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🌿 Black Forest — Satellite Forest Monitoring

📍 Germany · 48.3614°, 8.145° · Zone 50km · Last updated: 2026-09-16

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/ 100

Moderate Forest

Temperate Forest · 95.8% forest cover

🛰️ Analyzed by ESA Sentinel-2, NASA Landsat, NASA GEDI LiDAR & NASA FIRMS

0.729
🌿 NDVI
95.8%
🌳 Forest Cover
10.5m
📏 Canopy Height (GEDI)
3
🔥 Fire Pixels/year
+0.187
📈 NDVI Trend 10y
+0.231
🕰️ NDVI Trend 40y
78.4 t/ha
⚖️ Above-ground Biomass
Old-growth forest (>120 years)
🌱 Development Stage
⚠️ STABLE — No significant change

📊 Historical Analysis

🌿 NDVI Trend 3 years (Sentinel-2)+0.021
📡 NDVI Trend 10 years (Landsat 8/9)+0.187
🕰️ NDVI Trend 40 years (Landsat 1984)+0.231
📡 Sentinel-1 Radar (VV)-11.2 dB
🔥 Fire Activity (NASA FIRMS)3 pixels/year

🛰️ Methodology

This analysis uses real satellite data from 6 sources processed by CanopySat Forest Intelligence:

• ESA Sentinel-2 (10m) — NDVI, NDRE, NBR vegetation indices and forest cover classification

• ESA Sentinel-1 (10m) — SAR radar backscatter for forest structure assessment

• NASA Landsat 8/9 (30m) — 10-year historical vegetation trend analysis

• NASA Landsat 4/5 (30m) — 40-year historical trend since 1984

• NASA FIRMS/VIIRS (375m) — Active fire detection and annual fire pixel count

• NASA GEDI LiDAR (25m) — Canopy height measured by laser from the International Space Station

All data processed via Google Earth Engine. Analysis date: 2026-09-16.

🌍 About Black Forest

The Black Forest (Schwarzwald) in southwestern Germany is one of Europe most iconic temperate forests, covering approximately 6,000 km². It is characterized by dense coniferous and mixed forests, with spruce, fir and beech as dominant species. The forest has shown remarkable recovery since the 1980s acid rain period, with CanopySat satellite data confirming a positive 40-year NDVI trend of +0.231.

📍 Methodological Note

This analysis covers a 50km sample zone representative of this forest region — not the entire forest. Data comes from real satellites (ESA Sentinel-2, NASA Landsat, NASA GEDI LiDAR) and is updated periodically.

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