Remote Sensing of Environment

Papers
(The H4-Index of Remote Sensing of Environment is 87. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-02-01 to 2024-02-01.)
ArticleCitations
Deep learning in environmental remote sensing: Achievements and challenges698
Land-cover classification with high-resolution remote sensing images using transferable deep models433
Remote sensing of night lights: A review and an outlook for the future412
Soybean yield prediction from UAV using multimodal data fusion and deep learning408
Mapping global forest canopy height through integration of GEDI and Landsat data404
Reconstructing 1-km-resolution high-quality PM2.5 data records from 2000 to 2018 in China: spatiotemporal variations and policy implications391
lidR: An R package for analysis of Airborne Laser Scanning (ALS) data342
A review of vegetation phenological metrics extraction using time-series, multispectral satellite data337
Have satellite precipitation products improved over last two decades? A comprehensive comparison of GPM IMERG with nine satellite and reanalysis datasets302
Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification262
Seamless retrievals of chlorophyll-a from Sentinel-2 (MSI) and Sentinel-3 (OLCI) in inland and coastal waters: A machine-learning approach226
Continental-scale land surface phenology from harmonized Landsat 8 and Sentinel-2 imagery216
Rapid and robust monitoring of flood events using Sentinel-1 and Landsat data on the Google Earth Engine203
Mapping and sampling to characterize global inland water dynamics from 1999 to 2018 with full Landsat time-series203
Terrestrial laser scanning in forest ecology: Expanding the horizon197
WHU-Hi: UAV-borne hyperspectral with high spatial resolution (H2) benchmark datasets and classifier for precise crop identification based on deep convolutional neural network with CRF196
Mapping cropping intensity in China using time series Landsat and Sentinel-2 images and Google Earth Engine175
Crop nitrogen monitoring: Recent progress and principal developments in the context of imaging spectroscopy missions169
A machine learning approach to estimate chlorophyll-a from Landsat-8 measurements in inland lakes168
Dual polarimetric radar vegetation index for crop growth monitoring using sentinel-1 SAR data165
A remote sensing approach to mapping fire severity in south-eastern Australia using sentinel 2 and random forest161
Landsat 9: Empowering open science and applications through continuity156
Full-coverage mapping and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China150
Remote sensing of shallow waters – A 50 year retrospective and future directions149
Validation practices for satellite soil moisture retrievals: What are (the) errors?149
Biomass estimation from simulated GEDI, ICESat-2 and NISAR across environmental gradients in Sonoma County, California146
Monitoring tropical forest degradation using spectral unmixing and Landsat time series analysis146
Evolution of evapotranspiration models using thermal and shortwave remote sensing data145
NASA's surface biology and geology designated observable: A perspective on surface imaging algorithms141
Tracking annual changes of coastal tidal flats in China during 1986–2016 through analyses of Landsat images with Google Earth Engine138
Satellite-derived bathymetry using the ICESat-2 lidar and Sentinel-2 imagery datasets138
Monitoring biodiversity in the Anthropocene using remote sensing in species distribution models136
Continuous monitoring of land disturbance based on Landsat time series135
Mapping urban dynamics (1992–2018) in Southeast Asia using consistent nighttime light data from DMSP and VIIRS134
ACIX-Aqua: A global assessment of atmospheric correction methods for Landsat-8 and Sentinel-2 over lakes, rivers, and coastal waters128
Deep learning on edge: Extracting field boundaries from satellite images with a convolutional neural network127
A roadmap for high-resolution satellite soil moisture applications – confronting product characteristics with user requirements125
Fifty years of Landsat science and impacts123
Thematic accuracy assessment of the NLCD 2016 land cover for the conterminous United States122
Rapid, robust, and automated mapping of tidal flats in China using time series Sentinel-2 images and Google Earth Engine122
Transitioning from change detection to monitoring with remote sensing: A paradigm shift120
A practical reanalysis data and thermal infrared remote sensing data merging (RTM) method for reconstruction of a 1-km all-weather land surface temperature119
Accurate cloud detection in high-resolution remote sensing imagery by weakly supervised deep learning119
Robust algorithm for estimating total suspended solids (TSS) in inland and nearshore coastal waters118
Hotspots of snow cover changes in global mountain regions over 2000–2018118
