geoskill-carbon-stock-estimation

由 NDVI 幂律异速生长方程估算地上生物量碳，叠加根茎比地下碳与类型化土壤碳密度。Estimates carbon stocks from biomass allometry and soil carbon density. 输出地上碳/土壤碳/总碳三张 GeoTIFF 与汇总 JSON。

碳储量估算 | Carbon Stock Estimation

Aboveground biomass is estimated with the power-law allometric equation AGB = scale × max(NDVI, 0)^power and multiplied by the IPCC default carbon fraction of 0.47 to obtain aboveground carbon; belowground carbon = aboveground carbon × root-to-shoot ratio (default 0.30); soil organic carbon is computed from five land cover classes — forest/grassland/cropland/bare land/water — with carbon densities of 60/45/35/15/0 Mg C/ha × pixel area. Total carbon = aboveground carbon × (1 + root-to-shoot ratio) + soil carbon.

Applicable scenarios: regional carbon baseline accounting, dual-carbon (carbon peak and carbon neutrality) target assessment, and measurement of ecological carbon sequestration projects.

Dependencies / 依赖

bash

pip install numpy rasterio

Usage / 使用方法

Example 1: Synthetic Scene with Default Parameters

bash

python geoskill-carbon-stock-estimation.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./output

Example 2: Real NDVI Raster (band1 Must Be NDVI, Values ≈ −1..1)

bash

python geoskill-carbon-stock-estimation.py --input ndvi.tif --output-dir ./real

Example 3: Custom Allometric Equation Parameters

bash

python geoskill-carbon-stock-estimation.py --bbox 116 39 117 40 --synthetic --scale 150 --power 1.8 --output-dir ./tuned

Example 4: Different Region

bash

python geoskill-carbon-stock-estimation.py --bbox 121 31 122 32 --synthetic --output-dir ./shanghai

Example 5: Quiet Batch Mode

bash

python geoskill-carbon-stock-estimation.py --bbox 113 23 114 24 --synthetic --quiet --output-dir ./batch

Output / 输出

File	Format	Description
agb_carbon.tif	GeoTIFF (float32)	Aboveground biomass carbon (Mg C/pixel)
soil_carbon.tif	GeoTIFF (float32)	Soil organic carbon (Mg C/pixel)
total_carbon.tif	GeoTIFF (float32)	Total carbon stock (Mg C/pixel)
carbon_params.json	JSON	Carbon fraction, root-to-shoot ratio, and totals of each carbon pool
output-manifest.json	JSON	Run manifest (inputs/outputs/QA/software versions)

Data Source / 数据源 / Source

Local GeoTIFF (band1=NDVI, values approximately −1..1; inputs outside this range are rejected with exit code 6); the carbon fraction (0.47) follows the IPCC 2006 Guidelines for National Greenhouse Gas Inventories, the root-to-shoot ratio follows the global meta-analysis of Mokany et al. 2006, and the soil carbon densities are order-of-magnitude defaults for the 0–30 cm soil layer (IPCC reference stock convention); synthetic mode generates data locally with no external data source.

Limitations / 局限（诚实声明）

• AGB = scale × NDVI^power is an empirical power-law model; scale/power must be calibrated by region and vegetation type, and the default values (200 / 2.0) are intended for screening-level estimates only and cannot be used directly for project-level accounting (MRV).
• The 0.30 root-to-shoot ratio is a global default: in reality it varies by biome (tropical forests ~0.24, shrublands/grasslands higher), and fine-scale accounting should replace it with biome-specific values.
• The soil carbon densities (forest 60 / grassland 45 / cropland 35 / bare land 15 / water 0 Mg C/ha) are fixed defaults that are not refined by climate zone or soil type; surface litter and deadwood carbon pools are not included.

Privacy / 隐私声明 / Privacy

• Runs fully offline by default; makes no network requests
• --synthetic mode reads no external data
• All computation is performed locally; no user data is uploaded

License / License

MIT

---

---

name: geoskill-carbon-stock-estimation description: '由 NDVI 幂律异速生长方程估算地上生物量碳，叠加根茎比地下碳与类型化土壤碳密度。Estimates carbon stocks from biomass allometry and soil carbon density. 输出地上碳/土壤碳/总碳三张 GeoTIFF 与汇总 JSON。'

碳储量估算 | Carbon Stock Estimation

地上生物量按幂律异速方程 AGB = scale × max(NDVI,0)^power 估算，乘以 IPCC 默认含碳系数 0.47 得地上碳；地下碳 = 地上碳 × 根茎比（默认 0.30）；土壤有机碳按林/草/耕/裸/水五类碳密度（60/45/35/15/0 Mg C/ha）× 像元面积。总碳 = 地上碳×(1+根茎比) + 土壤碳。

适用场景：区域碳本底核算、双碳目标评估、生态固碳项目计量。

依赖

bash

pip install numpy rasterio

使用方法

示例 1：合成场景默认参数

bash

python geoskill-carbon-stock-estimation.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./output

示例 2：真实 NDVI 栅格（band1 必须为 NDVI，取值约 −1..1）

bash

python geoskill-carbon-stock-estimation.py --input ndvi.tif --output-dir ./real

示例 3：自定义异速方程参数

bash

python geoskill-carbon-stock-estimation.py --bbox 116 39 117 40 --synthetic --scale 150 --power 1.8 --output-dir ./tuned

示例 4：不同区域

bash

python geoskill-carbon-stock-estimation.py --bbox 121 31 122 32 --synthetic --output-dir ./shanghai

示例 5：静默批量

bash

python geoskill-carbon-stock-estimation.py --bbox 113 23 114 24 --synthetic --quiet --output-dir ./batch

输出

文件	格式	说明
agb_carbon.tif	GeoTIFF (float32)	地上生物量碳（Mg C/像元）
soil_carbon.tif	GeoTIFF (float32)	土壤有机碳（Mg C/像元）
total_carbon.tif	GeoTIFF (float32)	总碳储量（Mg C/像元）
carbon_params.json	JSON	含碳系数、根茎比、各碳库总量
output-manifest.json	JSON	运行清单（输入/输出/QA/软件版本）

数据源 / Source

本地 GeoTIFF（band1=NDVI，取值约 −1..1；超出该范围的输入会被拒绝，exit 6）； 含碳系数（0.47）参考 IPCC 2006 清单指南，根茎比参考 Mokany et al. 2006 全球元分析， 土壤碳密度为 0–30 cm 土层的量级默认值（IPCC 参考储量口径）；合成模式本地生成，无外部数据源。

局限（诚实声明）

• AGB = scale × NDVI^power 为经验幂律模型，scale/power 需按区域/植被类型标定， 默认值（200 / 2.0）仅作筛查级估算，不能直接用于项目计量（MRV）。
• 根茎比 0.30 为全球通用值：实际随生物区变化（热带林 ~0.24，灌丛/草地更高）， 精细核算应替换为生物区特异值。
• 土壤碳密度（林 60 / 草 45 / 耕 35 / 裸 15 / 水 0 Mg C/ha）为固定默认值， 未按气候区/土类细化；地表凋落物与死木碳库未计入。

隐私声明 / Privacy

• 默认完全离线运行，不发起任何网络请求
• --synthetic 模式不读取任何外部数据
• 所有计算在本地完成，不上传用户数据

License

MIT