Computational tools for urban analysis

A Machine Learning Approach to Forecasting Remotely Sensed Vegetation Health in Python

Land surface classification using remote sensing data with unsupervised machine learning (k-means).

Accessibility Toolbox for R and ArcGIS

A lightweight and customizable web GIS platform for the state of Goa, India. Designed as a community maintained tool for hyperlocal spatial data exploration and decision making.

Implement of neural networks on 'UC Merced Land Use' dataset with PyTorch

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

Calculate accessibility from OD matrix on Python

OpenStreetMap: Find residential areas with too few buildings in them

We provide a pixel level training dataset for landuse classification (four categories - Green, Water, Barren land and Built up Areas) using google earth engine for India. All associated scripts are also provided.

An interface for managing SWATPlus input and output files to aid in implementing, and visualizing the impact of land use changes on catchment hydrology in the SWATPlus model

A post-processing, interactive visualization, and analysis tool to synthesize multi-scenario, multi-watershed outputs from process-based geospatial models WEPP and SWAT

Land Use /Land Cover Classification using PyTorch with the RGB EuroSat Dataset

Workflow to compute habitat connectivity based on land-use/land-cover data

TMG's Integrated Land Use, Transportation, Environment

Ressources pour l'exploitation de l'occupation du sol à 2 dimensions des Hauts-de-France

Synthesize multi-scenario, multi-watershed outputs from process-based geospatial model WEPP (WEPPcloud) using this post-processing, interactive visualization, and analysis tool. A Shiny Web app implementation to assist in targeted management using WEPPcloud simulated outputs.

Google Earth Engine Application in the field of Climate change and Earth system monitoring by analysing climatic, physical and biophysical data.

🗺️ 全國土地使用分區GeoJSON下載平台

Tools for extracting and preparing Digital Earth Australia Satellite Multi-Spectral Images for use in Deep Learning Machine models.

Spatial analysis of agricultural land use trends in Illinois with a focus on the Chicagoland area and collar counties in northeastern Illinois.

The elaborated documentation imported from the previous Confluence wiki (https://www.wiki.ed.ac.uk/display/CRAFTY)

Interactive Shiny Dashboard for monitoring multi-year Land Use / Land Cover (LULC) changes in Istanbul using spatial and statistical visualizations.

Chaîne de traitements pour la segmentation multiclasses de l'occupation du sol.

A map tool for comparing places

Associated work available in below link

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

A spatial web application for visualizing fisher equivalent territories

Code and data used during the hackathon Code4Green by the team team_cli07_landscapeoptimizer

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