Application of deep learning for earth observation.

This work discusses how high resolution satellite images are classified into various classes like cloud, vegetation, water and miscellaneous, using feed forward neural network. Open source python libraries like GDAL and keras were used in this work. This work is generic and can be used for satellite images of any resolution, but with MX band sen…

Executable Research Compendium para a geração de mapas de Uso e Cobertura da Terra utilizando Cubos de dados de imagens de Satélite

This project focuses on land use and land cover classification using Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). The classification task aims to predict the category of land based on satellite or aerial images.

This repository is intended to provide a set of QGIS tools to facilitate land use/land cover construction.

This repo contains javascript code used in Google Earth engine to perform various Geospatial Data analysis tasks on satellite data. The code utilizes Google earth engines own archive of Satellite data.