Skip to content

OSINT-TECHNOLOGIES/gaia

Repository files navigation

GAIA - Geospatial & Aerial Images Analyser [BETA]

Note

Please note that this program solution is currently in BETA stage and some details are potentially to be changed, more functionality may be added soon or later.

Current version: 0.64b

Tip

You can find some useful info about GAIA aspects in wiki: https://github.com/OSINT-TECHNOLOGIES/gaia/wiki

Tip

You can contact GAIA developer by sending message on the following e-mail: [email protected]

GitHub (Pre-)Release Date GitHub GitHub repo size

Static Badge Static Badge Static Badge

Static Badge Static Badge

README Table of Contents:

What is GAIA and how can I use it?

GAIA is a program created using Mercury Framework (runmercury.com), Google Earth Engine (earthengine.google.com) and OpenStreetMap (openstreetmap.org) specially for those who works with geospatial images of Earth or interested in this subject. This program implements the idea of getting as much sources of sattelite and aerial images as it possible in one app. It allows you to get planetary images from different providers using APIs of various services and, what is important, without any coding knowledge and in a pleasant web interface

GAIA demo screenshots

  1. Fires map in South America, visualised using NASA FIRMS firms

  2. North Gaza visualised using Sentinel-2 MSI during October 2023 conflict north_gaza

  3. Google Earth Engine integrated knowledge base knowledge_base

  4. OpenStreetMap GeoJSON file processing osmgeojson

Supported imagery and map services

Google Earth Engine. This service combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities. Scientists, researchers, and developers use Earth Engine to detect changes, map trends, and quantify differences on the Earth's surface. Earth Engine is now available for commercial use, and remains free for academic and research use. Support has been added with 0.3b update.

OpenStreetMap. OSM is a collaborative project for world mapping using data from various sources and volunteers. In GAIA you can get, use and explore different OSM-provided maps with different additional functions. Support has been added with 0.4b update.

How to start researching with GAIA

The very first step on your way to start researching using GAIA is installing necessary requirements. You can install them using setup.py script

Your second step is integrated services connection. Instructions below will help you to properly configure and connect them to GAIA

Connecting Google Earth Engine

To start researching using Google Earth Engine you need to:

  1. Register on Google Earth Engine using your Google account (https://code.earthengine.google.com/register) OR start GAIA using start.bat and press EE registration button
  2. Register a new project with unpaid usage, choose any type of project you want and name it however you want
  3. Confirm everything you've chosen
  4. Go to https://console.cloud.google.com/iam-admin/serviceaccounts/ and create service account for your project.
  5. Once service account created, click the menu for that account, then Create key > JSON. Download the JSON key file and put it in GAIA directory
  6. Open GAIA in web interface and if you don't see any errors and see the map - congratulations, you've just finished Google EE connection procedure. Now you can start using GAIA with Google EE

Connecting OpenStreetMap

Basically you don't need to do any things out of GAIA to start researching using OpenStreetMap. You need only to install new libraries from system requirements and you'll be ready to start your research using OSM.

After all needed services are connected, you can start your research. In order to do this you need to start GAIA web-interface using start.bat script which will open welcome window in your default browser.

System requirements

Software requirements:

  1. OS Windows 10/11
  2. Python 3.10 and above (lower versions won't guarantee correct and stable work)
  3. PIP package installer

Installed Python libraries (all of them can be installed using setup.py script):

  1. ee==0.2
  2. earthengine-api==0.1.392
  3. mercury==2.3.7
  4. colorama==0.4.6
  5. osmnx==1.7.0
  6. contextily==1.4.0
  7. folium==0.16.0
  8. future==0.18.3
  9. eefolium==0.2.0
  10. ipyleaflet==0.18.2

Network:* High-Speed Broadband Internet connection for good experience with datasets downloading