-06-28 Jakob Wernicke, Christian Torsten Seltmann, Ralf Wenzel, Carina Becker, Michael Körner
Knowledge about the forest canopy stratification is of essential importance for forest management and planning. Collecting structural information (e.g. natural regeneration) still depends on cost and labour intensive forest inventories with a coarse spatio-temporal resolution. Remote sensing partly overcomes these limitations and particularly active sensors of type light detection and ranging (LiDAR)
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Decoupling of greenness and gross primary productivity as aridity decreases Remote Sens. Environ. (IF 13.85) Pub Date : 2022-06-28 Zhongmin Hu, Shilong Piao, Alan K. Knapp, Xuhui Wang, Shushi Peng, Wenping Yuan, Steve Running, Jiafu Mao, Xiaoying Shi, Philippe Ciais, Deborah N. Huntzinger, Jia Yang, Guirui Yu
Ecosystem primary productivity is a key ecological process influencing many ecosystem services, including carbon storage. Thus, clarifying how primary productivity in terrestrial ecosystems responds to climatic variability can reveal key mechanisms that will drive future changes in the global carbon budget. Satellite products of canopy greenness are widely used as proxies for vegetation productivity
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Improved global evapotranspiration estimates using proportionality hypothesis-based water balance constraints Remote Sens. Environ. (IF 13.85) Pub Date : 2022-06-28 Jianyu Fu, Weiguang Wang, Quanxi Shao, Wanqiu Xing, Mingzhu Cao, Jia Wei, Zefeng Chen, Wanshu Nie
Accurate estimation of global evapotranspiration (ET) is critical to understand the water and energy cycles in the Earth system. Satellite-driven ET algorithms serve as an effective way to estimate the global ET. However, many algorithms have been designed independently of water balance constraints, which potentially limit their ability to estimate ET in water-limited and high interception regions
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Submarine groundwater discharge detection through remote sensing: An application of Landsat 7 and 8 in Hawaiʻi and Ireland Remote Sens. Environ. (IF 13.85) Pub Date : 2022-06-28 Júlio Caineta, Brian F. Thomas, Daniel J. Bain
Submarine groundwater discharge (SGD) represents an important component of the global water cycle. Improved assessment of SGD occurrences provides information to constrain current estimates of total freshwater discharges, which are crucial for evaluation of changes in the global water cycle. This study leverages SGD linkages to patterns in sea surface temperature (SST) and color. Typically, groundwater
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Estimation of vertical plant area density from single return terrestrial laser scanning point clouds acquired in forest environments Remote Sens. Environ. (IF 13.85) Pub Date : 2022-06-28 Van-Tho Nguyen, Richard A. Fournier, Jean-François Côté, François Pimont
Plant area density (PAD in m2·m−3) defines the total one-sided total plant surface area within a given volume. It is a key variable in characterizing exchange processes between the atmosphere and land surface. Terrestrial laser scanning (TLS) provides unprecedented detail of the 3D structure of forest canopies. Yet, signal occlusion and uneven sampling density of the TLS point clouds limit our capacity
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Identification of saline landscapes from an integrated SVM approach from a novel 3-D classification schema using Sentinel-1 dual-polarized SAR data Remote Sens. Environ. (IF 13.85) Pub Date : 2022-06-28 Shoba Periasamy, Kokila Priya Ravi, Kevin Tansey
This study presented an integrated SVM classification method that investigated the relationship between intrinsic scattering attributes of the surface features and the conductivity characteristics of the soil in the newly proposed two- and three-dimensional classification (2D and 3D) schema to classify the saline landscape. The study was conducted in the Vellore district, Tamil Nadu, which is composed
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An advanced change detection method for time-series soil moisture retrieval from Sentinel-1 Remote Sens. Environ. (IF 13.85) Pub Date : 2022-06-28 Liujun Zhu, Rui Si, Xiaoji Shen, Jeffrey P. Walker
The feasibility of soil moisture retrieval from C-band Sentinel-1 data has been widely acknowledged, with pre-operational 1-km products currently available at regional and/or continental scale using the long-term (LTCD) or short-term change detection (STCD) methods. Both algorithms share the same assumptions of time-invariant roughness and vegetation, which can be questionable even for a short period
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Evaluating irrigation status in the Mekong Delta through polarimetric L-band SAR data assimilation Remote Sens. Environ. (IF 13.85) Pub Date : 2022-06-28 Hironori Arai, Thuy Le Toan, Wataru Takeuchi, Kei Oyoshi, Tamon Fumoto, Kazuyuki Inubushi
