A python Tkinter widget to display tile based maps like OpenStreetMap or Google Satellite Images.

An open-source benchmark framework for evaluating state-of-the-art deep learning approaches for image classification in Earth Observation (EO)

A simple python script that, given a location and a date, uses the Nasa Earth API to show a photo taken by the Landsat 8 satellite. The script must be executed on the command-line.

Multiband spectro-radiometric satellite image analysis with K-means cluster algorithm

MSc thesis - University of Twente.

Guia para el acceder a OTHERNET e instalar un punto de acceso wifi local para disponer de un repositorio de datos metereológicos, noticias, Wikipedia, mensajes y archivos procedentes de un enlace de datos con un satélite geoestacionario.

This Project is Semantic Segmentation of High-Resolution Multi-Spectral Optical Satellite Images: A Deep Learning-based Approach for Monitoring Deforestation

Fully automatic pipeline to download a set of satellite images from the ESA Copernicus Dataspace Ecosystem and do the post processing

Road Segmentation from Satelite images using custom Unet model

Using python3 beautifulsoup, download satelite-images.

IMAGE CLASSIFICATION w/ hybrid classification algorithms

This repository consolidate various analysis on EarthDaily Agro services and conference contributions.

Image classification in the LANDSAT and SENTINEL satellites images with Google Earth Engine

Landcover classification of satelite images

Python library/CLI client for sat4envi data

This project implements clustering on satellite images to analyze the distribution of green areas and buildings. It aims to evaluate the livability of regions for sustainable urban development using K-means clustering techniques.

Analyzing urban green cover changes using satellite imagery and Google Earth Engine (GEE). This project utilizes remote sensing techniques to assess vegetation elasticity, land use changes, and sustainability in urban environments, contributing to SDG 15 (Life on Land) and climate resilience. 🚀🌍

Use this repository as a baseline to Build Your Own Analytic based on metrics and imagery data following your business logic.

Python library/CLI client for sat4envi data

This project uses satellite imagery to classify different land cover types such as vegetation, water, and urban areas. It leverages machine learning techniques to automate the detection and mapping of land features.