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Title & Speakers	Event
Forest Modeling and Ecosystem Services Evaluation Through a Data-Driven Python Workflow 2025-10-16 · 14:00 Laya Zeinali – PhD candidate @ Tarbiat Modares University Exploring how to model forest structure and quantify ecosystem services using Python and Earth observation data (GEDI, Sentinel-1, Sentinel-2, SRTM) with data preprocessing, machine learning (Random Forest), and SHAP interpretation to understand variable importance. Estimating canopy height and aboveground biomass and mapping forest ecosystem services for monitoring and climate research. Case study combining GEDI, Sentinel, and SRTM data. Python gedi sentinel-1 sentinel-2 srtm geopandas rasterio Pandas random forest shap	[Online] Analyzing Geospatial Forest Data with Geopandas and Rasterio

Title & Speakers

Event

Forest Modeling and Ecosystem Services Evaluation Through a Data-Driven Python Workflow 2025-10-16 · 14:00

Laya Zeinali – PhD candidate @ Tarbiat Modares University

Exploring how to model forest structure and quantify ecosystem services using Python and Earth observation data (GEDI, Sentinel-1, Sentinel-2, SRTM) with data preprocessing, machine learning (Random Forest), and SHAP interpretation to understand variable importance. Estimating canopy height and aboveground biomass and mapping forest ecosystem services for monitoring and climate research. Case study combining GEDI, Sentinel, and SRTM data.

Python gedi sentinel-1 sentinel-2 srtm geopandas rasterio Pandas random forest shap

[Online] Analyzing Geospatial Forest Data with Geopandas and Rasterio

Showing 1 result