Install
openclaw skills install @ruiduobao/geoskill-smart-city-digital-twinMulti-source data fusion to build 3D scene configuration and API interface descriptions for a city digital twin
openclaw skills install @ruiduobao/geoskill-smart-city-digital-twinFuses multi-source geospatial data (DEM/DSM/building height) into a 3D scene configuration and API interface description for a city digital twin, consumable by 3D engines such as Cesium / three.js.
Building height is derived from DSM − DEM, footprints are extracted via connected-component analysis and extruded into LOD1 box blocks; a scene configuration with a unified coordinate system, scene bbox, tiling scheme, and LOD distance thresholds is generated; an OpenAPI-style list of REST endpoints (tile / building / scene metadata, etc.) is produced; and a fusion completeness check covering layer coverage and height consistency is performed.
pip install 'numpy' 'rasterio' 'geopandas' 'shapely' 'scipy'
python geoskill-smart-city-digital-twin.py --bbox 116.0 39.0 117.0 40.0 [other parameters]
python geoskill-smart-city-digital-twin.py --bbox 116 39 117 40 --synthetic --output-dir ./out
python geoskill-smart-city-digital-twin.py --input city.tif --output-dir ./out
python geoskill-smart-city-digital-twin.py --input city.tif --format scene --output-dir ./out
python geoskill-smart-city-digital-twin.py --input city.tif --format api --base-url https://twin.city.gov/api/v1 --output-dir ./out
python geoskill-smart-city-digital-twin.py --input city.tif --height-threshold 5 --lod-levels 5 --output-dir ./out
| File | Format | Description |
|---|---|---|
building_height.tif | GeoTIFF | Building / feature height (DSM−DEM) |
buildings_3d.geojson | GeoJSON | LOD1 building blocks (with height / number of floors, format=scene/both) |
scene_config.json | JSON | 3D scene configuration (CRS/bbox/layers/LOD/tiles) |
api_spec.json | JSON | OpenAPI-style endpoint list (format=api/both) |
twin_report.json | JSON | Fusion completeness report |
output-manifest.json | JSON | Run manifest |
A multi-band GeoTIFF with band order DEM / DSM, or --synthetic to generate physically consistent simulated data (fully offline).
--synthetic mode requires no network at all.MIT
把多源地理空间数据(DEM/DSM/建筑高度)融合为城市数字孪生的 3D 场景配置与 API 接口描述,供 Cesium / three.js 等三维引擎消费。
由 DSM − DEM 得建筑高度,连通域提取足迹并挤出为 LOD1 长方体体块;生成统一坐标系、场景 bbox、瓦片方案、LOD 距离阈值的场景配置;并以 OpenAPI 风格输出瓦片/建筑/场景元数据等 REST 端点清单;同时做图层覆盖率与高度一致性的融合完整性校验。
pip install 'numpy' 'rasterio' 'geopandas' 'shapely' 'scipy'
python geoskill-smart-city-digital-twin.py --bbox 116.0 39.0 117.0 40.0 [其他参数]
python geoskill-smart-city-digital-twin.py --bbox 116 39 117 40 --synthetic --output-dir ./out
python geoskill-smart-city-digital-twin.py --input city.tif --output-dir ./out
python geoskill-smart-city-digital-twin.py --input city.tif --format scene --output-dir ./out
python geoskill-smart-city-digital-twin.py --input city.tif --format api --base-url https://twin.city.gov/api/v1 --output-dir ./out
python geoskill-smart-city-digital-twin.py --input city.tif --height-threshold 5 --lod-levels 5 --output-dir ./out
| 文件 | 格式 | 说明 |
|---|---|---|
building_height.tif | GeoTIFF | 建筑/地物高度(DSM−DEM) |
buildings_3d.geojson | GeoJSON | LOD1 建筑体块(含高度/层数,format=scene/both) |
scene_config.json | JSON | 3D 场景配置(CRS/bbox/图层/LOD/瓦片) |
api_spec.json | JSON | OpenAPI 风格接口清单(format=api/both) |
twin_report.json | JSON | 融合完整性报告 |
output-manifest.json | JSON | 运行清单 |
多波段 GeoTIFF,波段顺序 DEM / DSM。 或使用 --synthetic 生成物理一致的模拟数据(完全离线)。
--synthetic 模式完全无网络。MIT