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| 1. **Global Urban Land Uses (10 m) with Sentinel‑2 + POI prompting (2025)** |
| Global 10 m urban land-use dataset with pixel-level multi-class masks, produced from Sentinel‑2 imagery and OSM POI prompts. |
| Paper: https://www.sciencedirect.com/science/article/abs/pii/S0034425725002287 |
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| 2. **Global Urban Open Space for 169 Megacities (1.19 m) (2025)** |
| High-resolution (1.19 m) semantic mapping of urban open space across 169 megacities with pixel-level classes (parks/green space, sports, transportation space, water, background). |
| Paper: https://www.nature.com/articles/s41597-025-04924-x |
| Code: https://github.com/RunyuFan/OpenspaceGlobal |
| Data: https://www.scidb.cn/en/detail?dataSetId=ddc0dd716dd740f0ae74a113e207bb64 |
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| 3. **GURS: Global Urban and Rural Settlement Dataset (100 m, 2000–2020) (2024)** |
| Global 100 m settlement product distinguishing urban vs rural areas for multiple years (GeoTIFF layers). |
| Paper: https://www.nature.com/articles/s41597-024-04195-y |
| Code: https://github.com/liuzht7-github/GURS.git |
| Data: https://zenodo.org/records/11160893 |
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| 4. **Multi-level Street-Block Divisions for 985 Cities Worldwide (2025)** |
| Global street-block division vectors for 985 cities with a uniform division rationale for consistent cross-city analysis. |
| Paper: https://www.nature.com/articles/s41597-025-04704-7 |
| Data: https://figshare.com/articles/dataset/MSDCW_Dataset_and_Code/26021314 |
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| 5. **CMAB: Multi-Attribute Building Dataset of China (2025)** |
| Nationwide instance-level building dataset for China with rich attributes (e.g., rooftop, height, structure, function, style, age, quality). |
| Paper: https://www.nature.com/articles/s41597-025-04730-5 |
| Data: https://figshare.com/articles/dataset/CMAB-The_World_s_First_National-Scale_Multi-Attribute_Building_Dataset/27992417/2 |
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| 6. **3D-GloBFP: Global 3D Building Footprints (2024)** |
| Global building footprint resource providing 3D/height-related building information (Zenodo release). |
| Paper: https://essd.copernicus.org/articles/16/5357/2024/essd-16-5357-2024-discussion.html |
| Data: https://doi.org/10.5281/zenodo.11319912 |
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| 7. **Google Open Buildings Temporal v1 (GEE)** |
| Temporal version of Google Open Buildings footprints (polygons + height/attributes) accessible via Google Earth Engine (see reference link). |
| Reference: https://mp.weixin.qq.com/s/5zM2lQJJ_5GomoKjOAejvw |
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| 8. **Google Open Buildings v3 (GEE)** |
| Global building footprint polygons (vector outlines), commonly accessed via Google Earth Engine (see reference link). |
| Reference: https://mp.weixin.qq.com/s/5zM2lQJJ_5GomoKjOAejvw |
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| 9. **Global Photovoltaic (PV) Solar Panel Dataset (20 m, 2019–2022) (2025)** |
| Annual global PV mapping product at 20 m resolution (TIFF), with validation vectors and additional annotated samples/original imagery. |
| Paper: https://www.nature.com/articles/s41597-025-04985-y |
| Data (Zenodo): https://doi.org/10.5281/zenodo.10684793 |
| GEE App: https://cxh1216.users.earthengine.app/view/solarpv-bnu |
| Validation: https://doi.org/10.5281/zenodo.14348427 |
| Samples/Images: https://doi.org/10.5281/zenodo.14922538 |
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| 10. **Great Britain Primary Substations + Household Heating (2024)** |
| GB primary substation dataset (location/capacity/demand/parent nodes) integrated with household heating types from census data. |
| Paper: https://www.sciencedirect.com/science/article/pii/S2352340924004529 |
| Code: https://github.com/HDRah/Data-PS-GB |
