📦🐍 Python package to model and forecast the risk of deforestation

🌍 📝 Modelling and forecasting deforestation in the tropics

MUSE is an urban expansion-oriented open-access land change simulation software built upon cellular automata modeling scheme. It used multiple patch generation engines to emulate the process of urban development, thus scaling up the representation of urban development events from cell to patch level, in line with real-world mechanisms.

Online documentation for Collect Earth Online.

A land use change and environmental assessment tool based on preconfigured data animal population numbers based on negative emissions allowance

A Google Earth Engine script for detecting multi-decadal vegetation change using Landsat Collection 2 time series. Implements 8-class change detection based on dynamic NDVI thresholds, Mann-Kendall trend significance testing, and linear trend analysis.

Python code accompanying: "Feeding-efficiency-gains-can-increase-the-greenhouse-gas-mitigation-potential-of-Tanzania's-dairy-sector"

Global sensitivity analysis for climate/land-use change co-extinctions analysis

R code for Mariana Orsini's MSc thesis

A simple factor-cluster analysis on global deforestation patterns based on FAO data.

Data analysis of urban and land-use transformations in the Northern Coast of Rio Grande do Sul, Brazil.