{"name": "CA-Markov \u571f\u5730\u5229\u7528\u53d8\u5316\u9884\u6d4b", "package_name": "qgis_camarkov", "description": "CA-Markov land-use change analysis, model training and scenario prediction based on random-forest transition potentials.", "about": "CA-Markov land change modelling exposed as three Processing algorithms: transfer\nanalysis (fast transition-matrix preview), model training (random-forest transition\npotential maps) and multi-step scenario prediction with accuracy assessment.\nThe bundled engine (from the SharpGIS project, MIT licensed) runs in a separate Python\nsubprocess, so it never loads GDAL into the QGIS process.\nRequires numpy, scipy, scikit-learn, rasterio and matplotlib; QGIS 3.28 or newer\n(validated on 3.40.15 LTR). All input rasters must share the same grid and CRS.\nOutputs: a prediction GeoTIFF, a report, figures and a metrics JSON, shown in a\ndockable five-tab result panel.\n\u4e2d\u6587\uff1a\u63d0\u4f9b\u8f6c\u79fb\u5206\u6790\u3001\u8bad\u7ec3\u6a21\u578b\u3001\u53d8\u5316\u9884\u6d4b\u4e09\u4e2a\u5904\u7406\u7b97\u6cd5\uff0c\u7ed3\u679c\u4ee5\u975e\u6a21\u6001\u505c\u9760\u9762\u677f\u5c55\u793a\u3002", "homepage": "https://github.com/LQC20504-collab/qgis-camarkov", "repository": "https://github.com/LQC20504-collab/qgis-camarkov", "tracker": "https://github.com/LQC20504-collab/qgis-camarkov/issues", "author": "SharpGIS contributors", "tags": ["camarkov", "markov", "ca", "landuse", "landcover", "raster", "processing", "prediction"], "downloads": 9, "latest_version": "0.1.1", "versions": [{"version": "0.1.1", "experimental": false, "qgis_min": "3.28.0", "qgis_max": "3.99.0", "downloads": 9, "uploaded_by": "LQC20504-collab", "upload_datetime": "2026-11-04T06:12:55.183416"}]}