Study about Urban Green Spaces in Athens GR, using the Google Earth Engine platform, along with Landsat 8 and 9 imagery and Random Forest supervised machine learning algorithms.
This project estimates tree crown volumes using 3D modeling and high-resolution LiDAR datasets (AHN4 and Kavel_10) in Nijmegen, Netherlands. The study focuses on tree detection, biophysical parameter estimation, and crown volume mapping, highlighting applications in urban green space management and ecosystem services. Tools: Python, LiDAR, GIS soft
This directory analyzes Oakland's street trees. First, it visualizes the taxonomy of Oakland's trees. It then maps them in several ways. Finally, it creates a simple model to identify the trees most likely to have problems.
Repository created for Env Justice & Economics final paper
This repository is Fresh and Furious' entry to the NERC COVID-19 Hackathon 3: Ecosystem Services.
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