OOIR: Observatory of International Research

Papers

(The H4-Index of ISPRS Journal of Photogrammetry and Remote Sensing is 66. 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 2020-10-01 to 2024-10-01.)

Article	Citations
Review on Convolutional Neural Networks (CNN) in vegetation remote sensing	827
UNetFormer: A UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery	359
A deep translation (GAN) based change detection network for optical and SAR remote sensing images	229
FAIR1M: A benchmark dataset for fine-grained object recognition in high-resolution remote sensing imagery	224
Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks	213
Self-attention for raw optical Satellite Time Series Classification	181
Oriented objects as pairs of middle lines	174
Multimodal remote sensing benchmark datasets for land cover classification with a shared and specific feature learning model	172
Land-Use/Land-Cover change detection based on a Siamese global learning framework for high spatial resolution remote sensing imagery	162
ABCNet: Attentive bilateral contextual network for efficient semantic segmentation of Fine-Resolution remotely sensed imagery	150
A Global Context-aware and Batch-independent Network for road extraction from VHR satellite imagery	145
Learning deep semantic segmentation network under multiple weakly-supervised constraints for cross-domain remote sensing image semantic segmentation	142
Remote sensing image segmentation advances: A meta-analysis	142
Perception and sensing for autonomous vehicles under adverse weather conditions: A survey	139
UAV in the advent of the twenties: Where we stand and what is next	133
Sentinel SAR-optical fusion for crop type mapping using deep learning and Google Earth Engine	133
PBNet: Part-based convolutional neural network for complex composite object detection in remote sensing imagery	131
A practical approach to reconstruct high-quality Landsat NDVI time-series data by gap filling and the Savitzky–Golay filter	128
A spatially explicit surface urban heat island database for the United States: Characterization, uncertainties, and possible applications	125
CLNet: Cross-layer convolutional neural network for change detection in optical remote sensing imagery	119
Detection of banana plants and their major diseases through aerial images and machine learning methods: A case study in DR Congo and Republic of Benin	119
ChangeMask: Deep multi-task encoder-transformer-decoder architecture for semantic change detection	116
Lidar sheds new light on plant phenomics for plant breeding and management: Recent advances and future prospects	109
Growing status observation for oil palm trees using Unmanned Aerial Vehicle (UAV) images	109
A review of image fusion techniques for pan-sharpening of high-resolution satellite imagery	108

FCCDN: Feature constraint network for VHR image change detection	107
An attention-fused network for semantic segmentation of very-high-resolution remote sensing imagery	106
Automated tree-crown and height detection in a young forest plantation using mask region-based convolutional neural network (Mask R-CNN)	105
SceneNet: Remote sensing scene classification deep learning network using multi-objective neural evolution architecture search	103
Land surface phenology as indicator of global terrestrial ecosystem dynamics: A systematic review	101
Robust deep alignment network with remote sensing knowledge graph for zero-shot and generalized zero-shot remote sensing image scene classification	98
Balance learning for ship detection from synthetic aperture radar remote sensing imagery	97
A deep learning framework for matching of SAR and optical imagery	94
Parsing very high resolution urban scene images by learning deep ConvNets with edge-aware loss	93
A coarse-to-fine boundary refinement network for building footprint extraction from remote sensing imagery	92
Field-scale crop yield prediction using multi-temporal WorldView-3 and PlanetScope satellite data and deep learning	92
Efficient RTM-based training of machine learning regression algorithms to quantify biophysical & biochemical traits of agricultural crops	90
An enhanced pixel-based phenological feature for accurate paddy rice mapping with Sentinel-2 imagery in Google Earth Engine	88
Exploring multiscale object-based convolutional neural network (multi-OCNN) for remote sensing image classification at high spatial resolution	87
Long-term monitoring of evapotranspiration using the SEBAL algorithm and Google Earth Engine cloud computing	85
Automatic 3D building reconstruction from multi-view aerial images with deep learning	84
Exploring Sentinel-1 and Sentinel-2 diversity for flood inundation mapping using deep learning	83
Developing a machine learning based cotton yield estimation framework using multi-temporal UAS data	82
See the forest and the trees: Effective machine and deep learning algorithms for wood filtering and tree species classification from terrestrial laser scanning	82
Enhanced mangrove vegetation index based on hyperspectral images for mapping mangrove	81
Building outline delineation: From aerial images to polygons with an improved end-to-end learning framework	81
BT-RoadNet: A boundary and topologically-aware neural network for road extraction from high-resolution remote sensing imagery	80
CMGFNet: A deep cross-modal gated fusion network for building extraction from very high-resolution remote sensing images	79
A robust multimodal remote sensing image registration method and system using steerable filters with first- and second-order gradients	79
Active fire detection in Landsat-8 imagery: A large-scale dataset and a deep-learning study	79
Detecting tiny objects in aerial images: A normalized Wasserstein distance and a new benchmark	78
GTP-PNet: A residual learning network based on gradient transformation prior for pansharpening	76
Measuring residents’ perceptions of city streets to inform better street planning through deep learning and space syntax	75
A CNN approach to simultaneously count plants and detect plantation-rows from UAV imagery	75
High-resolution triplet network with dynamic multiscale feature for change detection on satellite images	75
MLRSNet: A multi-label high spatial resolution remote sensing dataset for semantic scene understanding	75
Estimating crop biomass using leaf area index derived from Landsat 8 and Sentinel-2 data	74
DKDFN: Domain Knowledge-Guided deep collaborative fusion network for multimodal unitemporal remote sensing land cover classification	72
Airborne LiDAR point cloud classification with global-local graph attention convolution neural network	70
Large-scale rice mapping under different years based on time-series Sentinel-1 images using deep semantic segmentation model	70
Land use mapping using Sentinel-1 and Sentinel-2 time series in a heterogeneous landscape in Niger, Sahel	69
Learning from multimodal and multitemporal earth observation data for building damage mapping	69
Cloud and cloud shadow detection for optical satellite imagery: Features, algorithms, validation, and prospects	69
Mapping coastal salt marshes in China using time series of Sentinel-1 SAR	67
Is field-measured tree height as reliable as believed – Part II, A comparison study of tree height estimates from conventional field measurement and low-cost close-range remote sensing in a deciduous	67
Mapping trees along urban street networks with deep learning and street-level imagery	67
Estimating daily full-coverage near surface O3, CO, and NO2 concentrations at a high spatial resolution over China based on S5P-TROPOMI and GEOS-FP	66