Remote Sensing Letters

Papers
(The H4-Index of Remote Sensing Letters is 15. 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 2020-03-01 to 2024-03-01.)
ArticleCitations
Tree extraction from multi-scale UAV images using Mask R-CNN with FPN59
Validation of sentinel-2 leaf area index (LAI) product derived from SNAP toolbox and its comparison with global LAI products in an African semi-arid agricultural landscape49
Combined use of Sentinel-2 and Landsat 8 to monitor water surface area dynamics using Google Earth Engine38
Remote Sensing Letters contribution to the success of the Sustainable Development Goals - UN 2030 agenda31
SSS-YOLO: towards more accurate detection for small ships in SAR image26
Deep CNN-based hyperspectral image classification using discriminative multiple spatial-spectral feature fusion23
An improved unsupervised representation learning generative adversarial network for remote sensing image scene classification21
Simple weakly supervised deep learning pipeline for detecting individual red-attacked trees in VHR remote sensing images20
Snow covered with dust after Chamoli rockslide: inference based on high-resolution satellite data19
Sentinel-2 based prediction of spruce budworm defoliation using red-edge spectral vegetation indices19
A non-local capsule neural network for hyperspectral remote sensing image classification18
Effects of the Covid-19 pandemic on the oceans18
Prediction of sea surface temperature using a multiscale deep combination neural network17
Hydroponic farming hotspot analysis using the Getis–Ord Gi* statistic and high-resolution satellite data of Majuli Island, India16
Improved quantum evolutionary particle swarm optimization for band selection of hyperspectral image15
Radar CFAR detection in Weibull clutter based on zlog(z) estimator15
Snow depth and snow water equivalent retrieval using X-band PolInSAR data15
Multi-temporal mapping of flood damage to crops using sentinel-1 imagery: a case study of the Sesia River (October 2020)15
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