geoskill-spatial-data-validation

空间数据质量验证 | Spatial Data Validation

Performs four-dimensional quality validation on vector data: geometry validity (shapely checks each feature for self-intersection, ring self-intersection, empty geometries, and null geometries, with reasons given), topology checks (duplicate geometry counts, pairwise polygon overlap detection), attribute completeness (null-value ratio per required field), and CRS consistency (actual EPSG compared against the expected value).

The four dimensions are combined by weights (geometry 0.40 / topology 0.20 / attributes 0.25 / CRS 0.15) into a 0–1 composite score, mapped to A–F grades, and invalid geometry features are exported as GeoJSON for manual review. Suitable for pre-load quality control, deliverable acceptance, and self-checks before data submission.

--synthetic mode generates features with intentionally planted defects (bowtie self-intersecting polygons, null geometries, missing attributes), reproducing all defect-detection paths offline.

Dependencies / 依赖

pip install numpy rasterio geopandas shapely fiona pyproj

Usage / 使用方法

Basic Usage

python geoskill-spatial-data-validation.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out

Example 1 (Synthetic Data, Offline)

python geoskill-spatial-data-validation.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out

示例 2：验证 Shapefile

python geoskill-spatial-data-validation.py --input parcels.shp --crs EPSG:4326 --output-dir ./report

Example 3: Custom Required Attribute Fields

python geoskill-spatial-data-validation.py --input buildings.gpkg --fields id,name,height,type --output-dir ./r2

示例 4：验证 GeoPackage 并检查投影一致性

python geoskill-spatial-data-validation.py --input roads.gpkg --crs EPSG:3857 --output-dir ./r3

Example 5: Silent Quality Check

python geoskill-spatial-data-validation.py --input data.geojson --quiet --output-dir ./r4

Output / 输出

Data Source / 数据源 / Source

• --input: local vector file (any OGR format)
• --synthetic: locally generates defective test features

Privacy / 隐私声明 / Privacy

• Runs offline by default; --synthetic mode requires no network at all.
• All processing is done locally; no user data is uploaded.

License / License

MIT

---

---

name: geoskill-spatial-data-validation description: '检查矢量几何有效性、拓扑错误、属性完整性与 CRS 一致性，输出分级质量报告。Validate geometry validity, topology, attribute completeness and CRS consistency for vector data and emit a graded quality report.'

空间数据质量验证 | Spatial Data Validation

对矢量数据执行四个维度的质量验证：几何有效性（shapely 逐要素判定 self-intersection、ring 自交、空几何、null 几何并给出原因）、拓扑检查 （重复几何计数、多边形两两重叠检测）、属性完整性（逐必填字段统计 空值比例）、CRS 一致性（实际 EPSG 与期望值比对）。

四个维度按权重（几何 0.40 / 拓扑 0.20 / 属性 0.25 / CRS 0.15）合成 0-1 综合评分，映射为 A-F 等级，并把无效几何要素导出为 GeoJSON 供人工 复核。适合数据入库质检、成果验收、数据汇交前自检。

--synthetic 模式生成含刻意缺陷的要素（bowtie 自相交多边形、null 几何、 缺失属性），可离线复现全部缺陷检出路径。

依赖

pip install numpy rasterio geopandas shapely fiona pyproj

使用方法

基本用法

python geoskill-spatial-data-validation.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out

示例 1（合成数据，离线）

python geoskill-spatial-data-validation.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out

示例 2：验证 Shapefile

python geoskill-spatial-data-validation.py --input parcels.shp --crs EPSG:4326 --output-dir ./report

示例 3：自定义必填属性字段

python geoskill-spatial-data-validation.py --input buildings.gpkg --fields id,name,height,type --output-dir ./r2

示例 4：验证 GeoPackage 并检查投影一致性

python geoskill-spatial-data-validation.py --input roads.gpkg --crs EPSG:3857 --output-dir ./r3

示例 5：静默质检

python geoskill-spatial-data-validation.py --input data.geojson --quiet --output-dir ./r4

输出

数据源 / Source

• --input：本地矢量文件（任意 OGR 格式）
• --synthetic：本地生成含缺陷的测试要素

隐私声明 / Privacy

• 默认离线运行，--synthetic 模式完全无网络。
• 所有处理在本地完成，不上传用户数据。

License

MIT