Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
awesome-earthobservation-code
A curated list of awesome tools, tutorials, code, projects, links, stuff about Earth Observation, Geospatial Satellite Imagery
https://github.com/acgeospatial/awesome-earthobservation-code
Last synced: 3 days ago
JSON representation
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`Python` processing of optical imagery (non deep learning)
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Processing imagery - post processing
- Intro to Python GIS - Great free 3-day course by the University of Helsinki on GIS processing with Python
- get_river_width - Find the river width (and other properties) from a masked water image `Python`
- extract_water - Extract water from nIR imagery `Python`
- StarFM for Python - The STARFM fusion model for `Python` (image fusion)
- Remote Sensing indicies calc - Calculate spectral remote sensing indices from satellite imagery
- EarthPy - A package built to support working with spatial data using open source python. [docs](https://earthpy.readthedocs.io/en/latest/)
- RasterFrames / pyrasterframes - brings together Earth-observation (EO) data access, cloud computing, and DataFrame-based data science. [docs](https://rasterframes.io/)
- SIF tools - some tools for accessing OCO-2 data
- SIAC - A sensor invariant Atmospheric Correction (SIAC) [alg doc](http://www2.geog.ucl.ac.uk/~ucfafyi/Atmo_Cor/)
- S2_TOA_TO_LAI - From Sentinel 2 TOA reflectance to LAI
- cresi - Road network extraction from satellite imagery, with speed and travel time estmates
- 6S_emulator - Atmospheric correction in Python using a 6S emulator
- bv - Quickly view satellite imagery, hyperspectral imagery, and machine learning image outputs directly in your iTerm2 terminal. `Python`
- mapchete - Tile-based geodata processing using rasterio & Fiona `Python`
- unmixing - Interactive tools for spectral mixture analysis of multispectral raster data in `Python`
- landsat and sentinel fusion - Complementarity Between Sentinel-1 and Landsat 8 Imagery for Built-Up Mapping in Sub-Saharan Africa `Python`
- Planet Movement - Find and process Planet image pairs to highlight object movement. `Python`
- cedar-datacube - cedar - Create Earth engine Datacubes of Analytical Readiness `Python` [docs](https://ceholden.github.io/cedar-datacube/master/)
- stems - Spatio-temporal Tools for Earth Monitoring Science - Spatio-temporal Tools for Earth Monitoring Science `Python` [docs](https://ceholden.github.io/stems/master/)
- ipyearth - An IPython Widget for Earth Maps `Python`
- Python-for-remote-sensing - `Python` codes for remote sensing applications will be uploaded. [blog](https://earthobserv.com/)
- esda dissertation - MSc Energy Systems & Data Analytics dissertation project notebooks - identifying solar PV from aerial imagery with computer vision `Python`
- geff_notebooks - Jupyter notebooks to post-process fire danger data using `Python`/`xarray`
- river-width - Extracts water features from 4 band NAIP imagery and calculates river metrics. `Python`
- pyresample - Geospatial image resampling in `Python`
- spatialist - A `Python` module for spatial data handling
- CometTS - Comet Time Series Toolset for working with a time-series of remote sensing imagery and user defined polygons
- Telluric - telluric is a `Python` library to manage vector and raster geospatial data in an interactive and easy way
- onearth - High-performance web services for tiled raster imagery and vector tiles `Python`
- geocube - Tool to convert geopandas vector data into rasterized xarray data. `Python` [docs](https://corteva.github.io/geocube/stable/)
- verde - Processing and gridding spatial data using Green's functions
- s2p - Satellite Stereo Pipeline `Python`
- xcube - xcube is a `Python` package for generating and exploiting data cubes powered by xarray, dask, and zarr
- geonotebook - A Jupyter notebook extension for geospatial visualization and analysis `Python`
- tatortot - Prototype for a simple image annotation tool `Python`
- tiletanic - `Python` library to support generalized geographic tiling schemes
- openaq-s5 - Map openaq data onto Sentinel5P data using AWS lambda
- vegetation health - Predicting vegetation health from precipitation and temperature
- Satellite-Image-Analysis - PlanetScope, Landsat-8 and Sentinel-2 Image analysis `Python` codes
- felicette - Satellite imagery for dummies. `Python`
- CostalSat - Global shoreline mapping tool from satellite imagery `Python`
- Python-Remote-Sensing-Scripts - `Python` 3. X scripts for remote sensing processing
- fc-up42 - UP42 Block for Fractional Cover calculation from Sentinel 2 L2A Data `Python`
- nansat - Scientist friendly Python toolbox for processing 2D satellite Earth observation data. `Python`[docs](https://nansat.readthedocs.io/en/latest/index.html)
- nansat-lite - nansat-lite is not a full nansat build for `Python` 3.5. Only bits of code from main classes, to start with. Eventually, if need it, more code will be added.
