Techniques for deep learning with satellite & aerial imagery

Satellite imagery for dummies.

Global shoreline mapping tool from satellite imagery

A curated list of resources focused on Machine Learning in Geospatial Data Science.

Spatiotemporal Arrays, Raster and Vector Data Cubes

GeoTorchAI: A Framework for Training and Using Spatiotemporal Deep Learning Models at Scale

A python package that extends Google Earth Engine.

Satellite Image Classification using semantic segmentation methods in deep learning

1st place solution to the Satellite Remote Sensing Image Change Detection Challenge hosted by SenseTime

A QGIS plugin tool using Segment Anything Model (SAM) to accelerate segmenting or delineating landforms in geospatial raster images.

The repository contains the implementation of different machine learning techniques such as classification and clustering on Hyperspectral and Satellite Imagery.

DeepGlobe Land Cover Classification Challenge遥感影像语义分割

AiTLAS implements state-of-the-art AI methods for exploratory and predictive analysis of satellite images.

Algorithms for computing global land surface temperature and emissivity from NASA's Landsat satellite images with Python.

crop classification using deep learning on satellite images

A curated list on building detection from remote sensing images

ParaView plugins

Building a Yolov8n model from scratch and performing object detection in optical remote sensing images and videos.

Beach-face slope estimation from satellite-derived shorelines, extension of the CoastSat toolbox.

[NeurIPS 2023] Fine-Grained Cross-View Geo-Localization Using a Correlation-Aware Homography Estimator