{"total":24,"rows":[{"id":"2312.05327","title":"Better, Not Just More: Data-Centric Machine Learning for Earth Observation","created":"2023-12-08","cited_by_count":19,"area":null},{"id":"2303.18087","title":"Evaluation Challenges for Geospatial ML","created":"2023-03-31","cited_by_count":10,"area":null},{"id":"2411.14354","title":"Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas","created":"2024-11-21","cited_by_count":6,"area":null},{"id":"2605.26036","title":"CITYREP: A Unified Benchmark for Urban Representations Across Cities, Tasks, and Modalities","created":"2026-05-25","cited_by_count":5,"area":null},{"id":"2104.10922","title":"Continental-scale land cover mapping at 10 m resolution over Europe (ELC10)","created":"2021-04-22","cited_by_count":4,"area":null},{"id":"2201.01869","title":"Earthquake Nowcasting with Deep Learning","created":"2021-12-18","cited_by_count":3,"area":null},{"id":"2505.23980","title":"DeepTopoNet: A Framework for Subglacial Topography Estimation on the Greenland Ice Sheets","created":"2025-05-29","cited_by_count":2,"area":null},{"id":"2203.14673","title":"Using Machine Learning to generate an open-access cropland map from satellite images time series in the Indian Himalayan Region","created":"2022-03-28","cited_by_count":1,"area":null},{"id":"2303.04693","title":"A path in regression Random Forest looking for spatial dependence: a taxonomy and a systematic review","created":"2023-03-08","cited_by_count":1,"area":null},{"id":"2311.11057","title":"Challenges in data-based geospatial modeling for environmental research and practice","created":"2023-11-18","cited_by_count":1,"area":null},{"id":"2404.06978","title":"The CAST package for training and assessment of spatial prediction models in R","created":"2024-04-10","cited_by_count":1,"area":null},{"id":"2509.08571","title":"Improving Greenland Bed Topography Mapping with Uncertainty-Aware Graph Learning on Sparse Radar Data","created":"2025-09-10","cited_by_count":1,"area":null},{"id":"2101.08258","title":"Autocart -- spatially-aware regression trees for ecological and spatial modeling","created":"2021-01-20","cited_by_count":0,"area":null},{"id":"2202.02959","title":"A Machine Learning Approach for Material Type Logging and Chemical Assaying from Autonomous Measure-While-Drilling (MWD) Data","created":"2022-02-07","cited_by_count":0,"area":null},{"id":"2406.01982","title":"Variable importance measure for spatial machine learning models with application to air pollution exposure prediction","created":"2024-06-04","cited_by_count":0,"area":null},{"id":"2503.04300","title":"Enhancing Poverty Targeting with Spatial Machine Learning: An application to Indonesia","created":"2025-03-06","cited_by_count":0,"area":null},{"id":"2602.07681","title":"Mapping Drivers of Greenness: Spatial Variable Selection for MODIS Vegetation Indices","created":"2026-02-07","cited_by_count":0,"area":null},{"id":"2603.08393","title":"Decoupling Distance and Networks: Hybrid Graph Attention-Geostatistical Methods for Spatio-temporal Risk Mapping","created":"2026-03-09","cited_by_count":0,"area":null},{"id":"2604.13882","title":"Evaluating Supervised Machine Learning Models: Principles, Pitfalls, and Metric Selection","created":"2026-04-15","cited_by_count":0,"area":null},{"id":"2607.20592","title":"STeMP: Spatio-Temporal Modelling Protocol","created":"2026-07-22","cited_by_count":0,"area":null},{"id":"2608.21059","title":"The Cost of a Physics Prior Is Bounded by the Ablation Gap","created":"2026-08-21","cited_by_count":0,"area":null},{"id":"2609.13265","title":"Forward-Facing Near-Infrared Adds Little to Colour for Farm-Machinery Traversability: A Site-Disjoint Evaluation of Sensor-Dependent Spatial Leakage","created":"2026-09-07","cited_by_count":0,"area":null},{"id":"2609.28895","title":"GeoDose-CP: Graph-Local Conformal Inference for Continuous-Treatment Earth Observation","created":"2026-09-24","cited_by_count":0,"area":null},{"id":"2610.01204","title":"Autoregressive Drillhole Modelling Under Distribution Shift","created":"2026-10-01","cited_by_count":0,"area":null}],"next_cursor":null}