| Data: https://zenodo.org/records/10866260 |
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| 11. **GloHydroRes32: Global Hydropower Plants + Reservoirs (2025)** |
| Global tabular dataset combining open hydropower plant and reservoir sources (capacity, dam/reservoir attributes such as height, depth, area, volume). |
| Paper: https://www.nature.com/articles/s41597-025-04975-0 |
| Code: https://github.com/SustainableWaterSystems/GloHydroRes/tree/main |
| Data: https://zenodo.org/records/14526360 |
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| 12. **China 1 km Monthly Mean Temperature (1901–2023)** |
| China-wide gridded monthly mean temperature dataset (~1 km, NetCDF), downscaled from global climate datasets and validated with independent stations. |
| Data: https://data.tpdc.ac.cn/zh-hans/data/71ab4677-b66c-4fd1-a004-b2a541c4d5bf/ |
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| 13. **TerraClimate: Monthly Climate & Climatic Water Balance (1958–2024) (GEE)** |
| Global monthly climate and water-balance dataset (temperature, precipitation, radiation, wind, PET, runoff, soil moisture, etc.) available in Google Earth Engine. |
| GEE Catalog: https://developers.google.com/earth-engine/datasets/catalog/IDAHO_EPSCOR_TERRACLIMATE?hl=zh-cn |
| Reference: https://mp.weixin.qq.com/s/siDwbNtzyDZxOTTgu2WS5w |
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| 14. **China Forest AGB Time Series (30 m, 1985–2023) (Preprint)** |
| Annual 30 m aboveground biomass (AGB) mapping time series for China; accessible via a GEE script and Zenodo releases split by period. |
| Preprint: https://essd.copernicus.org/preprints/essd-2025-96/ |
| GEE Script: https://code.earthengine.google.com/4f8ad8d32ddb84e826e941a95f31f9be |
| Zenodo (Parts): |
| - https://doi.org/10.5281/zenodo.12620984 |
| - https://doi.org/10.5281/zenodo.12637101 |
| - https://doi.org/10.5281/zenodo.12655492 |
| - https://doi.org/10.5281/zenodo.12658255 |
| - https://doi.org/10.5281/zenodo.12742210 |
| - https://doi.org/10.5281/zenodo.12747329 |
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| 15. **GEDTM30: Global Ensemble Digital Terrain Model (30 m) (Preprint)** |
| Global 30 m terrain model fused from ICESat‑2, GEDI, and multi-source inputs; also provides derived land-surface/topographic parameters at multiple scales. |
| Preprint: https://www.researchsquare.com/article/rs-6280607/v1 |
| Code/Data: https://github.com/openlandmap/GEDTM30 |
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| 16. **Main Grain Land (MGL) Changes in China (30 m, 1985–2020) (2024)** |
| 30 m change-mapping dataset for China’s main grain land from 1985–2020, supporting crop distribution and land-change analysis. |
| Paper: https://www.nature.com/articles/s41597-024-04292-y |
| Data: https://doi.org/10.6084/m9.figshare.26212643.v2 |
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| 17. **FloodCastBench (2025)** |
| Large-scale dataset and foundation-model benchmark for flood modeling/forecasting; includes code to reproduce the dataset. |
| Paper: https://www.nature.com/articles/s41597-025-04725-2 |
| Code: https://github.com/HydroPML/FloodCastBench |
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| 18. **HydroRIVERS (HydroSHEDS)** |
| Global vector river network dataset widely used in hydrological and watershed analyses. |
| Product: https://www.hydrosheds.org/products/hydrorivers |
| Reference (Chinese): https://mp.weixin.qq.com/s/VZkdlHZB107EfE22QXKkuA |
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| 19. **Global Concurrent Hazards Inventory (1981–2020)** |
| Global inventory and hotspot analysis of concurrent hazards compiled from multiple event databases (earthquake, storm, landslide, volcano, wildfire, flood). |
| Paper: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2024EF004490 |
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| 20. **International Migration Flows (online-data derived) (2025)** |
| Dataset estimating global international migration flows using online data signals; published on HDX. |
