GeoMonitoring with Python: Innovative Solutions for Latin America’s Challenges
summary
Concrete Python pipelines using GDAL, NumPy, Rasterio, Fiona, Matplotlib and GeoPandas read Sentinel-2 multispectral tiles, compute indices like NDBI, and run segmentation with Random Forest and zero‑shot SAM. The system fuses Sentinel-2, radar, station and model data to detect boats, classify wetlands and map floods; example processing of a storm with 290 mm in 12 hours produced results in two to three days and quantified inundation as 519, 73 and 209 football fields.
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chapters (11)
- 0:00Introduction
- 3:34Interdisciplinary approach
- 9:51Python in geomonitoring
- 13:58Workflow with libraries
- 16:05Case study: lagoon monitoring
- 17:35Coastal geomorphology analysis
- 19:44Beach visitor detection
- 20:28Wetland monitoring and land use
- 24:44Flood prediction models
- 27:33Future vision
- 30:22Working groups
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