- IEO - Irish Earth Observation (IEO) remote sensing data processing Python module `Python`
- IEOtools - Tools for managing Earth observation data. Currently only supports Landsat imagery `Python`
- pykic - 'Python' module for remote sensing and GIS domain (image/signal, vector, miscellaneous processing)
- ukis-csmask - masks clouds and cloud shadows in Sentinel-2, Landsat-8, Landsat-7 and Landsat-5 images `Python`
- jeolib-pyjeo - pyjeo is a library for image processing for geospatial data implemented in JRC Ispra. `Python`
- pyrgis - This repository cointains the source code of the 'pyrsgis' `Python` package.
- EOReader - Opensource `Python` library reading optical and SAR sensors, loading and stacking bands in a sensor-agnostic way.
- LandSurfaceClustering - Land surface classification using remote sensing data with unsupervised machine learning (k-means) `Python`
- Opensource_OBIA_processing_chain - An open-source semi-automated processing chain for urban OBIA classification.
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Cloud Native Geospatial
- stac-utils - Tools for working with SpatioTemporal Asset Catalogs (STAC) (perhaps worth going here first for STAC) `Python` `Javascript`
- async-cog-reader - Read Cloud Optimized GeoTiffs without GDAL`Python`
- COG pptx/pdf - talk on COG
- aws-sat-api-py - Process Satellite data using AWS Lambda functions
- GeoLambda - Create and deploy Geospatial AWS Lambda functions `Python`
- rio-viz - Visualize Cloud Optimized GeoTIFF in browser `html` `Python`
- Sentinel-s3 - `Python` libraries for extracting Sentinel-2's metadata from Amazon S3
- geocore - GeoCore is an Open Source Cloud Native (AWS) Geospatial Catalog | GeoCore est un catalogue géospatial Open Source Cloud Native (AWS)
- cng-workshop - Intro to cloud-native geospatial workshop
- cloud-native-geospatial - resource [introduction to cloud native geospatial](https://ua-datalab.github.io/cloud-native-geospatial/)
- pystac - `Python` library for working with any SpatioTemporal Asset Catalog (STAC)
- stactools - Command line utility and `Python` library for STAC
- stac-server - A Node-based STAC API, AWS Serverless, OpenSearch `Javascript`
- stac-fastapi - STAC API implementation with FastAPI. `Python`
- stac-fastapi-pgstac - PostgreSQL backend for stac-fastapi using pgstac
- STAC Spec - SpatioTemporal Asset Catalog specification - making geospatial assets openly searchable and crawlable
- stac-validator - Validator for the stac-spec `Python`
- stackstac - Turn a list of STAC items into a 4D xarray DataArray `Python`
- stac-nb - STAC in Jupyter Notebooks `Python`
- qgis-stac-plugin - QGIS plugin for reading STAC APIs `Python`
- easystac - A `Python` package for simple STAC queries
- stac-utils - Provides a class interface for running custom algorithms on STAC ItemCollections `Python`
- stac-asset - Read and download STAC Assets, using a variety of authentication schemes
- elastic search - Elasticsearch backend for stac-fastapi with Opensearch support. `Python`
- stac4s - A `Scala` library with primitives to build applications using the SpatioTemporal Asset Catalogs specification
- stac-rs - `Rust` implementation of the SpatioTemporal Asset Catalog (STAC) specification
- stac-table
- stac-fields - A minimal STAC library that contains a list of STAC fields with some metadata and helper functions for styling as HTML. `Javascript`
- titiler-pgstac - TiTiler + PgSTAC
- stac-api-validator - A STAC API validation client `Python`
- xpystac - For extending xarray.open_dataset to accept pystac objects `Python`
- stac-pydantic - Pydantic data models for the STAC spec `Python`
- stac-migrate - A tool to migrate Items, Catalogs and Collections from old versions to the most recent one. `Javascript`
- stac-node-validator - Simple validator for STAC Items, Catalogs, and Collections. STAC 1.0.0 compliant! `Javascript`
- stac-geoparquet - Convert STAC items to geoparquet. `Python`
- stac-index - A service that lists all available and registered STAC catalogs and APIs.
- stac-check - Linting and validation tool for STAC assets
- stac-terminal - Output info on STAC Items in the terminal
- stac-layer - Visualize a STAC Item or Collection on a Leaflet Map
- pgstac-rs - `Rust` interface to pgstac
- COG Validator - Cloud Optimized GeoTIFF validation service
- titiler - A modern dynamic tile server built on top of `FastAPI` and `Rasterio/GDAL`.
- cogeo-mosaic - Create and use COG mosaic based on mosaicJSON `Python`
- Sentinel-2-cog - Convert Sentinel-2 JPEG 2000 to COG with AWS Lambda `Python`
- COG Dumper - Dumps tiles out of a cloud optimized geotiff `Python`
- aiocogeo - Asynchronous cogeotiff reader `Python`
- cogeotiff - High performance cloud optimised geotiff reader
- ecw-converter - Dockerised `Python` scripts & Nextflow pipeline for converting ecw files to either geotiffs or Cloud Optimised Geotiffs (COGs)
- pystac-client - `Python` client for searching STAC APIs
- pgstac - Schema, functions and a python library for storing and accessing STAC collections and items in PostgreSQL
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Download
- EODAG - Command line tool and a plugin-oriented Python framework for searching, aggregating results and downloading remote sensed images while offering a unified API for data access regardless of the data provider.
