Forest analysis and forestry management. Use when analyzing forest cover change, timber inventory, deforestation detection, forest carbon stocks, wildfire risk assessment, or canopy structure analysis.
Resources
9Install
npx skillscat add activeinferenceinstitute/geo-infer/geo-infer-forest Install via the SkillsCat registry.
We need to produce a 2-3 sentence plain-text summary, objective, factual, no marketing, no bullet points, no headings, no markdown. Max 60 words. Summarize skill: forest analysis and forestry management, used for forest cover change, timber inventory, deforestation detection, carbon stocks, wildfire risk, canopy structure. Problem: need to analyze forest data, detect changes, estimate carbon, assess fire risk, etc. When to use: when analyzing forest cover change, timber inventory, deforestation detection, carbon stocks, wildfire risk, canopy structure. Provide 2-3 sentences.
GEO-INFER-FOREST
Instructions
Core Capabilities
- Forest cover: Change detection, canopy height models, NDVI analysis
- Timber inventory: Volume estimation, growth modeling, harvest planning
- Deforestation: Alert systems, historical trend analysis, driver attribution
- Carbon stocks: Above/below-ground biomass, soil organic carbon
- Wildfire: Risk mapping, fire spread modeling, post-fire recovery
Key Imports
from geo_infer_forest.core.cover_analysis import ForestCoverAnalyzer
from geo_infer_forest.core.carbon import CarbonStockEstimator
from geo_infer_forest.core.fire_risk import WildfireRiskModel
from geo_infer_forest.core.inventory import TimberInventoryExamples
from geo_infer_forest.core.cover_analysis import ForestCoverAnalyzer
analyzer = ForestCoverAnalyzer()
change = analyzer.detect_change(t1_raster, t2_raster)
loss_area_km2 = change.total_loss_area()Guidelines
Integrations
- Integrates with BIO for forest biodiversity assessment
- Integrates with CLIMATE for climate-driven forest risk
- Integrates with SPACE for H3-based forest tessellation
- Test:
uv run python -m pytest GEO-INFER-FOREST/tests/ -v