| Paper: https://www.pnas.org/doi/10.1073/pnas.2409418122 |
| Data: https://data.humdata.org/dataset/international-migration-flows |
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| 21. **EarthView (2017–2022; ~15 TB) (WACV 2025)** |
| Large-scale multi-modal remote sensing dataset for self-supervised learning and foundation-model pretraining (hosted on Hugging Face). |
| Paper: https://openaccess.thecvf.com/content/WACV2025W/CV4EO/papers/Velazquez_EarthView_A_Large_Scale_Remote_Sensing_Dataset_for_Self-Supervision_WACVW_2025_paper.pdf?utm_source=chatgpt.com |
| Data: https://huggingface.co/datasets/satellogic/EarthView |
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| 22. **Falcon: Remote Sensing Vision-Language Foundation Model (Preprint)** |
| Open vision-language foundation model for remote sensing with released code. |
| Paper: https://arxiv.org/abs/2503.11070 |
| Code: https://github.com/tianhuilab/falcon |
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| 23. **Text2Earth (Remote Sensing Text-to-Image Generation) (2025)** |
| Global-scale dataset and foundation model for text-driven remote sensing image generation. |
| Paper: https://ieeexplore.ieee.org/document/10988859 |
| Project: https://chen-yang-liu.github.io/Text2Earth/ |
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| 24. **MMM-RS (NeurIPS 2024) Text-to-Image Benchmark** |
| Multi-modal, multi-GSD, multi-scene remote sensing dataset and benchmark for text-to-image generation. |
| Paper: https://arxiv.org/abs/2410.22362 |
| Dataset/Repo: https://github.com/ljl5261/MMM-RS |
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| 25. **VRSBench (2024)** |
| Versatile vision-language benchmark dataset for remote sensing image understanding (data/code via project page). |
| Paper: https://arxiv.org/abs/2406.12384 |
| Project: https://vrsbench.github.io |
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| 26. **UrBench (AAAI 2025)** |
| Benchmark for evaluating large multimodal models in multi-view urban scenario understanding. |
| Paper: https://arxiv.org/abs/2408.17267 |
| Project: https://opendatalab.github.io/UrBench/ |
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| 27. **RSTeller (Remote Sensing Captioning / VLM Scaling)** |
| Resource for scaling remote sensing vision-language modeling using rich linguistic semantics derived from open data and LLMs. |
| Paper: https://arxiv.org/abs/2408.14744 |
| Code: https://github.com/SlytherinGe/RSTeller |
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| 28. **GlobalGeoTree (Tree Species; Vision-Language) (Preprint)** |
| Multi-granular vision-language dataset for global tree species classification (curated from sources such as GBIF); released on GitHub and Hugging Face. |
| Paper: https://arxiv.org/pdf/2505.12513 |
| Code: https://github.com/MUYang99/GlobalGeoTree |
| Data (HF): https://huggingface.co/datasets/yann111/GlobalGeoTree |
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| 29. **EarthDial (CVPR 2025)** |
| Project for interactive dialogue over multi-sensory Earth observations (vision-language style). |
| Repo: https://github.com/hiyamdebary/EarthDial |
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| 30. **EEG + Eye-Tracking Dataset for Remote Sensing Object Detection (2025)** |
| Human experiment dataset with simultaneous EEG and eye-tracking collected during remote sensing object detection tasks; includes code for modeling/validation. |
| Paper: https://www.nature.com/articles/s41597-025-04995-w |
| Code (classification): https://github.com/Bing-1997/EEGET_RSOD/tree/main/eegnet |
| Code (validation): https://github.com/Bing-1997/EEGET_RSOD |
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| 31. **MUST: Multispectral UAV Single Object Tracking (CVPR 2025)** |
| Multispectral UAV single-object tracking dataset and unified framework for aerial/remote sensing tracking tasks. |
| Paper: https://arxiv.org/abs/2503.17699 |
| Code: https://github.com/q2479036243/MUST-Multispectral-UAV-Single-Object-Tracking |
| ``` |
