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geoskill-agriculture-subsidy-verification

读取本地 NDVI GeoTIFF 与申报地块矢量，按阈值把像元分类为作物/非作物，逐地块计算实测作物占比并与申报占比比较；支持 area-diff 与 class-match 两种方法，超容差即标记疑似违规，输出核查报告、作物掩膜、地块栅格与违规地块矢量。

ruiduobao
ruiduobao
热度 7.65
最近更新 2026-08-04 19:20:58
分类：数据依赖：代码执行 / 读写文件应用场景：数据处理 / 报告撰写

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add geoskill-agriculture-subsidy-verification
Metadata
name
geoskill-agriculture-subsidy-verification
description
高分辨率作物识别叠加申报地块做差异检测，核查补贴合规性。Verifies subsidy compliance by overlaying high-resolution crop classification on declared parcels for difference detection.

农业补贴遥感核查 | Agriculture Subsidy Verification

Uses an NDVI raster derived from remote sensing imagery to classify crop/non-crop by threshold, overlays it with the vector parcels declared for subsidy, computes the "remotely sensed crop fraction" per parcel, and compares it with the "declared crop fraction": parcels exceeding the tolerance are flagged as suspected violations (over-declared / under-declared). This is a simplified implementation of the area-consistency check used in the EU CAP "Checks by Monitoring" and in national cropland subsidy verification.

Two verification methods:

  • area-diff (default): flagged when |measured fraction − declared fraction| > tolerance;
  • class-match: binarizes declared/measured fractions into "crop/non-crop" at the 0.5 boundary, flagged when classes do not match.

Data quality rules: NoData pixels are excluded from statistics; parcels with no valid pixels inside (or parcels smaller than the pixel and thus not burned in) are recorded as no-coverage and are not flagged as violations; NDVI values are validated to [-1,1]; bbox does not support crossing the 180° meridian.

Dependencies / 依赖

pip install 'numpy' 'rasterio' 'geopandas' 'shapely'

Usage / 使用方法

Basic Usage

python geoskill-agriculture-subsidy-verification.py --bbox 116.0 39.0 117.0 40.0 [other parameters]

Example 1 (Synthetic Data, Offline)

python geoskill-agriculture-subsidy-verification.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out

示例 2（真实 NDVI + 申报地块）

python geoskill-agriculture-subsidy-verification.py --input ndvi.tif --parcels parcels.geojson --output-dir ./out

Example 3 (Class Matching + Custom Tolerance)

python geoskill-agriculture-subsidy-verification.py --input ndvi.tif --parcels parcels.geojson --method class-match --tolerance 0.1

示例 4（调整 NDVI 阈值）

python geoskill-agriculture-subsidy-verification.py --input ndvi.tif --parcels parcels.geojson --threshold 0.35

Example 5 (Projected Coordinate Input with Auto-Reprojection)

python geoskill-agriculture-subsidy-verification.py --input ndvi_utm.tif --parcels parcels_utm.gpkg --output-dir ./out

Output / 输出

File Format Description
crop_mask.tif GeoTIFF Crop mask (1=crop, 0=non-crop, nodata in NoData areas)
parcel_grid.tif GeoTIFF Parcel ID raster (background 0, parcels start from 1)
verification_report.json JSON Per-parcel verification records and statistics (primary output)
flagged_parcels.geojson GeoJSON Vector of suspected violation parcels
output-manifest.json JSON Run manifest

Data Source / 数据源 / Source

Local high-resolution NDVI GeoTIFF (EPSG:4326; projected coordinates are automatically reprojected) + declared parcel vectors (GeoJSON/GPKG/Shapefile, must contain parcel_id and declared_crop_frac columns, with declared fraction in [0,1]); --synthetic mode simulates offline without network.

Privacy / 隐私声明 / Privacy

  • Runs offline by default; --synthetic mode requires no network at all.
  • All processing is done locally; user data is never uploaded.

License / License

MIT

name: geoskill-agriculture-subsidy-verification description: '高分辨率作物识别叠加申报地块做差异检测，核查补贴合规性。Verifies subsidy compliance by overlaying high-resolution crop classification on declared parcels for difference detection.'

农业补贴遥感核查 | Agriculture Subsidy Verification

用遥感影像派生的 NDVI 栅格做作物/非作物阈值分类，与申报补贴的地块矢量叠加， 逐地块计算"遥感实测作物占比"，与"申报作物占比"比较，超过容差即标记为疑似违规 （虚报 over-declared / 少报 under-declared）。这是欧盟 CAP "Checks by Monitoring" 与各国耕地补贴核查中面积一致性检查的简化实现。

两种核查方法：

  • area-diff（默认）：|实测占比 − 申报占比| > tolerance 即标记；
  • class-match：以 0.5 为界把申报/实测二值化为"作物/非作物"，类别不一致即标记。

数据质量规则：NoData 像元不参与统计；地块内无有效像元（或地块小于像元未被烧录） 记为 no-coverage，不判定违规；NDVI 值域校验 [-1,1]；bbox 不支持跨 180° 经线。

依赖

pip install 'numpy' 'rasterio' 'geopandas' 'shapely'

使用方法

基本用法

python geoskill-agriculture-subsidy-verification.py --bbox 116.0 39.0 117.0 40.0 [其他参数]

示例 1（合成数据，离线）

python geoskill-agriculture-subsidy-verification.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out

示例 2（真实 NDVI + 申报地块）

python geoskill-agriculture-subsidy-verification.py --input ndvi.tif --parcels parcels.geojson --output-dir ./out

示例 3（类别匹配法 + 自定义容差）

python geoskill-agriculture-subsidy-verification.py --input ndvi.tif --parcels parcels.geojson --method class-match --tolerance 0.1

示例 4（调整 NDVI 阈值）

python geoskill-agriculture-subsidy-verification.py --input ndvi.tif --parcels parcels.geojson --threshold 0.35

示例 5（投影坐标输入自动重投影）

python geoskill-agriculture-subsidy-verification.py --input ndvi_utm.tif --parcels parcels_utm.gpkg --output-dir ./out

输出

文件 格式 说明
crop_mask.tif GeoTIFF 作物掩膜（1=作物，0=非作物，NoData 区域为 nodata）
parcel_grid.tif GeoTIFF 地块编号栅格（背景 0，地块从 1 起）
verification_report.json JSON 逐地块核查记录与统计（主产物）
flagged_parcels.geojson GeoJSON 疑似违规地块矢量
output-manifest.json JSON 运行清单

数据源 / Source

本地高分辨率 NDVI GeoTIFF（EPSG:4326；投影坐标自动重投影）+ 申报地块矢量 （GeoJSON/GPKG/Shapefile，需含 parcel_id 与 declared_crop_frac 列， 申报占比取值 [0,1]）；--synthetic 模式离线模拟，无需网络。

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