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.

开源矢量地理数据获取与预处理工具(POI/AOI/行政区/路网/土地利用)

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

Code and models for efficient training on the BigEarthNet dataset for Land Use Land Cover classification

Land cover mapping of the Orinoquía region in Colombia, in collaboration with Wildlife Conservation Society Colombia. An #AIforEarth project

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

Python for Land Use Suitability Analysis Tools

Groundwater pumping estimation in Arizona using remote sensing datasets and machine learning

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

Offline version of the GCAM land allocation module

Global land-use and land-cover (LULC) data under historical, current, and future climatic conditions.

Biweekly mapping of land use and land cover using MODIS time series (MOD13Q1) and LSTM Neural Networks.

R Client Library for Land Cover Classification System Web Service

This repository holds code for PSRC data science projects.

Land Cover Classification System Web Service

The URBANMOD-ZIPF, a global-scale urban land expansion model that preserves Zipf's Law of urban sizes.

The source code of the Sentinel-2 Land Cover Explorer has been moved to https://github.com/Esri/imagery-explorer-apps

Python Client Library for Land Cover Classification System Web Service

Land Cover Classification System Database Model

Creates mock properties and simulates LUP based on forestry regulations