Moja global Chile data pre-processing project setup

The following section describes how to set up the project on your local machine. The following are minimum requirements:

  1. R programming language

  2. R Studio

  3. Git

Setting up the project

The following instructions describe how to install all the required tools to do live data pre-processing on a Windows 10 system.

After installing, R Studio and R programming language, start the R Studio IDE and follow these steps:

  1. Click on File and select New Project.

  2. Click on Version Control to checkout a project from a version control repository.

  3. Click on Git to clone the project from our GitHub repository.

  4. Add the repository URL: Select the subdirectory as per your needs and click on Create Project.

  5. After the repository is cloned and a workspace is initialized, download the Input data required for the data pre-processing. You can download it from the GitHub releases:

    1. Visit the GitHub releases on the GCBM Chile Data Preprocessing repository and check out the latest release.

    2. Scroll down to find the Input_Files.rar which contains the dataset used by the pre-processing algorithm.

    3. Click on Input_Files.rar and download it on your local machine. Extract the Input_Files directory on the root of the cloned GCBM Chile Data Preprocessing repository.

    4. Optional: You can download the Output_Files.rar as well for reproducibility and checking the results of the pre-processing algorithm.

  6. Ensure the following directory structure for the project:

├── Input_Files
│   ├── Growth                # Excel spreadsheet with growth data
│   ├── LUC                   # Trazabilidad (Land use) data
│   ├── SOC                   # Soil Organic carbon data
|   └── Temperature           # Temperature raw data (NetCDF)
├── Output_Files
│   ├── input_database
│   └── layers
│     └── raw
        ├── disturbances
│       ├── environment
|       └── inventory
├── Processing_codes
├── docs/
├── run_all.R
└── ...

Running the project

With the initial setup complete, you are now ready to run the pre-processing algorithm code.

  1. From the R Studio IDE, select the run_all.R file and click on Run to run all the pre-processing code.

  2. Optionally, choose the individual files in the Preprocessing_Codes to run them singularly. Make sure to install the R packages as suggested by the R Studio.

With the repository and tools set up on your workstation, you can now either edit existing code or prepare local datasets for a GCBM run using R.