- data-prep-scripts - This collection of `R` and `Python` scripts can be used to download data and perform basic data processing functions such as georeferencing, reprojecting, converting, and reformatting data. All scripts are available for download from the LP DAAC User Resources [BitBucket Code Repository](https://git.earthdata.nasa.gov/projects/LPDUR).
- Stream NASA data directly into Python objects - Skip the download! Stream NASA data directly into Python objects from [blog post](https://medium.com/pangeo/intake-stac-nasa-4cd78d6246b7)
- Sedas API - `Python` client library for the SeDAS API
- esa_sentinel - ESA Sentinel Search & Download API
- get_modis - Downloading MODIS data from the USGS repository `Python`
- landsatexplore - Search and download Landsat scenes from EarthExplorer. `Python`
- pylandsat - Search, download, and preprocess Landsat imagery `Python`
- Sentinel-download - Automated download of Sentinel-2 L1C data from ESA (through wget) `Python`
- sentinelsat - Search and download Copernicus Sentinel satellite images [sentinelsat docs](https://sentinelsat.readthedocs.io/en/stable/) `Python`
- LANDSAT-Download - Automated download of LANDSAT data from USGS website
- Landsat-Util - A utility to search, download and process Landsat 8 satellite imagery `Python`
- sat-extractor - Extract Satellite Imagery from public constellations at scale `Python`
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Case studies / Projects
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Povetry predition using satellite imagery - Poverty Prediction by Combination of Satellite Imagery
- Python from space - `Python` Examples for Remote Sensing
- count blue pixels - This project is an experiment in using simple image processing techniques on satellite images downloaded from Google Maps in order to quantify the relative density of temporary shelters in adjacent qudarants. `Python` `Ruby`
- Satellite imagery analysis with Python - Getting acquainted with the concept of satellite imagery data and how it can be analyzed to investigate real-world environmental and humanitarian challenges. `Python` `Jupyter Notebooks` [associated blog](https://medium.com/analytics-vidhya/satellite-imagery-analysis-with-python-3f8ccf8a7c32)
- Satellite imagery in Pakistan - This repository contains a study how we can examine the vegetation cover of a region with the help of satellite data. The notebook in this repository aims to familiarise with the concept of satellite imagery data and how it can be analyzed to investigate real-world environmental and humanitarian challenges.
- SentinelBot - A twitter bot which processes raw sentinel data `Python` [SentinelBot on twitter](https://twitter.com/sentinel_bot)
- ap-latem - Detection of slums and informal settlements from satellite imagery `Python`
- local_structire_wpb-severity - Analysis of drone imagery to characterize forest structure and severity of a tree killing insect `Python`
- Truck_Detection_Sentinel2_COVID19 - This repository is designated to detecting trucks using Sentinel-2 data. `Python`
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
- Artificial Intelligence for Geospatial Analysis with Pytorch’s TorchGeo (multi parts) - An end-to-end deep learning geospatial segmentation project using Pytorch and TorchGeo packages - [code](https://gist.github.com/cordmaur/d050973aa3ed980023e9239183a2cb66#file-earthsurfacewater_medium_2-ipynb)
-
Reflectance / pre processing
- Landsat7 errors - Identifies errors in raw values of Landsat 7
- data-retrieval-in-EO - data-retrieval-in-EO, a project with reports from TU wien
- PyProSail - Python interface to the ProSAIL leaf/canopy reflectance model
- Py6S - A `Python`interface to the 6S Radiative Transfer Model
- prosail - `Python` bindings for the PROSAIL canopy reflectance model
- ACOLITE_MR - ACOLITE_MR: Atmospheric correction for aquatic applications of metre-scale satellites
- radiometric_normalization - Implementation of radiometric normalization workflows `Python`
- color_balance - Balance your colors! `Python`
-
Python libraries related to EO
- rasterio - Rasterio reads and writes geospatial raster datasets
- Xarray pyconuk 2018 - Code and slides for my talk at PyCon UK 2018 on XArray `Python`
- RasterStats - Summary statistics of geospatial raster datasets based on vector geometries. `Python`
- SatPy - `Python` package for earth-observing satellite data processing
- pyimpute - Spatial classification and regression using Scikit-learn and Rasterio `Python`
- dask-rasterio - Read and write rasters in parallel using Rasterio and Dask `Python`
- rioxarray - geospatial xarray extension powered by rasterio [docs](https://corteva.github.io/rioxarray/stable/)
- xarray-spatial - Raster-based Spatial Analysis for `Python`
- actinia core - Actinia Core is an open source REST API for scalable, distributed, high performance processing of geographical data that uses mainly GRASS GIS for computational tasks. `Python`
- actinia satellite plugin - This actinia plugin is designed for efficient satellite data handling, especially Landsat and Sentinel-2 scenes `Python`
- Whitebox Python - WhiteboxTools `Python` Frontend
- ukis-pysat - generic classes and functions to query, access and process multi-spectral and SAR satellite images
- rasterio - Rasterio reads and writes geospatial raster datasets
- actinia core - Actinia Core is an open source REST API for scalable, distributed, high performance processing of geographical data that uses mainly GRASS GIS for computational tasks. `Python`
-
Testing your code
- image-similarity-measures - Implementation of eight evaluation metrics to access the similarity between two images. `Python`
- fake-geo-images - A module to programmatically create geotiff images which can be used for unit tests. `Python`
-
Company specific examples
- Planet notebooks - interactive notebooks from Planet Engineering `Python`
- Planet-client-API - `Python` client for Planet APIs
- Maxar GDBx tools - Python SDK for using GBDX.
