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 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.
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 repository is Fresh and Furious' entry to the NERC COVID-19 Hackathon 3: Ecosystem Services.
Add a description, image, and links to the urban-greenspace topic page so that developers can more easily learn about it.
To associate your repository with the urban-greenspace topic, visit your repo's landing page and select "manage topics."