ISPRS Journal of Photogrammetry and Remote Sensing

Papers
(The H4-Index of ISPRS Journal of Photogrammetry and Remote Sensing is 67. 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 2020-07-01 to 2024-07-01.)
ArticleCitations
Review on Convolutional Neural Networks (CNN) in vegetation remote sensing753
A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sensing images537
UNetFormer: A UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery291
A deep translation (GAN) based change detection network for optical and SAR remote sensing images213
Improved land cover map of Iran using Sentinel imagery within Google Earth Engine and a novel automatic workflow for land cover classification using migrated training samples204
Cloud removal in Sentinel-2 imagery using a deep residual neural network and SAR-optical data fusion201
FAIR1M: A benchmark dataset for fine-grained object recognition in high-resolution remote sensing imagery197
Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks196
X-ModalNet: A semi-supervised deep cross-modal network for classification of remote sensing data180
Oriented objects as pairs of middle lines163
UAVid: A semantic segmentation dataset for UAV imagery157
Self-attention for raw optical Satellite Time Series Classification156
Multimodal remote sensing benchmark datasets for land cover classification with a shared and specific feature learning model149
Efficient structure from motion for large-scale UAV images: A review and a comparison of SfM tools143
Land-Use/Land-Cover change detection based on a Siamese global learning framework for high spatial resolution remote sensing imagery141
Learning deep semantic segmentation network under multiple weakly-supervised constraints for cross-domain remote sensing image semantic segmentation131
A Global Context-aware and Batch-independent Network for road extraction from VHR satellite imagery130
Remote sensing image segmentation advances: A meta-analysis130
PBNet: Part-based convolutional neural network for complex composite object detection in remote sensing imagery129
Development and application of a new mangrove vegetation index (MVI) for rapid and accurate mangrove mapping128
ABCNet: Attentive bilateral contextual network for efficient semantic segmentation of Fine-Resolution remotely sensed imagery122
UAV in the advent of the twenties: Where we stand and what is next122
Sentinel SAR-optical fusion for crop type mapping using deep learning and Google Earth Engine121
A spatially explicit surface urban heat island database for the United States: Characterization, uncertainties, and possible applications116
HyperLi-Net: A hyper-light deep learning network for high-accurate and high-speed ship detection from synthetic aperture radar imagery112
Detection of banana plants and their major diseases through aerial images and machine learning methods: A case study in DR Congo and Republic of Benin111
Mapping croplands of Europe, Middle East, Russia, and Central Asia using Landsat, Random Forest, and Google Earth Engine110
A practical approach to reconstruct high-quality Landsat NDVI time-series data by gap filling and the Savitzky–Golay filter110
CLNet: Cross-layer convolutional neural network for change detection in optical remote sensing imagery104
Perception and sensing for autonomous vehicles under adverse weather conditions: A survey102
Growing status observation for oil palm trees using Unmanned Aerial Vehicle (UAV) images100
Lidar sheds new light on plant phenomics for plant breeding and management: Recent advances and future prospects96
Identifying floods and flood-affected paddy rice fields in Bangladesh based on Sentinel-1 imagery and Google Earth Engine96
A review of image fusion techniques for pan-sharpening of high-resolution satellite imagery96
Automated tree-crown and height detection in a young forest plantation using mask region-based convolutional neural network (Mask R-CNN)95
A novel deep learning instance segmentation model for automated marine oil spill detection95
From LiDAR point cloud towards digital twin city: Clustering city objects based on Gestalt principles95
SceneNet: Remote sensing scene classification deep learning network using multi-objective neural evolution architecture search94
An attention-fused network for semantic segmentation of very-high-resolution remote sensing imagery93
Robust deep alignment network with remote sensing knowledge graph for zero-shot and generalized zero-shot remote sensing image scene classification92
Land surface phenology as indicator of global terrestrial ecosystem dynamics: A systematic review91
A deep learning framework for matching of SAR and optical imagery90
ChangeMask: Deep multi-task encoder-transformer-decoder architecture for semantic change detection89
FCCDN: Feature constraint network for VHR image change detection87
Parsing very high resolution urban scene images by learning deep ConvNets with edge-aware loss86
Balance learning for ship detection from synthetic aperture radar remote sensing imagery85
Thin cloud removal in optical remote sensing images based on generative adversarial networks and physical model of cloud distortion84
Efficient RTM-based training of machine learning regression algorithms to quantify biophysical & biochemical traits of agricultural crops84
A coarse-to-fine boundary refinement network for building footprint extraction from remote sensing imagery82
Field-scale crop yield prediction using multi-temporal WorldView-3 and PlanetScope satellite data and deep learning80
Exploring multiscale object-based convolutional neural network (multi-OCNN) for remote sensing image classification at high spatial resolution80
An enhanced pixel-based phenological feature for accurate paddy rice mapping with Sentinel-2 imagery in Google Earth Engine80
Automatic 3D building reconstruction from multi-view aerial images with deep learning78
Long-term monitoring of evapotranspiration using the SEBAL algorithm and Google Earth Engine cloud computing77
Developing a machine learning based cotton yield estimation framework using multi-temporal UAS data77
BT-RoadNet: A boundary and topologically-aware neural network for road extraction from high-resolution remote sensing imagery75
Building outline delineation: From aerial images to polygons with an improved end-to-end learning framework74
Land-cover classification of multispectral LiDAR data using CNN with optimized hyper-parameters72
A robust multimodal remote sensing image registration method and system using steerable filters with first- and second-order gradients71
A CNN approach to simultaneously count plants and detect plantation-rows from UAV imagery70
GTP-PNet: A residual learning network based on gradient transformation prior for pansharpening70
See the forest and the trees: Effective machine and deep learning algorithms for wood filtering and tree species classification from terrestrial laser scanning70
MLRSNet: A multi-label high spatial resolution remote sensing dataset for semantic scene understanding69
Estimating crop biomass using leaf area index derived from Landsat 8 and Sentinel-2 data69
Exploring Sentinel-1 and Sentinel-2 diversity for flood inundation mapping using deep learning69
High-resolution triplet network with dynamic multiscale feature for change detection on satellite images69
Airborne LiDAR point cloud classification with global-local graph attention convolution neural network67
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