landuse

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).

An open web GIS platform with a url API built with Mapbox GL. Prompted from Goa, India.

Accessibility Toolbox for R and ArcGIS

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

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

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

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

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

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

TMG's Integrated Land Use, Transportation, Environment

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

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.

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