Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.

Open framework for calculating spatial urban sprawl indices and performing disaggregated population estimates using open data

Satsense is a Python library for land use/cover classification using satellite imagery

A Simple Data Explorer for NYC's PLUTO Tax Lot Dataset

Offline version of the GCAM land allocation module

A tool for computing accessibility measures, supporting aggregation, variable limits, and intermodality.

Web del proyecto SIOSE-INNOVA (CSO2016-79420-R)

Papers for Copernicus Land Monitoring Services evolution - based on H2020 ECoLaSS project

Homepage for the VisionEval project

Load NYC PLUTO 16v2 dataset into a MySQL database

R implementation of the Greenhouse Gas Value Calculator

Settlement System Dataset for China. Please check our website for detail https://mikemengmengli.github.io/cscproject/

Multi-scale spatial analyses for the delimitation and management of protected area buffer zones

Project assessing the impact of a solar installation on the deforestation in Kauai

Agent-based model representing the competition for land between stakeholders of farming and herding

The NMC model, a sequel of the Musical Chairs model, explores how land use competition could be constrained by cooperation and social institutions.