Inconsistency Detection in Cross-Layer Tile Maps with Super-Pixel Segmentation

The consistency of geospatial data is great significance for the application and updating geographic information in web maps. Due to multiple sources different temporal versions, tile maps usually meet inconsistency question across layers. This study tries develop a method detect this kind utilizing raster-based scaling approach. Compared with vector-based handling, can be directly available multi-level images pixel representation form. proposed cross-layer raster map rendering (CRTMRM) consists four primary aspects: object separation, rules, derivation super-pixel segmentation, detection. scale transformation strategy attempts obtain simplified representation. Taking lifespan variation geometric rules into account, detection conducted between multi-sources, scales through actual derived overlay analysis. experiment focuses on features water or vegetation areas Level 9 14 Baidu Maps, Amap, Google Maps. able serve as basis massive unstructured support intelligent rendering.