This is a R toolkit and developer version package to estimate multidimensional aspects of greenness and nature exposure, such as availability, accessibility and visibility using various geospatial data and models

Developing a modelling system to quantify features of land use in urban environments, UK based

Term project for the course Spatial Statistics and Spatial Machine learning.

iOS survey app for greenspace research using Apple's ResearchKit Framework

Codebase and datasets for reproducing a study of associations between greenness change and mental distress prevalence change, stratified by housing tenure

Automatization of Indicator Development for Green Space Health Research in QGIS

Repository for exam project of Spatial analytics course 2021 at Aarhus University. Project name: 'Happiness and green urban spaces: how green is happiness?' The project was done by Ruta Slivkaite and Bianka Szöllősi.

Project to investigate and develop spatial data-driven Geo-AI models (Convolutional Neural Network) to identify urban greenspace from Satellite images by integrating multiple data sources (e.g. vector data of urban parks)

GWR model analysing the relationship between access to greenspace and deprivation in Bradford

Exploratory analysis and report on open space in North Lawndale neighborhood of Chicago.

Provides tools to access and analyze multi-band greenspace seasonality data cubes (available for 1,028 major global cities) and global NDVI data from the ESA WorldCover 10m Annual Composites Dataset.