There are 6 repositories under land-cover topic.
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.
Classification of the Hyperspectral Image Indian Pines with Convolutional Neural Network
LANDSAT Time Series Analysis for Multi-temporal Land Cover Classification using Machine Learning techniques in Python and GUI development for automation of the process.
Land Cover Change Detection using Satellite Image Segmentation.
Land cover mapping of the OrinoquĂa region in Colombia, in collaboration with Wildlife Conservation Society Colombia. An #AIforEarth project
[ISPRS 2024] LoveNAS: Towards Multi-Scene Land-Cover Mapping via Hierarchical Searching Adaptive Network
Satsense is a Python library for land use/cover classification using satellite imagery
Reproducible remote sensing analysis using Google Earth Engine (GEE) to identify vegetation change in Columbia.
QGIS Plugin 'Curve Number Generator' has multiple algorithms to generate the curve number layer for any area of interest using different datasets.
This repository contains the computer code of a semi-automated framework for land cover mapping using OBIA and local USPO
LINDER (Land use INDexER) is an open-source machine-learning based land use/land cover (LULC) classifier using Sentinel 2 satellite imagery
A web mapping app to test, tweak and train the land cover classification from a deep neural network model built by @microsoft
R Client Library for Web Land Trajectory Service
Code repository for the ENS Challenge Data 2021 by Preligens
Segmentation for land cover using raw satellite data (Sentinel 2La)
GEE code for national-scale land cover classification using Sentinel imagery
TiSeLaC ECML/PKDD 2017 discovery challenge solution
A crash course in analysing spatial patterns of the landscape using R
R Client Library for Land Cover Classification System Web Service
Land Use and Land Cover (LULC) Classification using Convolutional Neural Networks and Transfer Learning
Biweekly mapping of land use and land cover using MODIS time series (MOD13Q1) and LSTM Neural Networks.
Land Cover Classification System Web Service
Python Client Library for Land Cover Classification System Web Service
The source code of the Sentinel-2 Land Cover Explorer has been moved to https://github.com/Esri/imagery-explorer-apps
Land Cover Classification System Database Model
Land Cover Classification System Web Service Specification
Hackathon "Automatic land cover mapping" at OpenGeoHub Summer School 2023
Water Accounting+ dashboard
Exploring NYC's DEP Citywide Parcel-Based Impervious Area GIS Study.
Hosting repository for the RLCMS methodology and code using GEE
This project is to find the land cover on a satellite image using machine learning models. This project uses CNN and SVM as Hybrid to do so.
Papers for Copernicus Land Monitoring Services evolution - based on H2020 ECoLaSS project
32 satellite imagery maps of Sri Lanka from 2017-2024, ranging from normal RGB, to high contrast versions, to gridded land cover / land use mapped by our in-house machine learning models.