- gdbx-surface-water - Reservoir surface area detection with Digital Globe imagery and Bayesian methods
- SentinelHub-py - Download and process satellite imagery in Python using Sentinel Hub services.
- sentinel2-cloud-detector - Sentinel Hub Cloud Detector for Sentinel-2 images in `Python`
- Orbit predictor - Python library to propagate satellite orbits.
- up42-py - Python SDK for UP42, the geospatial marketplace and developer platform. `Python`
- S2-superresolution - Deep Learning-based algorithm to upsample all Sentinel-2 bands to 10m. Also an example how to use GPUs on UP42. `Python`
- icecube - Create time-series datacubes for supervised machine learning with ICEYE SAR images. `Python`
-
-
Earth Observation Introduction
- ESA newcomers guide - The aim of this guide is to help non-experts in providing a starting point in the decision process for selecting an appropriate Earth Observation (EO) solution.
- The state of satellites - The satellite systems we use to capture, analyze, and distribute data about the Earth are improving every day, creating bold new opportunities for impact in global development.
- satellite-imagery
- earth-observation
- Data Catalogs
- Landsats Enduring Legacy - pdf download over 600 pages of remote sensing!
- Earth Observation Text books - Earth Observation: Data, Processing and Applications is an Australian Earth Observation (EO) community undertaking to describe EO data, processing and applications in an Australian context and includes a wide range of local case studies to demonstrate Australia’s increasing usage of EO data.
- I Couldn't Find a Video Explaining Satellite Images, So I Made One
- How Radar Satellites See through Clouds (Synthetic Aperture Radar Explained)
-
Open EO
- Open EO - openEO develops an open API to connect `R`, `Python`, `JavaScript` and other clients to big Earth observation cloud back-ends in a simple and unified way.
- openeo-processes - Interoperable processes for openEO's big Earth observation cloud processing [website](https://processes.openeo.org/)
-
Remote Sensing.info
- RemoteSensing - Short tutorials and reference to useful software tools for the acquisition and processing of remote sensed Earth Observation data
- RSGISLib - The Remote Sensing and GIS software library (RSGISLib) is a collection of tools for processing remote sensing and GIS datasets. The tools are accessed using `Python` bindings.
- ARCSI - Software to automate the production of optical analysis ready data (ARD) from Landsat, Sentinel-2 and others
- eodatadown - The Earth Observation Data Downloader (EODataDown) is a tool for automatically downloading and processing EO data to an analysis ready data product. This software forms a core component of a monitoring system based on EO data.
-
Resources for `R`
-
Testing your code
- Geospatial R Books - some `R` books on geospatial
- R-Spatial - This book provides a short introduction to satellite data analysis with R.
- Remote Sensing analysis with R - Builds on above R-Spatial
- GDAL Cubes - Earth Observation Data Cubes from Satellite Image Collections. Also [here on github](https://github.com/appelmar/gdalcubes_R)
- R code for ML in Sat imagery - # Random Forest image classification Adapted from [stackoverflow](http://gis.stackexchange.com/a/57786/12899).
- RasterVIS - Methods for enhanced visualization and interaction with raster data. It implements visualization methods for quantitative data and categorical data, both for univariate and multivariate rasters. It also provides methods to display spatiotemporal rasters, and vector fields.
- Landsat - Processing of Landsat or other multispectral satellite imagery. Includes relative normalization, image-based radiometric correction, and topographic correction options.
- A Step-by-Step Guide to Making 3D Maps with Satellite Imagery in R - Walk you through [on] how to obtain the data required to make these types of maps, as well as the R code used to generate them
- lidR - `R` package for airborne LiDAR data manipulation and visualisation for forestry application. Plus [lidRplugins](https://github.com/Jean-Romain/lidRplugins) - Extra functions and algorithms for lidR package
- lidR - `R` package for airborne LiDAR data manipulation and visualisation for forestry application. Plus [lidRplugins](https://github.com/Jean-Romain/lidRplugins) - Extra functions and algorithms for lidR package
- whiteboxR - An R frontend of the advanced geospatial data analysis platform - [whitebox-tools](https://github.com/jblindsay/whitebox-tools).
