Geoskill: Nature Risk TNFD

TNFD LEAP-based nature-related financial risk screening. Locates enterprise assets relative to protected areas, water stress, and forest cover; evaluates nature dependency and impact using sector materiality; produces priority risk inventory and audit-ready evidence package.

Nature Risk TNFD

TNFD LEAP approach (Locate → Evaluate) for screening enterprise assets against ecological sensitive areas, ecosystem state, and natural dependencies. Produces a spatial evidence package for nature-related financial risk assessment.

Trigger

Use when the user wants to:

• Screen enterprise assets for proximity to protected areas / Key Biodiversity Areas
• Assess nature dependency and impact by sector using TNFD LEAP methodology
• Evaluate water stress, forest cover, and biodiversity pressure at asset locations
• Generate a priority nature risk inventory for ESG / TNFD reporting
• Produce a Locate-phase spatial evidence package

CLI Usage

bash

# Synthetic demo mode (no input files needed)
python scripts/nature_risk_tnfd.py --output-dir ./nrt-output

# With custom assets file (GeoJSON or CSV)
python scripts/nature_risk_tnfd.py --assets ./my-assets.geojson --output-dir ./nrt-output

# With sector override and custom buffers
python scripts/nature_risk_tnfd.py --sector agriculture --buffers "facility:5000,watershed:10000" --output-dir ./nrt-output

# With all parameters
python scripts/nature_risk_tnfd.py --assets ./assets.csv --sector mining --buffers "facility:10000" --indicators-config ./my-indicators.json --output-dir ./nrt-output

Parameters

Parameter	Default	Description
--assets	None	Path to assets file (GeoJSON or CSV with lat/lon)
--sector	None	Override sector for all assets (agriculture/mining/manufacturing/energy/real_estate/tourism)
--buffers	facility:5000	Buffer distances as type:meters pairs
--indicators-config	None	Path to TNFD indicators JSON
--output-dir	./nrt-output	Output directory

Output

File	Description
asset_nature_context.geojson	Per-asset nature context with all indicators
indicator_table.csv	Tabular indicator values for all assets
priority_assets.geojson	High/medium risk assets for prioritization
data_gaps.json	Identified data gaps by asset and severity
tnfd_screening_report.html	Human-readable screening report
request.json	Analysis request metadata
dataset-manifest.json	Dataset inventory
output-manifest.json	Output file inventory
qa.json	Quality assurance checks
run.log	Execution log

Key Algorithms

Locate: Spatial Screening

For each asset, computes:

• Protected area proximity: Direct overlap, nearest distance (haversine), buffer overlap
• Water stress: Raster lookup at asset location, classified into 4 levels
• Forest cover: Raster lookup at asset location, classified into 4 levels

Evaluate: Dependency and Impact Scoring

Uses sector materiality matrix (0-5 scale) adjusted for location context:

• Dependency: Water supply, pollination, flood protection, climate regulation, timber/fiber
• Impact: Land use change, pollution, water withdrawal, GHG emissions, invasive species
• Location adjustments: water stress increases water dependency; protected area proximity increases land use impact

Priority Scoring

Priority = (dependency + impact) / 2, classified into: negligible / low / medium / high

Geographic Calculations

• Distances: Haversine formula (great-circle)
• Buffers: cos(lat) * 111320 m/degree approximation
• Areas: cos(lat) * 111320^2 m^2/degree^2 approximation

Exit Codes

Code	Meaning
0	Success
2	Argument error
3	Dependency missing
6	Data validation failure
7	Processing failure

Important Limitations

• Screening only, NOT disclosure: This is a Locate/Evaluate-phase screening tool. Full TNFD disclosure requires Prepare and Assess phases with enterprise processes.
• Synthetic data for demo: Without real ecological data inputs, demo mode uses synthetic data. Replace with real WDPA, WRI Aqueduct, Hansen GFC data for production use.
• Approximate geographic calculations: Buffer and area calculations use cos(lat) approximation. For precise analysis, use projected coordinate systems.
• Sensitive species data excluded: KBA/IBAT sensitive species locations are not included in outputs. Access requires separate licensing.
• Sector materiality is generic: Default scores are indicative. Enterprises should calibrate materiality to their specific value chain.

Data Licensing

• Do NOT package commercial biodiversity data (IBAT/KBA) in the skill
• WDPA data requires acceptance of terms of use
• WRI Aqueduct data: CC BY 4.0
• Hansen Global Forest Change: CC BY 4.0

References

• TNFD (Taskforce on Nature-related Financial Disclosures) LEAP approach
• WDPA (World Database on Protected Areas)
• WRI Aqueduct Water Risk Atlas
• Hansen Global Forest Change dataset
• IUCN Protected Area Categories

数据下载

本 skill 可自动从 Microsoft Planetary Computer 下载数据 (无需 API key):

bash

python nature_risk_tnfd.py --bbox 116,39,117,40 --date-range 2024-06-01,2024-06-30 --output-dir <tmp>

• --bbox W,S,E,N: WGS-84 边界框 (西, 南, 东, 北)
• --date-range START,END: 日期范围 (YYYY-MM-DD,YYYY-MM-DD)
• --aoi-file <path.geojson>: 替代 --bbox 的 GeoJSON 多边形
• --cache-dir <path>: 缓存目录 (默认 ~/.geoskill_cache)

当用户只给 --bbox + --date-range (没有 --assets) 时，skill 自动下载数据。 当用户给 --assets 时，走原文件路径 (向后兼容)。