For sustainable food production in the Mekong Delta, local information on irrigation status is essential for allocating water resources efficiently at the community level. ALOS-2 PALSAR-2 L-band SAR can be used to detect submerged and nonsubmerged soil covered by rice plants at a spatial resolution compatible with field observation but a low temporal resolution. In this study, a new multiscale data
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Statistically rigorous, model-based inferences from maps Remote Sens. Environ. (IF 13.85) Pub Date : 2022-06-21 Ronald E. McRoberts, Erik Næsset, Sassan Saatchi, Shaun Quegan
Statistically rigorous inferences in the form of confidence intervals for map-based estimates require model-based inferential methods. Model-based mean square errors (MSE) incorporate estimates of both residual variability and sampling variability, of which the latter includes population unit variance estimates and pairwise population unit covariance estimates. Bootstrapping, which can be used with
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Estimating sea level, wind direction, significant wave height, and wave peak period using a geodetic GNSS receiver Remote Sens. Environ. (IF 13.85) Pub Date : 2022-06-22 Xiaolei Wang, Xiufeng He, Jian Shi, Shu Chen, Zijin Niu
Monitoring oceanographic parameters is essential for marine engineering construction, coastal safety, marine analysis, and climatic analysis. Traditionally, oceanographic parameters have been monitored using different sensors. With the development of global navigation satellite systems (GNSS), signal-to-noise ratio (SNR) observations have been found to oscillate due to the interference between direct
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Determination of weather-induced short-term sea level variations by GNSS reflectometry Remote Sens. Environ. (IF 13.85) Pub Date : 2022-06-21 Théo Gravalon, Lucía Seoane, Guillaume Ramillien, José Darrozes, Laurent Roblou
We propose to derive local sea level variations by using the Signal-to-Noise Ratio (SNR) of the GNSS reflected signals at four GNSS single antenna sites (ILDG, TAR0, FFT2, LYTT) located at different latitudes. For these sites representing various ocean conditions (waves, tides, storm surges, etc…), tides estimates by SNR are highly consistent to tide gauges records as highlighted by tidal harmonic
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A scale-sensitive framework for the spatially explicit accuracy assessment of binary built-up surface layers Remote Sens. Environ. (IF 13.85) Pub Date : 2022-06-21 Johannes H. Uhl, Stefan Leyk
To better understand the dynamics of human settlements, thorough knowledge of the uncertainty in geospatial built-up surface datasets is critical. While frameworks for localized accuracy assessments of categorical gridded data have been proposed to account for the spatial non-stationarity of classification accuracy, such approaches have not been applied to (binary) built-up land data. Such data differs
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Multi-frequency radiometer-based soil moisture retrieval and algorithm parameterization using in situ sites Remote Sens. Environ. (IF 13.85) Pub Date : 2022-06-21 Y. Gao, A. Colliander, M.S. Burgin, J.P. Walker, E. Dinnat, C. Chae, M.H. Cosh, T.G. Caldwell, A. Berg, J. Martinez-Fernandez, M. Seyfried, P.J. Starks, D.D. Bosch, H. McNairn, Z. Su, R. van der Velde
L-band brightness temperature (TB) has been shown to provide the best sensitivity to soil moisture (SM) although C- and X-band based products offer a longer time-series from satellite-based measurements. Currently, global coverage SM is routinely produced from spaceborne measurements using all three frequency bands, but despite continued validation efforts of the products, the relative characteristics
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Exploring the interrelated effects of soil background, canopy structure and sun-observer geometry on canopy photochemical reflectance index Remote Sens. Environ. (IF 13.85) Pub Date : 2022-06-20 Peiqi Yang
Photochemical reflectance index (PRI) is an intriguing avenue for monitoring photosynthetic light use efficiency (LUE), which is a crucial physiological variable and the primary source of uncertainty in gross primary production (GPP) prediction. The correlations between PRI and LUE induced by the energy-dependent xanthophyll cycle are overall convincing at the leaf scale. However, their relationship
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Effects of environmental conditions on ICESat-2 terrain and canopy heights retrievals in Central European mountains Remote Sens. Environ. (IF 13.85) Pub Date : 2022-06-17 Vítězslav Moudrý, Kateřina Gdulová, Lukáš Gábor, Eliška Šárovcová, Vojtěch Barták, Francois Leroy, Olga Špatenková, Duccio Rocchini, Jiří Prošek