- rnoaa - R interface to many NOAA data APIs
- MODISTools - Interface to the MODIS Land Products Subsets Web Services [Docs](https://docs.ropensci.org/MODISTools/)
- landsatlinkr - An automated system for creating spectrally consistent and cloud-free Landsat image time series stacks from a combination of MSS, TM, ETM+, and OLI sensors [project](http://jdbcode.github.io/LandsatLinkr/)
- ForestTools - Detect and segment individual tree from remotely sensed data
- Spatiotemporal Arrays: Raster and Vector Datacubes - Spatiotemporal Arrays, Raster and Vector Data Cube
- getSpatialData - An `R` package making it easy to query, preview, download and preprocess multiple kinds of spatial data [docs](https://jakob.schwalb-willmann.de/getSpatialData/)
- RStoolbox - RStoolbox is a R package providing a wide range of tools for your every-day remote sensing processing needs.
- rHarmonics - `R` package for harmonic modelling of time-series data
- rerddap - `R` client for working with ERDDAP servers [docs](https://docs.ropensci.org/rerddap/) reference the [ERDDAP Server](https://upwell.pfeg.noaa.gov/erddap/index.html)
- Spatial_Data_in_R - SWIRL-course on spatial data in `R`
- cognition-datasources - Standardized query interface for searching geospatial assets via STAC.
- caliver - caliver: CALIbration and VERification of gridded fire danger models `R`
- clip_time_series - create snippets of Landsat and Sentinel imagery
- RGISTools - Tools for Downloading, Customizing, and Processing Time Series of Satellite Images from Landsat, MODIS, and Sentinel
- Grassland-Species-Classification - Codes for: Javier Lopatin, Fabian E. Fassnacht, Teja Kattenborn, Sebastian Schmidtlein. Mapping plant species in mixed grassland communities using close range imaging spectroscopy. Remote Sensing of Environment 201, 12-23. `R`
- UAV-InvasiveSpp - Mapping invasive tree species in Chile using UAV `R`
- Peatland-carbon-stock - Codes for: Lopatin, J., et al. (2019). Using aboveground vegetation attributes as proxies for mapping peatland belowground carbon stocks. Remote Sens. Environ. 231, 111217 `R`
- SpeciesRichness-GLMvsRF-LiDAR - `R`-codes for: Lopatin, J., Dolos, K., Hernández, J., Galleguillos, M., Fassnacht, F. E. (2016): Comparing Generalized Linear Models and random forest to model vascular plant species richness using LiDAR data in a natural forest in central Chile. Remote Sensing of Environment 173, pp. 200–210. 10.1016/j.rse.2015.11.029
- tree_segmentation - LiDAR tree segmentation `R`
- swdt - Sentinel-1 Water Dynamics Toolkit `R`
- What_are_data_cubes - Analyzing and visualising spatial and spatiotemporal data cubes - Part I
- classifying_satellite_imagery_in_R - For this tutorial, we use Landsat 8 imagery from Calgary
- Landsat_land_surface_temperature - `R` Estimate land surface temperature using Landsat satellite imagery.
- planetR - `R` tools to search, activate and download satellite imagery from the Planet API.
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-
Languages other than `Python` and `R`
-
Testing your code
- Georust - A collection of geospatial tools and libraries written in `Rust`
- ArchGDAL docs
- GeoTrellis homepage - GeoTrellis is a geographic data processing engine for high performance applications. `Scala`
- Perl extension for GDAL - Geo:: GDAL - `Perl` extension for the GDAL library for geospatial data
- Global Forest Watch - Global Forest Watch: An online, global, near-real time forest monitoring tool
- stac4s - a `scala` library with primitives to build applications using the SpatioTemporal Asset Catalogs specification
- Orfeo ToolBox - An open-source project for state-of-the-art remote sensing, including a fast image viewer, apps callable from `Bash`, `Python` or QGIS, and a powerful `C++` API.
- pktools - pktools is a suite of utilities written in `C++` for image processing with a focus on remote sensing applications. It relies on the Geospatial Data Abstraction Library ([GDAL](http://www.gdal.org)) and OGR.
- Global Forest Watch - Global Forest Watch: An online, global, near-real time forest monitoring tool
- ArchGDAL - Julia - `Julia` A high level API for GDAL - Geospatial Data Abstract
- iris - Semi-automatic tool for manual segmentation of multi-spectral and geo-spatial imagery. `Javascript`
-
-
Training and learning
-
Testing your code
- EO College Github
- Andrew Cutts Github - I am an Earth Observation and Geospatial enthusiast, primarily using `Python` to automate and process images at scale using computer vision
- Geoprocessing with Python - GIS circa 2009 - This material is really old and some of it is outdated (not all, though!). One of these days I might get around to putting newer class materials online, but you're stuck with this for now.
- Python for Geospatial Analysis - A crashcourse introduction to using Python to wrangle, plot, and model geospatial data `Python`
-
-
Deep learning and Machine Learning
-
Testing your code
- future learn course - artificial intelligence for earth monitoring
- Robin Cole on satellite imagery and deep learning resources - Resources for deep learning with satellite & aerial imagery. <b>This is the best place to go for this topic</b> I've removed 95% of the associated links from awesome-eo-code as it is just a repetition.
