{"total":71,"rows":[{"id":"2306.03831","title":"GEO-Bench: Toward Foundation Models for Earth Monitoring","created":"2023-06-06","cited_by_count":124,"area":null},{"id":"2503.11849","title":"Towards a Unified Copernicus Foundation Model for Earth Vision","created":"2025-03-14","cited_by_count":53,"area":null},{"id":"2306.09424","title":"SSL4EO-L: Datasets and Foundation Models for Landsat Imagery","created":"2023-06-15","cited_by_count":49,"area":null},{"id":"2210.04936","title":"EarthNets: Empowering AI in Earth Observation","created":"2022-10-10","cited_by_count":40,"area":null},{"id":"2503.10845","title":"Panopticon: Advancing Any-Sensor Foundation Models for Earth Observation","created":"2025-03-13","cited_by_count":34,"area":null},{"id":"2405.04285","title":"On the Foundations of Earth and Climate Foundation Models","created":"2024-05-07","cited_by_count":33,"area":null},{"id":"2406.15658","title":"TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learning","created":"2024-06-21","cited_by_count":31,"area":null},{"id":"2312.02199","title":"USat: A Unified Self-Supervised Encoder for Multi-Sensor Satellite Imagery","created":"2023-12-02","cited_by_count":28,"area":null},{"id":"2305.13456","title":"Revisiting pre-trained remote sensing model benchmarks: resizing and normalization matters","created":"2023-05-22","cited_by_count":27,"area":null},{"id":"2503.20563","title":"TerraTorch: The Geospatial Foundation Models Toolkit","created":"2025-03-26","cited_by_count":25,"area":null},{"id":"2207.07189","title":"Current Trends in Deep Learning for Earth Observation: An Open-source Benchmark Arena for Image Classification","created":"2022-07-14","cited_by_count":18,"area":null},{"id":"2310.19231","title":"There Are No Data Like More Data- Datasets for Deep Learning in Earth Observation","created":"2023-10-30","cited_by_count":16,"area":null},{"id":"2402.06994","title":"A Change Detection Reality Check","created":"2024-02-10","cited_by_count":13,"area":null},{"id":"2412.05600","title":"Global and Dense Embeddings of Earth: Major TOM Floating in the Latent Space","created":"2024-12-07","cited_by_count":12,"area":null},{"id":"2605.12678","title":"No One Knows the State of the Art in Geospatial Foundation Models","created":"2026-05-12","cited_by_count":12,"area":null},{"id":"2511.02101","title":"Measuring the Intrinsic Dimension of Earth Representations","created":"2025-11-03","cited_by_count":10,"area":null},{"id":"2202.14000","title":"Resolving label uncertainty with implicit posterior models","created":"2022-02-28","cited_by_count":8,"area":null},{"id":"2201.08789","title":"AiTLAS: Artificial Intelligence Toolbox for Earth Observation","created":"2022-01-21","cited_by_count":7,"area":null},{"id":"2403.06758","title":"EarthLoc: Astronaut Photography Localization by Indexing Earth from Space","created":"2024-03-11","cited_by_count":7,"area":null},{"id":"2504.06962","title":"Efficient Self-Supervised Learning for Earth Observation via Dynamic Dataset Curation","created":"2025-04-09","cited_by_count":7,"area":null},{"id":"2402.00732","title":"MobilityDL: A Review of Deep Learning From Trajectory Data","created":"2024-02-01","cited_by_count":6,"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":"2310.13098","title":"SRAI: Towards Standardization of Geospatial AI","created":"2023-10-19","cited_by_count":5,"area":null},{"id":"2409.09451","title":"On the Generalizability of Foundation Models for Crop Type Mapping","created":"2024-09-14","cited_by_count":5,"area":null},{"id":"2505.14951","title":"MultiMAE Meets Earth Observation: Pre-training Multi-modal Multi-task Masked Autoencoders for Earth Observation