geoskill-lulc-change-matrix

两期土地覆被分类栅格逐像元交叉制表，输出转移矩阵、变化面积统计与 Sankey 流向数据

土地覆被转移矩阵 | Land Cover Transition Matrix

Perform pixel-by-pixel cross-tabulation of two land cover classification rasters (integer classes) to quantify transitions between classes. Outputs a transition matrix (rows = earlier epoch t1, columns = later epoch t2, cell values = pixel counts), per-class gross loss / gross gain / net change and area statistics, as well as nodes + links data ready to be used directly in a Sankey flow diagram.

Typical applications: cropland loss / built-up expansion monitoring, land use transition analysis, and national land change ledgers. Diagonal cells are unchanged pixels, while off-diagonal cells are pixels that have transitioned; combined with the bbox, pixel counts can be converted to square kilometers. Synthetic mode injects a known number of class transitions (e.g., cropland → built_up) so that "detected change = injected change" can be verified offline.

Dependencies / 依赖

bash

pip install 'numpy' 'rasterio' 'pandas'

Usage / 使用方法

Basic Usage

bash

python geoskill-lulc-change-matrix.py --bbox 116.0 39.0 117.0 40.0 --n-classes 5

Example 1 (synthetic data, offline)

bash

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

Example 2 (read two local classification rasters)

bash

python geoskill-lulc-change-matrix.py --t1 cls_2015.tif --t2 cls_2020.tif --output-dir ./out

Example 3 (different area + quiet mode)

bash

python geoskill-lulc-change-matrix.py --bbox 121.0 31.0 122.0 32.0 --synthetic --quiet --output-dir ./out

Example 4 (3-class scenario)

bash

python geoskill-lulc-change-matrix.py --bbox 116 39 117 40 --synthetic --n-classes 3 --output-dir ./out

Output / 输出

File	Format	Description
transition_matrix.csv	CSV	Transition matrix (with row and column totals)
change_areas.json	JSON	Per-class gross loss/gain/net change + area in km²
sankey.json	JSON	Sankey flow nodes + links
change_map.tif	GeoTIFF (int32)	Change map (0 = unchanged, 1 = changed)
output-manifest.json	JSON	Run manifest

Data Source / 数据源 / Source

• Two local classification GeoTIFFs (integer classes, spatially aligned);
• --synthetic generates a two-epoch classification pair 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; no user data is uploaded.

License / License

MIT

---

---

name: geoskill-lulc-change-matrix description: '两期土地覆被分类栅格逐像元交叉制表，输出转移矩阵、变化面积统计与 Sankey 流向数据'

土地覆被转移矩阵 | Land Cover Transition Matrix

对两期土地覆被分类栅格（整数类别）做逐像元交叉制表，量化类别之间的 转移关系。输出转移矩阵（行=前期 t1，列=后期 t2，元素为像元数）、 逐类毛损失/毛增益/净变化与面积统计，以及可直接用于 Sankey 流向图的 nodes + links 数据。

典型应用：耕地流失/建设用地扩张监测、土地利用转型分析、国土变化台账。 对角线为未变化像元，非对角线即发生转移的像元；结合 bbox 可把像元数 换算为平方公里。合成模式会注入确定数量的类别转移（如 cropland → built_up）， 便于离线验证「检测到的变化量 = 注入量」。

依赖

bash

pip install 'numpy' 'rasterio' 'pandas'

使用方法

基本用法

bash

python geoskill-lulc-change-matrix.py --bbox 116.0 39.0 117.0 40.0 --n-classes 5

示例 1（合成数据，离线）

bash

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

示例 2（读取两期本地分类栅格）

bash

python geoskill-lulc-change-matrix.py --t1 cls_2015.tif --t2 cls_2020.tif --output-dir ./out

示例 3（不同区域 + 静默）

bash

python geoskill-lulc-change-matrix.py --bbox 121.0 31.0 122.0 32.0 --synthetic --quiet --output-dir ./out

示例 4（3 类场景）

bash

python geoskill-lulc-change-matrix.py --bbox 116 39 117 40 --synthetic --n-classes 3 --output-dir ./out

输出

文件	格式	说明
transition_matrix.csv	CSV	转移矩阵（含行列合计）
change_areas.json	JSON	逐类毛损失/增益/净变化 + 面积 km²
sankey.json	JSON	Sankey 流向 nodes + links
change_map.tif	GeoTIFF (int32)	变化图（0=未变，1=变化）
output-manifest.json	JSON	运行清单

数据源 / Source

• 本地两期分类 GeoTIFF（整数类别，空间对齐）；
• --synthetic 离线合成两期分类对（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