Geocarto International

(The H4-Index of Geocarto International 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.)
Flash-flood susceptibility mapping based on XGBoost, random forest and boosted regression trees117
An ensemble architecture of deep convolutional Segnet and Unet networks for building semantic segmentation from high-resolution aerial images73
Ensemble models of GLM, FDA, MARS, and RF for flood and erosion susceptibility mapping: a priority assessment of sub-basins71
Comparative analysis of gradient boosting algorithms for landslide susceptibility mapping65
A new high resolution filter for source edge detection of potential field data64
An interpretable model for the susceptibility of rainfall-induced shallow landslides based on SHAP and XGBoost62
Decision tree based ensemble machine learning approaches for landslide susceptibility mapping58
Evaluation efficiency of hybrid deep learning algorithms with neural network decision tree and boosting methods for predicting groundwater potential58
Novel ensemble machine learning models in flood susceptibility mapping55
Land use/land cover and change detection mapping in Rahuri watershed area (MS), India using the google earth engine and machine learning approach50
Examining LightGBM and CatBoost models for wadi flash flood susceptibility prediction48
Assessing spatio-temporal mapping and monitoring of climatic variability using SPEI and RF machine learning models43
Distribution, exposure, and human health risk analysis of heavy metals in drinking groundwater of Ghayen County, Iran42
Evaluating urban environment quality (UEQ) for Class-I Indian city: an integrated RS-GIS based exploratory spatial analysis42
Assessment of PTEs in water resources by integrating HHRISK code, water quality indices, multivariate statistics, and ANNs42
Rainfall induced landslide susceptibility mapping using novel hybrid soft computing methods based on multi-layer perceptron neural network classifier41
Flash-flood hazard susceptibility mapping in Kangsabati River Basin, India39
ASTER and WorldView-3 satellite data for mapping lithology and alteration minerals associated with Pb-Zn mineralization37
Annual assessment on the relationship between land surface temperature and six remote sensing indices using landsat data from 1988 to 201936
Edge detection of potential field sources using the softsign function36
Artificial neural network and sensitivity analysis in the landslide susceptibility mapping of Idukki district, India35
A GIS-based flood risk mapping of Assam, India, using the MCDA-AHP approach at the regional and administrative level33
Extent of anthropogenic influence on groundwater quality and human health-related risks: an integrated assessment based on selected physicochemical characteristics31
Detailed and automated classification of land use/land cover using machine learning algorithms in Google Earth Engine31
Multi-satellite precipitation products for meteorological drought assessment and forecasting in Central India30
Toward the development of deep learning analyses for snow avalanche releases in mountain regions30
Prediction of suspended sediment concentration using hybrid SVM-WOA approaches29
Crop type identification and spatial mapping using Sentinel-2 satellite data with focus on field-level information29
Deep learning and boosting framework for piping erosion susceptibility modeling: spatial evaluation of agricultural areas in the semi-arid region28