Tasks","created":"2025-05-20","cited_by_count":5,"area":null},{"id":"2601.13134","title":"Earth Embeddings as Products: Taxonomy, Ecosystem, and Standardized Access","created":"2026-01-19","cited_by_count":5,"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":"2202.13251","title":"Supervising Remote Sensing Change Detection Models with 3D Surface Semantics","created":"2022-02-26","cited_by_count":4,"area":null},{"id":"2310.11029","title":"Core Building Blocks: Next Gen Geo Spatial GPT Application","created":"2023-10-17","cited_by_count":4,"area":null},{"id":"2408.02348","title":"Earth System Data Cubes: Avenues for advancing Earth system research","created":"2024-08-05","cited_by_count":3,"area":null},{"id":"2510.05879","title":"OBSR: Open Benchmark for Spatial Representations","created":"2025-10-07","cited_by_count":3,"area":null},{"id":"2510.22964","title":"Survey of Multimodal Geospatial Foundation Models: Techniques, Applications, and Challenges","created":"2025-10-27","cited_by_count":3,"area":null},{"id":"2404.08325","title":"Uncertainty Aware Tropical Cyclone Wind Speed Estimation from Satellite Data","created":"2024-04-12","cited_by_count":2,"area":null},{"id":"2404.13911","title":"GlobalBuildingMap -- Unveiling the Mystery of Global Buildings","created":"2024-04-22","cited_by_count":2,"area":null},{"id":"2502.15032","title":"GeoAggregator: An Efficient Transformer Model for Geo-Spatial Tabular Data","created":"2025-02-20","cited_by_count":2,"area":null},{"id":"2503.12843","title":"Towards Scalable Foundation Model for Multi-modal and Hyperspectral Geospatial Data","created":"2025-03-17","cited_by_count":2,"area":null},{"id":"2509.03749","title":"Mapping on a Budget: Optimizing Spatial Data Collection for ML","created":"2025-09-03","cited_by_count":2,"area":null},{"id":"2602.00117","title":"IC-EO: Interpretable Code-based assistant for Earth Observation","created":"2026-01-27","cited_by_count":2,"area":null},{"id":"2603.02386","title":"Advancing Earth Observation Through Machine Learning: A TorchGeo Tutorial","created":"2026-03-02","cited_by_count":2,"area":null},{"id":"2603.23408","title":"GeoSANE: Learning Geospatial Representations from Models, Not Data","created":"2026-03-24","cited_by_count":2,"area":null},{"id":"2608.06612","title":"SLED: Scalable Location Encoding via Distillation","created":"2026-08-06","cited_by_count":2,"area":null},{"id":"2401.06762","title":"Seeing the roads through the trees: A benchmark for modeling spatial dependencies with aerial imagery","created":"2024-01-12","cited_by_count":1,"area":null},{"id":"2404.11762","title":"IrrNet: Advancing Irrigation Mapping with Incremental Patch Size Training on Remote Sensing Imagery","created":"2024-04-17","cited_by_count":1,"area":null},{"id":"2407.06337","title":"GeoWATCH for Detecting Heavy Construction in Heterogeneous Time Series of Satellite Images","created":"2024-07-08","cited_by_count":1,"area":null},{"id":"2407.18128","title":"Estimating Earthquake Magnitude in Sentinel-1 Imagery via Ranking","created":"2024-07-25","cited_by_count":1,"area":null},{"id":"2409.17363","title":"Improving satellite imagery segmentation using multiple Sentinel-2 revisits","created":"2024-09-25","cited_by_count":1,"area":null},{"id":"2502.07003","title":"AstroLoc: Robust Space to Ground Image Localizer","created":"2025-02-10","cited_by_count":1,"area":null},{"id":"2603.02522","title":"NeighborMAE: Exploiting Spatial Dependencies between Neighboring Earth Observation Images in Masked Autoencoders Pretraining","created":"2026-03-03","cited_by_count":1,"area":null},{"id":"2603.10658","title":"How to Embed Matters: Evaluation of EO Embedding Design Choices","created":"2026-03-11","cited_by_count":1,"area":null},{"id":"2605.01250","title":"EO-Gym: