Coupling remote geological mapping in Google Earth with direct 3D geological modeling in GemPy.

The best way to get started is actually to go through the example in the book chapter - this is currently in review and more information will (hopefully) be provided here, soon!

Next to remote-geomod, you will require two additional major software components: (1) Google Earth Pro for remote mapping and (2) a Python distribution with specific software libraries. The software libraries remote-geomod relies on can be difficult to install on certain systems. Because of this we provide you with two possible installation paths that will take care of installing the dependecies:

• Using the open-source Anaconda Python distribution which allows convenient, automated installation of the dependencies.
• A local installation inside of a Docker environment, for wich we can directly ship all dependencies insode of a Docker image. We recommend this installation path for users familiar with using Dokcer of if the above one fails.

As a first step you need to download the Anaconda Python Distribution on your system. Make sure to select the correct Python 3.6 version for your operating system and install it (a comprehensive user guide with installation instructions can be found on the Conda Documentation website).

The next step is to either download and unpack the remote-geomod repository, or to directly clone it using your command-line tool of choice:

git clone https://github.com/cgre-aachen/remote-geomod.git

Once you have a local copy of the repository on your computer, you have to create a new Conda environment. You can either do this using your command-line tool (1) or the Anaconda Navigator (2):

1. Open your command-line tool in the downloaded or cloned remote-geomod folder and run conda env create -n rgeomod -f environment.yml. Afterwards you can activate the environment with the command activate rgeomod (Windows) or source activate rgeomod (macOS, Linux) or in your Anaconda Navigator.
2. For the latter option start the Anaconda Navigator, select Environments in the navigation bar on the left-hand side, then click Import at the bottom of the window and browse for the environment.yml file located in the remote-geomod folder and give the environment the same name. This will create a separate Conda environment and install all necessary dependencies automatically. Once the installation finished, make sure you have selected the newly created environment.

remote-geomod uses Python 3 and has several dependencies for numerical operations, geographical data operations, geological modeling and visualization. All dependencies can be found in the environment.yml file:

dependencies:
  - python=3.6
  - numpy
  - conda-forge::gdal
  - clinicalgraphics::vtk
  - theano=1.0.1
  - jupyter
  - nb_conda
  - matplotlib
  - pandas
  - seaborn
  - scikit-image
  - tqdm
  - pip:
    - mplstereonet
    - gempy

We also provide precompiled Docker images hosted on Docker Hub with all necessary dependencies to get remote-geomod up and running.

Docker is an operating-system-level-visualization software, meaning that we can package a tiny operating system with pre-installed software into a Docker image. This Docker image can then be shared with and run by others, enabling them to use intricate dependencies with just a few commands. For this to work the user needs to have a working Docker installation.

The easiest way to get remote-geomod running is by running the pre-compiled Docker image (containing everything you need) directly from the cloud service Docker Hub to get a locally running Docker container. Make sure to set your Docker daemon to Linux containers in Docker's context menu.

docker run -it -p 8888:8888 cgreaachen/rgeomod_complete

This will automatically pull the Docker image from Docker Hub and run it, opening a command line shell inside of the running Docker container. There you have access to the file system inside of the container. Note that this pre-compiled Docker image already contains the rgeomod repository. As rgeomod is undergoing active development, we can not guarantee that this Docker image always contains the latest release version.

If you just want the dependencies:

docker run -it -p 8888:8888 cgreaachen/rgeomod_dependencies

Alternatively, you can also build the Docker image yourself from the Dockerfile provided with the repository by running docker build . -t <image-tag> in its root directory. Once the Docker image is built you can look up it's image-id using docker images. Then, instead of using the DockerHub repository name, you can run the Docker image by using its id: docker run -it -p 888:8888 <image-id>.

A good way to get started is to follow the steps in the publication (see below) and to run the jupyter notebooks, supplied with this package.

Wellmann, F., A. Schaaf and C. von Hagke: "From GoogleEarth to 3-D Geology Problem 2: Seeing below the surface of the Digital Earth". Submitted as book chapter for "Structural Geology and Tectonics: Problems and Solutions".

This library is developed by LuFG Computational Geoscience and Reservoir Engineering (CGRE) at RWTH Aachen University, Germany.