geoskill-forest-cover-change

多期 NDVI 阈值与变化矢量幅度检测森林损失/增益/稳定，输出变化栅格与年度面积统计

森林覆盖变化检测 | Forest Cover Change Detection

Detects forest loss / gain / stable from multi-temporal NDVI. For each period, an NDVI threshold (default 0.3) classifies forest pixels; comparing the first and last periods, a pixel changing from forest to non-forest with a drop ≥ the drop threshold is recorded as loss, a pixel changing from non-forest to forest with an increase ≥ the gain threshold is recorded as gain, and everything else is recorded as stable. The change vector magnitude (CVA, the L2 norm of the adjacent-period difference) is also computed to quantify change intensity.

Typical applications: deforestation monitoring, afforestation effectiveness assessment, and annual forest resource change ledgers. In synthetic mode, logging (loss) and afforestation (gain) are injected into defined areas; the detection results match the injected mask pixel-by-pixel, and CVA intensity in the loss areas is significantly higher than in stable areas, enabling offline validation.

Dependencies / 依赖

bash

pip install 'numpy' 'rasterio' 'scipy'

Usage / 使用方法

Basic usage

bash

python geoskill-forest-cover-change.py --bbox 116.0 39.0 117.0 40.0 --n-dates 4

Example 1 (synthetic data, offline)

bash

python geoskill-forest-cover-change.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out

Example 2 (read multi-temporal NDVI rasters)

bash

python geoskill-forest-cover-change.py --input ndvi_series.tif --threshold 0.3 --output-dir ./out

Example 3 (stricter loss criterion)

bash

python geoskill-forest-cover-change.py --bbox 116 39 117 40 --synthetic --drop-threshold 0.2 --output-dir ./out

Example 4 (custom years + silence)

bash

python geoskill-forest-cover-change.py --bbox 121 31 122 32 --synthetic --start-year 2001 --interval-years 3 --quiet --output-dir ./out

Output / 输出

File	Format	Description
forest_change_class.tif	GeoTIFF (int32)	0=stable, 1=loss, 2=gain
cva_magnitude.tif	GeoTIFF (float32)	Change vector magnitude
area_stats.json	JSON	Per-class area + per-period forest area series
output-manifest.json	JSON	Run manifest

Data Source / 数据源 / Source

• Local multi-band NDVI GeoTIFF (one period per band);
• --synthetic synthesizes an NDVI series offline (no network, no account required).

Privacy / 隐私声明 / Privacy

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

License / License

MIT

---

---

name: geoskill-forest-cover-change description: '多期 NDVI 阈值与变化矢量幅度检测森林损失/增益/稳定，输出变化栅格与年度面积统计'

森林覆盖变化检测 | Forest Cover Change Detection

从多期 NDVI 检测森林覆盖的损失 / 增益 / 稳定。逐期用 NDVI 阈值（默认 0.3） 判定森林像元，比较首末期：由森林降为非森林且降幅 ≥ drop 阈值记为损失， 由非森林升为森林且升幅 ≥ gain 阈值记为增益，其余为稳定。同时计算 变化矢量幅度（CVA，相邻期差分的 L2 范数）量化变化强度。

典型应用：毁林监测、造林成效评估、森林资源年度变化台账。合成模式在 确定区域注入砍伐（损失）与造林（增益），检测结果与注入掩膜逐像元一致， 且损失区 CVA 强度显著高于稳定区，便于离线验证。

依赖

bash

pip install 'numpy' 'rasterio' 'scipy'

使用方法

基本用法

bash

python geoskill-forest-cover-change.py --bbox 116.0 39.0 117.0 40.0 --n-dates 4

示例 1（合成数据，离线）

bash

python geoskill-forest-cover-change.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out

示例 2（读取多期 NDVI 栅格）

bash

python geoskill-forest-cover-change.py --input ndvi_series.tif --threshold 0.3 --output-dir ./out

示例 3（更严格的损失判定）

bash

python geoskill-forest-cover-change.py --bbox 116 39 117 40 --synthetic --drop-threshold 0.2 --output-dir ./out

示例 4（自定义年份 + 静默）

bash

python geoskill-forest-cover-change.py --bbox 121 31 122 32 --synthetic --start-year 2001 --interval-years 3 --quiet --output-dir ./out

输出

文件	格式	说明
forest_change_class.tif	GeoTIFF (int32)	0=稳定, 1=损失, 2=增益
cva_magnitude.tif	GeoTIFF (float32)	变化矢量幅度
area_stats.json	JSON	逐类面积 + 逐期森林面积序列
output-manifest.json	JSON	运行清单

数据源 / Source

• 本地多波段 NDVI GeoTIFF（每波段一期）；
• --synthetic 离线合成 NDVI 序列（无需网络、无需账号）。

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