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62 search results found

Techniques ⭐ 7,678

Techniques for deep learning with satellite & aerial imagery

Awesome Geospatial ⭐ 3,703

Long list of geospatial tools and resources

Awesome Satellite Imagery Datasets ⭐ 3,381

🛰️ List of satellite image training datasets with annotations for computer vision and deep learning

Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

Raster Vision ⭐ 1,956

An open source library and framework for deep learning on satellite and aerial imagery.

GRASS GIS - free and open-source geospatial processing engine

Change Detection Review ⭐ 352

A review of change detection methods, including codes and open data sets for deep learning. From paper: change detection based on artificial intelligence: state-of-the-art and challenges.

Eye In The Sky ⭐ 248

Satellite Image Classification using semantic segmentation methods in deep learning

Awesome_satellite_benchmark_datasets ⭐ 231

Supplementary material for our paper "THERE IS NO DATA LIKE MORE DATA" is provided.

Geospatial Machine Learning ⭐ 196

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

Deep Learning for Satellite Imagery

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

Callisto Dataset Collection ⭐ 142

A list of datasets aiming to enable Artificial Intelligence applications that use Copernicus data.

Rsgislib ⭐ 130

Remote Sensing and GIS Software Library; python module tools for processing spatial data.

Raster4ml ⭐ 114

A geospatial raster processing library for machine learning

Semi-automatic tool for manual segmentation of multi-spectral and geo-spatial imagery.

Pytorch Psetae ⭐ 98

PyTorch implementation of the model presented in "Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention"

Ml4eo Bootcamp 2021 ⭐ 83

Machine Learning for Earth Observation Training of Trainers Bootcamp

Pycrop Yield Prediction ⭐ 80

A PyTorch Implementation of Jiaxuan You's Deep Gaussian Process for Crop Yield Prediction

Hyperspectral_image_analysis_simplified ⭐ 77

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

Land Cover To Land Use Classification ⭐ 47

Satellite image processing pipeline to classify land-cover and land-use

Hephaestus ⭐ 44

Hephaestus: A large scale multitask dataset towards InSAR understanding

Label Pixels ⭐ 42

Label-Pixels is the tool for semantic segmentation of remote sensing images using Fully Convolutional Networks. Initially, it is designed for extracting the road network from remote sensing imagery and now, it can be used to extract different features from remote sensing imagery.

Downscale Satellitelst ⭐ 35

A python class for enhancing the spatial resolution of satellite-derived Land Surface Temperatures (LST) using statistical downscaling.

Unstructured Change Detection Using Cnn ⭐ 34

Unstructured Change detection in satellite imagery

🛰️ Python library and CLI tools for processing geospatial imagery for ML

UAV related Remote Sensing Toolbox

Geospatial Learn ⭐ 24

A python library for geo-spatial processing and machine learning

Ap Latam ⭐ 23

Detection of slums and informal settlements from satellite imagery

Lightweight Temporal Attention Pytorch ⭐ 23

A PyTorch implementation of the Light Temporal Attention Encoder (L-TAE) for satellite image time series. classification

Planesnet Detector ⭐ 23

Detect airplanes in Planet imagery using machine learning

Planesnet ⭐ 22

Labeled training data for detection of aircraft in Planet satellite imagery

Remotior_sensus ⭐ 20

A Python package that allows for the processing of remote sensing images and GIS data.

Remote Sensing for Movement Ecology

Deepicedrain ⭐ 19

Mapping and monitoring deep subglacial water activity in Antarctica using remote sensing and machine learning, with ICESat-2!

Shipsnet Detector ⭐ 19

Detect container ships in Planet imagery using machine learning

Orthoseg ⭐ 18

OrthoSeg makes it easy to train neural networks to segment orthophotos.

Python For Remote Sensing ⭐ 15

python codes for remote sensing applications will be uploaded here. I will try to teach everything I learn during my projects in here.

