Geospatial Research · 2025

By Bikal Shrestha

Wildfire Hotspot Analysis in Peru

Spatial Patterns, Temporal Trends & Threats to Protected Areas

This study analyzes active fire hotspots and burned area data across Peru using NASA FIRMS, MODIS MCD64, and Sentinel-2 LULC, identifying high-risk clusters and their overlap with national protected areas and indigenous territories.

🗺️ GIS · QGIS · ArcGIS Pro🛰️ MODIS · FIRMS · Sentinel-2🐍 Python · Pandas · DBSCAN📊 Spatial Analysis · Visualization
GitHubMethodology
32,364
Fire Hotspots
1.0%
Inside Protected Areas
September
Peak Fire Month
329
Hotspots in Protected Zones

Interactive Fire Map

Toggle layers · Pan & zoom · Click points for details

All

Data: NASA FIRMS · SERNANP · MINAM · Base map: OpenFreeMap

Fire by Land Governance Type

Distribution of fire hotspots across land governance categories · All years (2000–2024)

Key finding

98.6% of detected fires burned in unprotected forest. 329 hotspots (1.0%) fell within national protected areas.

  • Unprotected Forest31,925 · 98.6%
  • National Protected Area329 · 1%
  • Regional Conservation105 · 0.3%
  • Private Conservation5 · 0%

Fire seasonality

Hotspots by month · All years (2000–2024) · Peak: August–September

Temporal Analysis

Bar chart showing annual fire hotspot counts for Peru

Annual Fire Trend

Total hotspots per year · NASA FIRMS

Heatmap showing fire hotspot counts by year and month

Year × Month Heatmap

Fire intensity by year and month · 2000–2024

STL decomposition plot of monthly fire time series

Seasonal Decomposition

STL trend · seasonal · residual components

Active Fire Hotspots vs Burned Area

Annual comparison 2001–2024 · Left axis: Fire Hotspots count · Right axis: Burned Areas polygon count

Fire HotspotsBurned Areas

Regional Fire Ranking

Top 20 districts by hotspot count · All years (2000–2024)

RankDistrictHotspots% of top 20Share
#1Puerto Inca4,39015.2%
#2Padre Abad3,85713.4%
#3Coronel Portillo3,46112.0%
#4Tambopata2,3998.3%
#5Bellavista1,9886.9%
#6Tahuamanu1,9866.9%
#7Mariscal Cáceres1,5625.4%
#8Oxapampa1,2504.3%
#9Satipo1,0163.5%
#10Ucayali8422.9%
#11Alto Amazonas8422.9%
#12La Convención7632.7%
#13Lamas6572.3%
#14Picota6502.3%
#15San Martín6092.1%
#16Huallaga6072.1%
#17Leoncio Prado5692.0%
#18Atalaya5091.8%
#19Tocache4311.5%
#20Marañón4031.4%

Methodology & Tools

Data Sources

  • 🛰️ NASA FIRMS — J1V-C2, J2V-C2, SV-C2, M-C61
  • 🌍 MODIS MCD64A1 Burned Area
  • 🗺️ Sentinel-2 10m LULC 2024
  • 🏛️ SERNANP National Protected Areas
  • 🌱 MINAM Indigenous Community Boundaries

Analysis Pipeline

  • 🐍 Python · GeoPandas · Pandas
  • 📊 DBSCAN Spatial Clustering
  • 📈 STL Temporal Decomposition
  • 🗺️ QGIS · ArcGIS Pro
  • 📁 R Markdown · Jupyter Notebooks