IEEE Geoscience and Remote Sensing Letters
IEEE Geoscience and Remote Sensing Letters (GRSL) publishes short papers (maximum length 5 pages) addressing new ideas and formative concepts in remote sensing as well as important new and timely results and concepts. Papers should relate to the theory, concepts and techniques of...
Metrics
Scimago and CountryOfPapers database fields
SJR Impact
1,258
H-index
163
Docs (year)
1199
Docs 3y
3127
Total refs
23286
Cites 3y
16671
Citable 3y
3127
Cites/Doc 2y
5.29
Ref/Doc
19.42
Immediate OA
2157 €
Embargoed OA
NPD
Non OA / Submission
0 €
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Best articles by citations
A Landsat Surface Reflectance Dataset for North America, 1990–2000
Road Extraction by Deep Residual U-Net
Deep Learning Classification of Land Cover and Crop Types Using Remote Sensing Data
Composite Kernels for Hyperspectral Image Classification
Unsupervised Change Detection in Satellite Images Using Principal Component Analysis and $k$-Means Clustering
623 Citations View moreSVM- and MRF-Based Method for Accurate Classification of Hyperspectral Images
HybridSN: Exploring 3-D–2-D CNN Feature Hierarchy for Hyperspectral Image Classification
Deep Learning Based Feature Selection for Remote Sensing Scene Classification
Land Surface Temperature Retrieval Methods From Landsat-8 Thermal Infrared Sensor Data
Vehicle Detection in Satellite Images by Hybrid Deep Convolutional Neural Networks
457 Citations View moreA Global Quality Measurement of Pan-Sharpened Multispectral Imagery
A Fast Intensity–Hue–Saturation Fusion Technique With Spectral Adjustment for IKONOS Imagery
Unambiguous SAR Signal Reconstruction From Nonuniform Displaced Phase Center Sampling
Deep Learning Earth Observation Classification Using ImageNet Pretrained Networks
Human Detection and Activity Classification Based on Micro-Doppler Signatures Using Deep Convolutional Neural Networks
Convolutional Neural Network With Data Augmentation for SAR Target Recognition
Similarity-Based Unsupervised Band Selection for Hyperspectral Image Analysis
An Adaptive IHS Pan-Sharpening Method
Classification of Hyperspectral Images by Using Extended Morphological Attribute Profiles and Independent Component Analysis
Hyperspectral Image Compression Using JPEG2000 and Principal Component Analysis
A Two-Dimensional Spectrum for Bistatic SAR Processing Using Series Reversion
Polarimetric SAR Image Classification Using Deep Convolutional Neural Networks
Feature Selection Based on Hybridization of Genetic Algorithm and Particle Swarm Optimization
Boosting the Accuracy of Multispectral Image Pansharpening by Learning a Deep Residual Network