-
-
GDAL of course
-
Testing your code
- GDAL tutorial - This blogpost gives in an introduction to GDAL/OGR and explains how the various command line tools can be used.
- An Introduction to GDAL - An Introduction to GDAL - Robert Simmon
- A Gentle Introduction to GDAL prt 1 - command line working
- A Gentel Introduction to GDAL prt 2 - Map Projections
- A Gentel Introduction to GDAL prt 3 - Geodesy
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-
Earth Observation coding on YouTube
-
Testing your code
- xArray at PyConUK2018 - Robin Wilson - Processing thousands of satellite images to understand air quality in the UK - it's efficient and easy with XArray
- Visualizing & Analyzing Earth Science Data Using PyViz & PyData - Julia Signell - In this talk, we'll work through some specific workflows and explore how various tools - such as Intake, Dask, Xarray, and Datashader - can be used to effectively analyze and visualize these data. Working from within the notebook, we'll iteratively build a product that is interactive, scalable, and deployable.
- Python from space - Katherine Scott - In this talk we will work through a jupyter notebook that covers the satellite data ecosystem and the python tools that can be used to sift through and analyze that data. Topics include python tools for using Open Street Maps data, the Geospatial Data Abstraction Library (GDAL), and OpenCV and NumPy for image processing.
- Remote Sening with Python in Jupyter - In this video we're looking at using Google Earth Engine in Jupyter with the Python API.
- Google Earth Engine Python - Qiusheng Wu - Introducing the geemap Python package for interactive mapping with Google Earth Engine and ipyleaflet.
- Google Earth Engine EE101 Condensed - Noel Gorelick - Introduction to the Earth Engine API and a conceptual overview of key functionality such as compositing, reducing, mapping, zonal statistics and cluminating with building a small app.
- Image classification with RandomForests using the R language
- GeoPython 2019 stream - 17:23 Machine Learning for Land Use/Landcover Statistics of Switzerland (Adrian Meyer), 50:58 How to structure geodata, 1:18:13 Terrain segmentation with label bootstrapping for lidar datasets, case of doline detection (Rok Mihevc), 2:34:41 Bias in machine learning, 3:06:23 Software for planning research aircraft missions (Reimar Bauer), 3:32:38 How Technology Moves Fast (PJ Hagerty) , 5:02:05 Spotting Sharks with the TensorFlow Object Detection API (Andrew Carter), 5:40:23 Center for Open Source Data and AI Technologies (CODAIT), 6:03:40 Bayesian modeling with spatial data using PyMC3 (Shreya Khurana) (Sound at 6:04:23 ^^), 7:02:45 Understanding and Implementing Generative Adversarial Networks(GANs) (Anmol Krishan Sachdeva), 7:37:00 Messaging with Satellites from Anywhere on the Planet (Andrew Carter), 8:04:52 Automation of the definition and optimizatino of census sampling areas using AREA (GRID3) (Freja Hunt), 8:35:26 Coastline Mapping with Python, Satellite Imagery and Computer Vision (Rachel Keay)
- Google Earth Engine in QGIS - This playlist looks at the GEE plugin for QGIS
- QiushengWu's youtube - This youtube channel has pretty much everything you need Earth Engine, git, colab, Python, Geoscience. Highest quality stuff.
- The OpenDataCube Conference 2021 - Playlist from the 2021 conference
- Dask and Geopandas - Scalable geospatial data analysis with Dask| Dask Summit 2021
- Google Earth Engine Python - Qiusheng Wu - Introducing the geemap Python package for interactive mapping with Google Earth Engine and ipyleaflet.
- Hands on Satellite Imagery 2019 edition - Sara Safavi - In this tutorial, gain hands-on experience exploring Planet’s publicly-available satellite imagery and using Python tools for geospatial and time-series analysis of medium- and high-resolution imagery data. Using free & open source libraries, learn how to perform foundational imagery analysis techniques and apply these techniques to real satellite data.
- Writing Image Processing Algorithms with ArcGIS/ArcPy - Jamie Drisdelle - learn how your algorithms can integrate with the raster processing and visualization pipelines in ArcGIS. We’ll demonstrate the concept and discuss the API by diving deep into a few interesting examples with a special focus on multidimensional scientific rasters.
- Handling and analysing vector and raster data cubes with R - Edzer Pebesma (Institute for Geoinformatics, University of Münster) Summary: vector and raster data cubes include vector and raster data as special cases, but extend this to vector time series, OD matrices, multi-band raster data, multi-band raster time series, multi-attribute vector or raster time series, and more general to array data where one ore more dimensions are associated with space and/or with time. Examples come from pretty much all areas dealing with spatiotemporal data. This tutorial will go through a large number of examples to illustrate this idea, mostly focusing on the packages stars and sf and those supporting their classes (like tmap, mapview, gstat, ggplot2).