Generation of MODIS-like land surface temperatures under all-weather conditions based on a data fusion approach118
Three-dimensional convolutional neural network model for tree species classification using airborne hyperspectral images117
Lessons learned implementing an operational continuous United States national land change monitoring capability: The Land Change Monitoring, Assessment, and Projection (LCMAP) approach117
Performance evaluation of GEDI and ICESat-2 laser altimeter data for terrain and canopy height retrievals116
Soil moisture experiment in the Luan River supporting new satellite mission opportunities114
Modelling lidar-derived estimates of forest attributes over space and time: A review of approaches and future trends113
Sea surface salinity estimates from spaceborne L-band radiometers: An overview of the first decade of observation (2010–2019)113
The PRISMA imaging spectroscopy mission: overview and first performance analysis113
SMOS-IC data record of soil moisture and L-VOD: Historical development, applications and perspectives112
Eutrophication changes in fifty large lakes on the Yangtze Plain of China derived from MERIS and OLCI observations109
Continental-scale mapping and analysis of 3D building structure108
Tree species classification from airborne hyperspectral and LiDAR data using 3D convolutional neural networks108
PROSPECT-PRO for estimating content of nitrogen-containing leaf proteins and other carbon-based constituents105
A systematic review and assessment of algorithms to detect, characterize, and monitor urban land change104
RF-MEP: A novel Random Forest method for merging gridded precipitation products and ground-based measurements104
Multi-sensor remote sensing for drought characterization: current status, opportunities and a roadmap for the future103
Hyperlocal mapping of urban air temperature using remote sensing and crowdsourced weather data102
DeepCropMapping: A multi-temporal deep learning approach with improved spatial generalizability for dynamic corn and soybean mapping101
Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission100
Building damage assessment for rapid disaster response with a deep object-based semantic change detection framework: From natural disasters to man-made disasters100
Mapping sugarcane plantation dynamics in Guangxi, China, by time series Sentinel-1, Sentinel-2 and Landsat images100
High-resolution retrieval of cloud microphysical properties and surface solar radiation using Himawari-8/AHI next-generation geostationary satellite100
How to quantify the cooling effect of urban parks? Linking maximum and accumulation perspectives99
Evaluation of machine learning algorithms for forest stand species mapping using Sentinel-2 imagery and environmental data in the Polish Carpathians97
Present-day land subsidence rates, surface faulting hazard and risk in Mexico City with 2014–2020 Sentinel-1 IW InSAR96
Improving land cover classification in an urbanized coastal area by random forests: The role of variable selection95
Review of GPM IMERG performance: A global perspective94
A review of machine learning in processing remote sensing data for mineral exploration94
Changes of water clarity in large lakes and reservoirs across China observed from long-term MODIS93
Fusing simulated GEDI, ICESat-2 and NISAR data for regional aboveground biomass mapping93
Reconstruction of daytime land surface temperatures under cloud-covered conditions using integrated MODIS/Terra land products and MSG geostationary satellite data93
Characterizing land cover/land use from multiple years of Landsat and MODIS time series: A novel approach using land surface phenology modeling and random forest classifier92
Validation of ICESat-2 terrain and canopy heights in boreal forests92
Generating surface soil moisture at 30 m spatial resolution using both data fusion and machine learning toward better water resources management at the field scale92
Deep building footprint update network: A semi-supervised method for updating existing building footprint from bi-temporal remote sensing images92
Pan-tropical soil moisture mapping based on a three-layer model from CYGNSS GNSS-R data91
Deep learning-based air temperature mapping by fusing remote sensing, station, simulation and socioeconomic data90
Monthly estimation of the surface water extent in France at a 10-m resolution using Sentinel-2 data90
Phenology of short vegetation cycles in a Kenyan rangeland from PlanetScope and Sentinel-289
InSAR-based detection method for mapping and monitoring slow-moving landslides in remote regions with steep and mountainous terrain: An application to Nepal89
The application of Unmanned Aerial Vehicles (UAVs) to estimate above-ground biomass of mangrove ecosystems87
Mapping erosion and deposition in an agricultural landscape: Optimization of UAV image acquisition schemes for SfM-MVS87
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