DeepGeo: Deep Learning for Earth Observation data ToolBox

Solar Panel Segmentation ⭐ 13

A U-Net for solar panel identification and segmentation

Hydromst ⭐ 11

Source codes for groundwater pumping prediction using integrated remote sensing datasets and machine learning

Coastguard ⭐ 11

Coastal Observation + Analysis using Satellite-derived Timeseries, Generated Using AI + Real-time Data

Deeppvmapper ⭐ 11

Automated pipeline for large scale detection of solar arrays in France

Satellite Imagery Road Extraction ⭐ 10

Developed a Software for semantic segmentation of remote sensing imagery using Fully Convolutional Networks (FCNs). Initially, this software developed for extracting the road network from high-resolution remote sensing imagery. And now, this software can be used to extract various features (Semantic segmentation of remote sensing imagery). This project can also extract from Vector Data. This is part of my Internship at ISRO (Indian SPace Research Organization)'s NRSC (National Remote Sensing Cen

Making Deep Learning for Earth Observation more easy

Automatic detection of impervious surfaces

Remote Sensing ⭐ 8

And this Repository made the Journey of FEZtool.com

Missing Pixel Filler ⭐ 7

missing-pixel-filler is a python package that, given images that may contain missing data regions (like satellite imagery with swath gaps), returns these images with the regions filled.

Obbstacking ⭐ 7

Repo for the OBBStacking: An Ensemble Method for Remote Sensing Object Detection

Remotesensingandcomputervision ⭐ 7

This contains personal reading list for remote sensing and applications of computer vision

Landsurfaceclustering ⭐ 6

Land surface classification using remote sensing data with unsupervised machine learning (k-means).

Dataselectionmaps ⭐ 6

Enhanced spatio-temporal electric load forecasts with less data using active deep learning

Satellite_led_liverpool ⭐ 6

Data and code for the paper "Remote Sensing-Based Measurement of Living Environment Deprivation - Improving Classical Approaches with Machine Learning", by Dani Arribas-Bel, Jorge Patiño and Juanca Duque

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

Wildfire_research_resources ⭐ 6

A repository to be used as a resource in the wildfire area like the detection, forecasting, and segmentation of wildfires 🔥, after the heart-breaking wildfires in Turkey ❤️

Crop Maml ⭐ 6

Learning to predict crop type from heterogeneous sparse labels using meta-learning

Awesome Remote Sensing Relative Radiometric Normalization Datasets ⭐ 6

A. Moghimi, A. Mohammadzadeh, T. Celik and M. Amani, "A Novel Radiometric Control Set Sample Selection Strategy for Relative Radiometric Normalization of Multitemporal Satellite Images," in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 3, pp. 2503-2519, March 2021, doi: 10.1109/TGRS.2020.2995394.

Floating Marine Debris Data ⭐ 6

This repository contains data from Sentinel-2 imagery on floating marine debris, with annotations for six debris classes, including plastic, driftwood, seaweed, pumice, sea snot, and sea foam.

Crop Yield Predictor ⭐ 5

A tool which is capable of making predictions of cereal and potato yields for districts of the Slovak Republic.

Atrain Cloudseg ⭐ 5

Official GitHub repository for the A-Train Cloud Segmentation Dataset.

SOMOSPIE (Soil Moisture Spatial Inference Engine) consists of a Jupyter Notebook and a suite of machine learning methods to process inputs of available coarse-grained soil moisture data at its native spatial resolution. Features include the selection of a geographic region of interest, prediction of missing values across the entire region of interest (i.e., gap-filling), analysis of generated fine-grained predictions, and visualization of both predictions and analyses.

Multi Temporal Crop Classification Baseline ⭐ 5

Baseline model for crop type segmentation as part of the HLS FM downstream task evaluations

Debrisscan ⭐ 5

A tool to automatically label, classify, and count marine debris in your aerial imagery. Designed to automate the tedious parts of standing stock surveys for shoreline stranded marine debris. Powered by AI!

Forest_drought_forecasting ⭐ 5

Forecasting of forest drought impacts in Switzerland from satellite imagery, weather reanalysis and remote sensing data. Pixel-wise forecasts with feature engineering to provide model explainability.

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