Geospatial Machine Learning Applications
A reading list
Machine learning is no longer just an analytical tool - it’s becoming the backbone of geospatial intelligence.
From wildfire prediction and groundwater mapping to disease forecasting, carbon estimation, and urban sprawl detection, these papers show how spatial data + ML are reshaping environmental risk assessment, urban analytics, agriculture, and climate science.
If you're working at the intersection of GIS, remote sensing, and AI - this collection of recent research papers is worth bookmarking.
Exploration of Geo-Spatial Data and Machine Learning Algorithms for Robust Wildfire Occurrence Prediction
https://www.nature.com/articles/s41598-025-94002-4Enhancement of Groundwater Resources Quality Prediction Using an Improved DRASTIC Method and Machine Learning
https://www.nature.com/articles/s41598-024-78812-6Remote Sensing-Based Forest Cover Classification Using Machine Learning
https://www.nature.com/articles/s41598-023-50863-1Forest Age Estimation Based on a Machine Learning Pipeline Using Sentinel-2 and Auxiliary Data
https://www.nature.com/articles/s41598-023-49207-wFactors of Acute Respiratory Infection Among Under-Five Children Using Machine Learning Approaches
https://www.nature.com/articles/s41598-024-65620-1SAR Image Integration for Multi-Temporal Wetland Dynamics Analysis Using Machine Learning
https://www.nature.com/articles/s41598-024-76730-1Effects of Non-Landslide Sampling Strategies in Landslide Susceptibility Mapping
https://www.nature.com/articles/s41598-024-57964-5Enhancing Co-Seismic Landslide Susceptibility and Risk Analysis Through Machine Learning
https://www.nature.com/articles/s41598-024-54898-w10-m Scale Chemical Industrial Parks Map Along the Yangtze River Based on Machine Learning
https://www.nature.com/articles/s41597-024-03674-6Geospatial Distribution and Machine Learning Algorithms for Assessing Surface Water Quality in Morocco
https://www.nature.com/articles/s41598-023-47991-zLandscape Conservation and Protected Areas Influence on Social Wellbeing Using Random Forest
https://www.nature.com/articles/s41598-024-61924-4Analysis and Prediction of Infectious Diseases Using Spatial Visualization and Machine Learning
https://www.nature.com/articles/s41598-024-80058-1Annual 30-m Global Grassland Maps (2000–2022) Using Spatiotemporal Machine Learning
https://www.nature.com/articles/s41597-024-04139-6Prediction of Historical Defensive Objects Using Machine Learning
https://www.nature.com/articles/s41598-024-82290-1Future Groundwater Potential Mapping Under Climate Change Using Machine Learning
https://www.nature.com/articles/s41598-024-60560-2Improved CO₂ and Methane Estimation Using Machine Learning with Satellite Observations
https://www.nature.com/articles/s41598-024-84593-9Machine Learning-Based Urban Sprawl Assessment with Multi-Hazard and Environmental-Economic Integration
https://www.nature.com/articles/s41598-024-62001-6Global Soil Respiration Estimation Using Ecological Big Data and Machine Learning
https://www.nature.com/articles/s41598-024-64235-wMachine Learning and Hydrodynamic Proxies for Rapid Tsunami Vulnerability Assessment
https://www.nature.com/articles/s43247-024-01468-7Wheat Crop Genotype Identification Using Multispectral Radiometer Data and Machine Learning
https://www.nature.com/articles/s41598-023-46957-5Geospatial Data for Peer-to-Peer Communication Among Autonomous Vehicles Using Optimized ML Algorithms
https://www.nature.com/articles/s41598-024-71197-6Reproducible Ensemble Machine Learning Approach to Forecast Dengue Outbreaks
https://www.nature.com/articles/s41598-024-52796-9Mapping Soil Suitability for Medicinal Plants Using Machine Learning Methods
https://www.nature.com/articles/s41598-024-54465-3
I am working as we speak: Latest ArcUser open on my desk, with Bill Black’s two books on Transportation and “Transportation Transformation” (E. Simoudis) stacked beside me!
Amazing timing - and I will be reading your book, too!