GIScience & Remote Sensing

(The H4-Index of GIScience & Remote Sensing is 28. 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.)
A large-scale change monitoring of wetlands using time series Landsat imagery on Google Earth Engine: a case study in Newfoundland93
Application of machine learning techniques in groundwater potential mapping along the west coast of India76
Google Earth Engine for large-scale land use and land cover mapping: an object-based classification approach using spectral, textural and topographical factors71
A comparative analysis of trajectory similarity measures59
A review of building detection from very high resolution optical remote sensing images58
Improvement of Mangrove Soil Carbon Stocks Estimation in North Vietnam Using Sentinel-2 Data and Machine Learning Approach54
Generating annual high resolution land cover products for 28 metropolises in China based on a deep super-resolution mapping network using Landsat imagery53
Interpretation and sensitivity analysis of the InSAR line of sight displacements in landslide measurements50
Use of Local Climate Zones to investigate surface urban heat islands in Texas48
Urban tree species classification using UAV-based multi-sensor data fusion and machine learning44
Quantifying diurnal and seasonal variation of surface urban heat island intensity and its associated determinants across different climatic zones over Indian cities41
FROM-GLC Plus: toward near real-time and multi-resolution land cover mapping39
A stacking ensemble algorithm for improving the biases of forest aboveground biomass estimations from multiple remotely sensed datasets37
Factors affecting relative height and ground elevation estimations of GEDI among forest types across the conterminous USA36
RoadVecNet: a new approach for simultaneous road network segmentation and vectorization from aerial and google earth imagery in a complex urban set-up36
A deep learning model using geostationary satellite data for forest fire detection with reduced detection latency36
Quantitatively distinguishing the impact of climate change and human activities on vegetation in mainland China with the improved residual method36
Recent land deformation detected by Sentinel-1A InSAR data (2016–2020) over Hanoi, Vietnam, and the relationship with groundwater level change34
A workflow based on Sentinel-1 SAR data and open-source algorithms for unsupervised burned area detection in Mediterranean ecosystems33
Improving wetland cover classification using artificial neural networks with ensemble techniques32
Oil spill detection from Synthetic Aperture Radar Earth observations: a meta-analysis and comprehensive review31
Aboveground biomass mapping by integrating ICESat-2, SENTINEL-1, SENTINEL-2, ALOS2/PALSAR2, and topographic information in Mediterranean forests31
Exploring the advantages of the maximum entropy model in calibrating cellular automata for urban growth simulation: a comparative study of four methods30
Offshore Island Connection Line: A new perspective of coastal urban development boundary simulation and multi-scenario prediction30
A new type of dual-scale neighborhood based on vectorization for cellular automata models30
A comparison of the integrated fuzzy object-based deep learning approach and three machine learning techniques for land use/cover change monitoring and environmental impacts assessment29
Driving forces of grassland vegetation changes in Chen Barag Banner, Inner Mongolia29
Effect of landscape pattern and spatial configuration of vegetation patches on urban warming and cooling in Harare metropolitan city, Zimbabwe28
Simulating mixed land-use change under multi-label concept by integrating a convolutional neural network and cellular automata: a case study of Huizhou, China28