> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/thareUSGS/GDAL_scripts/llms.txt
> Use this file to discover all available pages before exploring further.

# Installation

> Step-by-step guide to installing GDAL Scripts and dependencies

## Prerequisites

GDAL Scripts requires Python 3.x and the GDAL library with Python bindings. The recommended approach is to use Anaconda, which simplifies GDAL installation and dependency management.

<Note>
  Python 2 versions of some scripts exist in the repository for legacy support, but Python 3 is strongly recommended for all new installations.
</Note>

## Installation Steps

<Steps>
  <Step title="Install Anaconda (Recommended)">
    If you don't already have Anaconda installed, download it from [anaconda.com](https://www.anaconda.com/download).

    Anaconda provides the easiest path to getting GDAL installed with all necessary dependencies.
  </Step>

  <Step title="Install GDAL">
    GDAL is the core dependency for all scripts in this collection. Install it using conda:

    ```bash theme={null}
    conda install gdal
    ```

    This command installs GDAL along with the Python bindings automatically.

    <Accordion title="Alternative: Install GDAL without Anaconda">
      If you prefer not to use Anaconda, you can install GDAL via other methods:

      **On Ubuntu/Debian:**

      ```bash theme={null}
      sudo apt-get update
      sudo apt-get install gdal-bin python3-gdal
      ```

      **On macOS with Homebrew:**

      ```bash theme={null}
      brew install gdal
      pip install gdal==$(gdal-config --version)
      ```

      **On Windows:**
      Download OSGeo4W installer from [osgeo.org](https://trac.osgeo.org/osgeo4w/) and select GDAL during installation.
    </Accordion>
  </Step>

  <Step title="Install Additional Python Dependencies">
    Several scripts require NumPy and SciPy for numerical operations:

    ```bash theme={null}
    conda install numpy scipy
    ```

    Or using pip:

    ```bash theme={null}
    pip install numpy scipy
    ```

    <Note>
      Not all scripts require these dependencies. Check individual script README files for specific requirements.
    </Note>
  </Step>

  <Step title="Clone the Repository">
    Clone the GDAL Scripts repository from GitHub:

    ```bash theme={null}
    git clone https://github.com/thareUSGS/GDAL_scripts.git
    cd GDAL_scripts
    ```

    The scripts are ready to use immediately - no build or install step is required.
  </Step>

  <Step title="Test Your Installation">
    Verify that GDAL is correctly installed by checking the version:

    ```bash theme={null}
    gdalinfo --version
    ```

    Test the Python bindings:

    ```bash theme={null}
    python -c "from osgeo import gdal; print(gdal.__version__)"
    ```

    Both commands should return version information without errors.
  </Step>
</Steps>

## Verifying Individual Scripts

Most scripts provide usage information when run without arguments:

<CodeGroup>
  ```bash Coordinate Conversion theme={null}
  python gdal2Coordinates/pixel2longlat.py
  ```

  ```bash Slope Analysis theme={null}
  python gdal_baseline_slope/gdal_baseline_slope.py
  ```

  ```bash Data Clipping theme={null}
  python gdal_clip2range/gdal_clip2range.py
  ```
</CodeGroup>

Each should display usage instructions, confirming the script is ready to use.

## Common Issues and Troubleshooting

<AccordionGroup>
  <Accordion title="ImportError: No module named 'osgeo'">
    This error indicates GDAL Python bindings are not installed or not in your Python path.

    **Solution:**

    * If using Anaconda: `conda install gdal`
    * If using pip: `pip install gdal`
    * Ensure you're using the same Python environment where GDAL was installed

    Check your Python environment:

    ```bash theme={null}
    which python
    conda env list  # if using Anaconda
    ```
  </Accordion>

  <Accordion title="ImportError: No module named 'numpy' or 'scipy'">
    Some scripts require NumPy and SciPy for array operations and filtering.

    **Solution:**

    ```bash theme={null}
    conda install numpy scipy
    ```

    or

    ```bash theme={null}
    pip install numpy scipy
    ```

    Scripts requiring these dependencies include:

    * `gdal_baseline_slope.py` (requires both)
    * Various terrain analysis tools
  </Accordion>

  <Accordion title="GDAL version mismatch errors">
    If you see errors about GDAL version mismatches between the library and Python bindings:

    **Solution with Anaconda (recommended):**

    ```bash theme={null}
    conda update gdal
    ```

    **Solution with pip:**

    ```bash theme={null}
    pip install gdal==$(gdal-config --version)
    ```

    This ensures the Python bindings match your GDAL library version.
  </Accordion>

  <Accordion title="Permission denied when running scripts">
    **Solution:**
    Make scripts executable:

    ```bash theme={null}
    chmod +x gdal2Coordinates/pixel2longlat.py
    ./gdal2Coordinates/pixel2longlat.py
    ```

    Or always run with Python explicitly:

    ```bash theme={null}
    python gdal2Coordinates/pixel2longlat.py
    ```
  </Accordion>

  <Accordion title="Scripts run slowly or use too much memory">
    Some scripts, particularly `gdal_baseline_slope.py`, load entire images into memory.

    **Solutions:**

    * Work with smaller regions of interest
    * Use 8-bit output (`-ot Byte` flag) instead of 32-bit when possible
    * Increase available system memory
    * Process images in tiles for very large datasets

    From the gdal\_baseline\_slope.py README:

    > "Current implementation loads full image into memory and is fairly slow."
  </Accordion>
</AccordionGroup>

## Environment Setup Tips

### Creating a Dedicated Conda Environment

For cleaner dependency management, create a dedicated environment:

```bash theme={null}
conda create -n planetary-tools python=3.9 gdal numpy scipy
conda activate planetary-tools
```

Activate this environment whenever working with GDAL Scripts:

```bash theme={null}
conda activate planetary-tools
```

### Adding Scripts to Your PATH

To run scripts from anywhere without specifying full paths:

```bash theme={null}
export PATH="$PATH:/path/to/GDAL_scripts"
```

Add this line to your `~/.bashrc` or `~/.zshrc` to make it permanent.

## System Requirements

<CardGroup cols={2}>
  <Card title="Minimum Requirements" icon="circle-check">
    * Python 3.6+
    * GDAL 2.0+
    * 4GB RAM (for small images)
    * Any major OS (Linux, macOS, Windows)
  </Card>

  <Card title="Recommended" icon="star">
    * Python 3.9+
    * GDAL 3.0+
    * 16GB+ RAM (for large planetary datasets)
    * SSD storage for faster I/O
  </Card>
</CardGroup>

## Next Steps

<Card title="Quick Start Guide" icon="rocket" href="/quickstart">
  Now that you have GDAL Scripts installed, try out some practical examples
</Card>