Digital Soil Mapping Soil Mapping Maps soil properties from samples using covariates and spatial validation, producing high-resolution predictions with confidence. Neural Networks Uses CNN/deep models to learn spatial patterns from gridded covariates, improving soil predictions with confidence layers. Stacking Combines multiple ML models (stacking/averaging) to reduce errors and improve stability of soil maps and uncertainty. Extrapolation Tests model generalization across regions and scales, mapping where predictions extrapolate and where uncertainty increases. X-AI Explains why models predict patterns by highlighting key drivers and local effects, improving trust and scientific insight. SOC Maps SOC and carbon stocks with environmental drivers, supporting monitoring, reporting, and targeted climate-smart management. Soil Sensing & Remote Observation Remote Sensing Compares multispectral, hyperspectral, and radar signals to predict soil properties, identifying best sensors and combinations. Soil Moisture Estimates soil moisture/VWC using UAV and satellite features, delivering field-scale maps for variable-rate irrigation. Spectroscopy Predicts soil properties from spectral fingerprints using ML calibration, enabling fast, low-cost soil characterization. Land Degradation & Soil Quality Soil Health Predicts soil health indicators spatially to support management zones, monitoring, and targeted restoration with confidence. Soil Erosion Detects erosion and deposition features from imagery using ML/CNN segmentation, producing high-resolution hotspot maps. Soil Salinity Maps salinity risk and trends using ML with terrain, climate, land use, and remote sensing to guide mitigation. Environmental Applications Dust Pollution Predicts pollutants across space and time using monitoring, meteorology, and covariates, generating exposure maps and hotspots. Heavy Metals Models contamination and exposure drivers to map risk hotspots, guiding sampling, remediation, and public-health interventions. Land Suitability Learns suitability patterns from soil and environmental constraints, producing spatial suitability maps and key limiting factors. Review Papers Synthesizes ML methods across domains, highlighting best practices in validation, explainability, and reproducible workflows.
