Karttur’s GeoImagine Framework offers a semi-automated processing environment for spatial data, mainly intended for Big Data processing of satellite images and other spatial datasets. To work with the Framework your machine must first be set up with a Spatial Data Integrated Development Environment (SPIDE) as described in my blog on Install and setup spatial data IDE.

At the core of the Framework are object oriented processes. These processes are assembled in groups (called roots), where each group is associated with either a particular data source (e.g. MODIS, Sentinel, Landsat, ancillary etc), or a particular kind of process (e.g. time series processing, scalar, overlay, export etc). Many root processes are also associated with a specific, purpose-built, Python package.

To search for a particular package or process, use these links to browse the content of Karttur’s GeoImagine Framework:

• Python packages
• Root processes
• Sub processes

Preparations

If you intend to setup a clone, or your own version, of Karttur’s GeoImagine Framework you first need to create a Python environment. It is strongly recommended that you do that as a Conda virtual environment.

The second step is to Get Karttur’s GeoImagine Framework into Eclipse, where Eclipse (for PyDev) is also part of the SPIDE installation.

Then you also have to prepare the database connections for the PostgreSQL database installed as part of the SPIDE. Before actually running any of the processes it will help if you get acquainted with the conceptual backbone. After that you can follow the step-by-step posts in the setup section.

The blog contains various examples processing different kinds of data in the Framework. Under Develop you find instructions for how to setup your own version of the Framework.

Python environment and database connection

• Python virtual environment January 05, 2021 Create Conda Python environment for Karttur’s GeoImagaine project
• Database connections January 06, 2021 Prepare database connections for Karttur’s GeoImagine Framework
• Run GRASS from Python January 08, 2021 How to start and run GRASS from within an external Python script.

Get Framework

• Git clone with Eclipse and no project November 20, 2020 Clone Karttur’s GeoImagine Framework from GitHub using Eclipse and create the PyDev project by linking

Concept

• Framework key concepts November 01, 2020 Key concepts: processes and compositions, and how they are represented in json.

Setup

• Complete installation October 20, 2020 A complete installation scheme for Karttur’s GeoImagine Framework
• Set up the database (setup_db) December 01, 2020 Run the setup_db package to setup the postgres database for Karttur’s GeoImagine Framework
• Setup processes (setup_processes) December 03, 2020 Setup the processes for Karttur’s GeoImagine Framework

Blog

• DEM processing 10: Extracting kernel indexes with GDAL May 24, 2021 Process chain for Copernicus DEM: xtracting kernel indexes with GDAL
• DEM image layout May 15, 2021 Elevation symbolisation; color ramping, hill shading and legends for image maps
• Process chain for Copernicus DEM May 14, 2021 Complete process chain for Copernicus DEM using Kartturs GeoImagine Framework
• Hydrografi March 25, 2021 Extracting hydrografi from DEMs
• Create regional DEM March 23, 2021 Identify and defined a regional DEM

Develop

• GitHub Submodules with git November 10, 2020 Create submodules and a superproject using git
• GitHub Submodules November 15, 2020 Organize GitHub repositories with python packages as submodules
• git superproject and submodels January 02, 2021 Create the git superproject with Kartturs GeoImagine Framework packages as submodules
• Add, commit and push submodules January 03, 2021 If your Farmework is not linked to a git origin, this post describes how to add, commit and push changes via the local repo that is linked to a git origin.

Depreciated