A Multimodal, Interactive Environment for Earth Observation Agents","created":"2026-05-02","cited_by_count":1,"area":null},{"id":"2605.18911","title":"Does Your Wildfire Prediction Model Actually Work, or Just Score Well?","created":"2026-05-14","cited_by_count":1,"area":null},{"id":"2606.24997","title":"What's in an Earth Embedding? An Explainability Analysis of Location Encoders","created":"2026-06-23","cited_by_count":1,"area":null},{"id":"2607.24532","title":"From Machine Learning to Large-Scale EO Products: Best Practices for Making Maps","created":"2026-07-27","cited_by_count":1,"area":null},{"id":"2301.09620","title":"Tracking the industrial growth of modern China with high-resolution panchromatic imagery: A sequential convolutional approach","created":"2023-01-23","cited_by_count":0,"area":null},{"id":"2306.00823","title":"Geo-Tiles for Semantic Segmentation of Earth Observation Imagery","created":"2023-06-01","cited_by_count":0,"area":null},{"id":"2309.05490","title":"Learning Semantic Segmentation with Query Points Supervision on Aerial Images","created":"2023-09-11","cited_by_count":0,"area":null},{"id":"2412.00777","title":"Local vs. Global: Local Land-Use and Land-Cover Models Deliver Higher Quality Maps","created":"2024-12-01","cited_by_count":0,"area":null},{"id":"2508.00627","title":"IAMAP: Unlocking Deep Learning in QGIS for non-coders and limited computing resources","created":"2025-08-01","cited_by_count":0,"area":null},{"id":"2509.18182","title":"AI-Derived Structural Building Intelligence for Urban Resilience: An Application in Saint Vincent and the Grenadines","created":"2025-09-18","cited_by_count":0,"area":null},{"id":"2510.02572","title":"Geospatial Machine Learning Libraries","created":"2025-10-02","cited_by_count":0,"area":null},{"id":"2510.16814","title":"Needles in the Landscape: Semi-Supervised Pseudolabeling for Archaeological Site Discovery under Label Scarcity","created":"2025-10-19","cited_by_count":0,"area":null},{"id":"2511.17134","title":"Four decades of circumpolar super-resolved satellite land surface temperature data","created":"2025-11-21","cited_by_count":0,"area":null},{"id":"2511.21523","title":"EoS-FM: Can an Ensemble of Specialist Models act as a Generalist Feature Extractor?","created":"2025-11-26","cited_by_count":0,"area":null},{"id":"2601.01781","title":"Subimage Overlap Prediction: Task-Aligned Self-Supervised Pretraining For Semantic Segmentation In Remote Sensing Imagery","created":"2026-01-05","cited_by_count":0,"area":null},{"id":"2602.00331","title":"Prototype-based Explainable Neural Networks with Channel-specific Reasoning for Geospatial Learning Tasks","created":"2026-01-30","cited_by_count":0,"area":null},{"id":"2607.11838","title":"HASTE: A Platform for Rapid Post-Disaster Building Damage Assessment","created":"2026-07-13","cited_by_count":0,"area":null},{"id":"2608.03410","title":"Earth Embeddings","created":"2026-08-04","cited_by_count":0,"area":null},{"id":"2608.21567","title":"Quantifying geographic domain shift to decouple the geospatial transferability of human mobility flow generation models","created":"2026-08-21","cited_by_count":0,"area":null},{"id":"2609.13182","title":"Land Art as a Big-Data Climate Sensor","created":"2026-07-29","cited_by_count":0,"area":null},{"id":"2609.13654","title":"Multimodal Foundation Models Adaptation based on Domain-Aware Relaxed Orthogonal Subspace for Remote Sensing","created":"2026-09-12","cited_by_count":0,"area":null},{"id":"2609.22379","title":"MarsRecon: Self-Supervised and Multimodal Surface Representations for Mars","created":"2026-09-17","cited_by_count":0,"area":null}],"next_cursor":null}