- Visualizing & Analyzing Earth Science Data Using PyViz & PyData - Julia Signell - In this talk, we'll work through some specific workflows and explore how various tools - such as Intake, Dask, Xarray, and Datashader - can be used to effectively analyze and visualize these data. Working from within the notebook, we'll iteratively build a product that is interactive, scalable, and deployable.
-
-
Earth Engine
-
Testing your code
- from GEE to Numpy to Geotiff - Use the GEE python api to export your data to numpy and store the result as a geotiff.
- Google Earth Engine Community - This organization contains content contributed by the Earth Engine developer community. This is not an officially supported Google product.
- Geo4Good 2019 workshop materials - 2019 material javascript and Python to be found here
- 2018 GEE summit - Dublin materials - 2018 material javascript and Python to be found here
- 10 tips for becoming an Earth Engine expert - Keiko Nomura shares her 10 favourite tips
- Earth Engine Developer list - registration required
- Earth Engine Beginner's Cookbook - n this tutorial, we will introduce several types of geospatial data, and enumerate key Earth Engine functions for analyzing and visualizing them. This cookbook was originally created as a workshop during Yale-NUS Data 2.0 hackathon, and later updated for Yale GIS Day 2018 and 2019. `JavaScript`
- Google Earth Engine Repos - all the repos matching `earth-engine`
- GEE Map - A Python package for interactive mapping with Google Earth Engine, ipyleaflet, and ipywidgets
- GEE Map - A Python package for interactive mapping with Google Earth Engine, ipyleaflet, and ipywidgets
-
-
Open Data Cube
-
Testing your code
-
-
Planetary Computer
-
Testing your code
- Sentinel2 on planetary computer - notebook explores Sentinel-2 data on Microsoft's Planetary Computer `Python`
- mircosoft - Microsoft git repo
- reading-stac - Reading Data from the STAC API
-
-
QGIS and Grass
-
Testing your code
- grass-dev-py3-pdal - Dockerfile which compiles GRASS GIS 7.9 master with Python 3 and PDAL suppor
-
-
Climate and weather based resources
-
Testing your code
- unidata on GOES-16 - This notebook shows how to make a true color image from the GOES-16 Advanced Baseline Imager (ABI) level 2 data. We will plot the image with matplotlib and Cartopy.`Python`
- MetPy docs
-
EUMETlab
- EUMETlab - This page contains groups of code repositories that have been made open to the public by EUMETSAT and our collaborators.
- atmosphere - LTPy - Learning tool for Python on Atmospheric Composition Data is a Python-based training course on Atmospheric Composition Data. The training course covers modules on data access, handling and processing, visualisation as well as case studies.
- sentinel-downloader - Python-based Sentinel satellite data downloader. This script allows for batch downloading of Sentinel data selected by various criteria include date, location, sensor, child products, flags and more.
- olci-iop-processor - Code to produce Inherent Optical Properties from Level-2 OLCI data.
-
-
DEM projects
-
EUMETlab
- The Stereo Pipeline (NASA) - The NASA Ames Stereo Pipeline (ASP) is a suite of free and open source automated geodesy and stereogrammetry tools designed for processing stereo imagery captured from satellites
-
-
SAR
-
EUMETlab
- Step by step: Radar-based flood mapping with Python - SPIDER/radar-based-flood-mapping) - This repository contains a Jupyter Notebook for automatic flood extent mapping using space-based information. `Python`
-
-
LiDAR
-
EUMETlab
- ICESAT extraction script - Python script to convert from ICESat-2 ATL08 HDF data to shapefile. Usage: 'python icesat2_shp.py
-
GEDI
- GEDI extraction script - Python script to take GEDI level 2 data and convert variables to a geospatial vector format
-
-
InSAR
-
GEDI
- Pyrocko - Can be utilized flexibly for a variety of geophysical tasks, like seismological data processing and analysis, modelling of InSAR, GPS data and dynamic waveforms, or for seismic source characterization.
-
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Visualisation
-
GEDI
-
-
Regular blogs of significant interest or posts of interest
-
GEDI
- Philipp Gartner blog
- Series Temporelles
- The downlinq
- GEDI canopy data - How we processed data to retrieving canopy height
-
-
EO code Competitions
-
GEDI
- Julia Wagemann github - Making open meteorological and climate data better accessible. `Python`, `Jupyter` and `R`.
- Sentinel hub competitions
- Planet: Understanding the Amazon from Space - Use satellite data to track the human footprint in the Amazon rainforest
- DeepGlobe Building Extraction Challenge - We would like to pose the challenge of automatically detecting buildings from satellite images.
- DSTL feature extraction - Kagglers are challenged to accurately classify features in overhead imagery
- crowdAI misisng maps challenge - Building Missing Maps with Machine Learning
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Useful EO code based twitter accounts
-
GEDI
- pyGEDI - pyGEDI is a Python Package for NASA's Global Ecosystem Dynamics Investigation (GEDI) mission, data extraction, analysis, processing and visualization.
