GIScience & Remote Sensing

Papers
(The H4-Index of GIScience & Remote Sensing is 33. 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 2021-05-01 to 2025-05-01.)
ArticleCitations
Trade-offs among productive-living-ecological lands for facilitating low-carbon and efficient cities: evidences in 30 major Chinese cities from 2015 to 202099
Forest carbon sink in North China increased in recent two decades, but decreased in extreme drought years91
A deep learning approach for automatic mapping of poplar plantations using Sentinel-2 imagery83
Mapping invasive alien plant species with very high spatial resolution and multi-date satellite imagery using object-based and machine learning techniques: A comparative study76
Mapping the tidal marshes of coastal Virginia: a hierarchical transfer learning approach74
Subtidal seagrass and blue carbon mapping at the regional scale: a cloud-native multi-temporal Earth Observation approach69
The use of multisource spatial data for determining the proliferation of stingless bees in Kenya60
Trends, turning points, and driving forces of desertification in global arid land based on the segmental trend method and SHAP model59
Regression-based surface water fraction mapping using a synthetic spectral library for monitoring small water bodies56
MSFTrans: a multi-task frequency-spatial learning transformer for building extraction from high spatial resolution remote sensing images55
Urban building extraction from high-resolution remote sensing imagery based on multi-scale recurrent conditional generative adversarial network52
Evaluating the contribution of Sentinel-2 view and illumination geometry to the accuracy of retrieving essential crop parameters52
A new strategy for improving the accuracy of forest aboveground biomass estimates in an alpine region based on multi-source remote sensing47
AFSNet: attention-guided full-scale feature aggregation network for high-resolution remote sensing image change detection44
Land cover change detection in the Aralkum with multi-source satellite datasets43
A hybrid integrated deep learning model for predicting various air pollutants43
Embedded physical constraints in machine learning to enhance vegetation phenology prediction43
Global de-trending significantly improves the accuracy of XGBoost-based county-level maize and soybean yield prediction in the Midwestern United States43
Remote sensing of terrestrial gross primary productivity: a review of advances in theoretical foundation, key parameters and methods42
Impacts of the world’s largest afforestation program (Three-North Afforestation Program) on desertification control in sandy land of China41
A review of building detection from very high resolution optical remote sensing images41
The use of maximum entropy and ecological niche factor analysis to decrease uncertainties in samples for urban gain models40
Leaf area index and aboveground biomass estimation of an alpine peatland with a UAV multi-sensor approach40
Development of earth observational diagnostic drought prediction model for regional error calibration: A case study on agricultural drought in Kyrgyzstan40
Spatial disparity of urban performance from a scaling perspective: a study of industrial features associated with economy, infrastructure, and innovation39
An optimal multivariate-stratification geographical detector model for revealing the impact of multi-factor combinations on the dependent variable39
An improved change detection method for high-resolution soil moisture mapping in permafrost regions39
Application of deep learning in cloud cover prediction using geostationary satellite images38
Error budget analysis of geocoding and geometric correction for KOMPSAT-5 SAR imagery37
Characterization of spatio-temporal patterns of grassland utilization intensity in the Selinco watershed of the Qinghai-Tibetan Plateau from 2001 to 2019 based on multisource remote sensing and artifi37
Ship detection and classification based on cascaded detection of hull and wake from optical satellite remote sensing imagery36
Strength-weighted flow cluster method considering spatiotemporal contiguity to reveal interregional association patterns34
Cross-comparison of Landsat-8 and Landsat-9 data: a three-level approach based on underfly images33
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