-
-
EO Geospatial companies or orgs making big contributions
-
GEDI
- development seed - now Maxar](https://github.com/DigitalGlobe) | [Azavea](https://github.com/azavea) | [Radiant Earth foundation](https://github.com/radiantearth) | [Sentinel Hub](https://github.com/sentinel-hub) | [PyTroll](https://github.com/pytroll) | [CosmiQ](https://github.com/CosmiQ) | [Theia software and tools](https://www.theia-land.fr/en/softwares-and-tools/) | [sparkgeo](https://github.com/sparkgeo) | [Geoscience Australia](https://github.com/GeoscienceAustralia) | [Dymaxion Labs](https://github.com/dymaxionlabs) | [Satellogic](https://github.com/satellogic) | [senbox-org](https://github.com/senbox-org) | [Nasa-gibs](https://github.com/nasa-gibs) | [mundialis](https://github.com/mundialis) | [ESA_PhiLab](https://github.com/ESA-PhiLab) | [Element 84](https://github.com/Element84)
-
-
Interesting Non EO parts Python
-
GEDI
- A-Z of tips and tricks for Python - 'Most of these ‘tricks’ are things I’ve used or stumbled upon during my day-to-day work. '
- Visual intro into Numpy - Visualizing machine learning one concept at a time
- unidata Python workshop - Would you like some in-depth training on the scientific Python ecosystem for atmospheric science and meteorology? Work through our workshop materials at your own pace to learn and practice the syntax, functionality, and utility of this powerful programming language, or return to the material after taking the workshop in-person to further your understanding of the material you were taught.
- Another Book on Data Science - Learn R and Python in Parallel
- Matplotlib colab notebook tutorial - This notebook demonstrates how to use the matplotlib library to plot beautiful graphs.
- PostGIS raster cheatsheet - Useful tips on rasters in PostGIS
- 65 data science books on Springer - not checked but perhaps useful
- Intro to Numerical Computing - youtube - Intro to Numerical Computing with NumPy (Beginner) | SciPy 2018 Tutorial | Alex Chabot-Leclerc
- Matplotlib_Cheatsheet - Matplotlib_Cheatsheet `Python`
- GeoStats, Resources - Geostatistics
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- 65 data science books on Springer - not checked but perhaps useful
- Matplotlib_Cheatsheet - Matplotlib_Cheatsheet `Python`
-
-
Data
-
GEDI
- gibs - This is EO
- awesome-gee-community-datasets - Community Datasets added by users and made available for use at large
-
-
A footnote on awesome
-
GEDI
- Awesome Sentinel - curated list of awesome tools, tutorials and APIs for Copernicus Sentinel satellite data
-
-
Great Github accounts
-
GEDI
- Chis Holden - [blog](http://jgomezdans.github.io/) | [Johntruckhenbrodt](https://github.com/johntruckenbrodt) | [Marcus Netler](https://github.com/neteler) | [Oliverhagolle](https://github.com/olivierhagolle) | [PerryGeo](https://github.com/perrygeo) | [giswqs - Qiusheng Wu](https://github.com/giswqs) | [rhammell](https://github.com/rhammell) | [Remote pixel](https://github.com/RemotePixel) | [robintw](https://github.com/robintw) | [Evan Roualt](https://github.com/rouault) | [samapriya](https://github.com/samapriya) | [shakasom](https://github.com/shakasom) | [yannforget](https://github.com/yannforget) | [Pete Bunting](https://github.com/petebunting) | [Vincent Sarago](https://github.com/vincentsarago) |
-
Programming Languages
Categories
`Python` processing of optical imagery (non deep learning)
215
Interesting Non EO parts Python
43
Resources for `R`
35
Earth Observation coding on YouTube
17
Languages other than `Python` and `R`
11
Earth Engine
10
Earth Observation Introduction
9
Climate and weather based resources
6
EO code Competitions
6
GDAL of course
5
Training and learning
4
Regular blogs of significant interest or posts of interest
4
Remote Sensing.info
4
Planetary Computer
3
Deep learning and Machine Learning
2
LiDAR
2
Data
2
Open EO
2
Great Github accounts
1
QGIS and Grass
1
Open Data Cube
1
Visualisation
1
Useful EO code based twitter accounts
1
A footnote on awesome
1
DEM projects
1
InSAR
1
EO Geospatial companies or orgs making big contributions
1
SAR
1
Sub Categories
Keywords
remote-sensing
32
python
32
earth-observation
21
satellite-imagery
18
geospatial
16
gis
15
stac
11
raster
11
landsat
9
r
8
satellite-data
7
satellite
7
gdal
7
rasterio
7
xarray
7
sentinel-2
7
machine-learning
6
python3
5
satellite-images
5
geospatial-data
5
vector
4
aws
4
image-processing
4
dask
4
r-package
3
cog
3
esa
3
copernicus
3
geoprocessing
3
python-library
3
satellites
3
api-client
3
classification
3
api
3
sentinel
3
jupyter-notebook
3
rstats
3
atmospheric-correction
3
grass-gis
3
geopandas
2
tile
2
science
2
spatial-data
2
netcdf
2
opensearch
2
sentinel-1
2
landsat-8
2
sentinel-hub
2
sdk
2
siac
2