> For the complete documentation index, see [llms.txt](https://guides.geospatial.bas.ac.uk/working-with-scientific-data-formats-in-gis/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://guides.geospatial.bas.ac.uk/working-with-scientific-data-formats-in-gis/intro-notes.md).

# Intro notes

This session is focused on tools and methods to prepare data in scientific/multidimensional formats (HDF, GRIB, NetCDF) for use in GIS, featuring tools like QGIS, GDAL, and XARRAY and GDAL API for Python.

It consists of 3 parts:

* **"Good" HDF** is an example of working with QGIS-readable MODIS NDSI data with the GDAL command line tool
* **"Good" GRIB** section features the Xarray Python library as an efficient tool for multidimensional data processing
* **"Not-so-good" NetCDF** is an example of how to treat datasets with incorrect georeferencing with GDAL and Xarray together
* **Reading Sentinel-3 data** is a ready-to-use script for converting Sentinel-3 L1 EFR data to GeoTiff. <br>

Below are the tips for installing the GDAL command line tool and configuring the conda environment for working with GDAL and Xarray in Python. Checked for Python 3.9.

{% hint style="info" %}
Terminal commands  are written in Linux syntax
{% endhint %}

<details>

<summary>GDAL installation</summary>

#### Windows

Usually, GDAL is installed along with QGIS. The easiest way to access GDAL is to open **OSGeo4W Shell**: Start > QGIS > OSGeo4W Shell.

#### Ubuntu / MacOS

Usually, GDAL is installed along with QGIS and can be called through the terminal window.&#x20;

#### No QGIS&#x20;

[Install anaconda](https://docs.anaconda.com/anaconda/install/index.html). Create a new Python environment.

```
conda create --name geo
conda activate geo
```

Install GDAL in this environment

<pre><code><strong>conda install -c conda-forge gdal
</strong></code></pre>

Check installation

```
gdlainfo
```

</details>

<details>

<summary>Configuring environment for Jupyter Notebook </summary>

Install anaconda. Create a new Python environment.

```shell
conda create --name geo
conda activate geo
```

Install geopandas (this will also install numpy, pandas and gdal), matplotlib, xarray and dependables netcdf4 and cfgrib.&#x20;

```
conda install -c conda-forge geopandas 
conda install -c conda-forge matplotlib
conda install -c conda-forge cfgrib
conda install -c conda-forge netcdf4
conda install -c conda-forge xarray
conda install -c anaconda jupyter
```

Navigate to your working directory and start Jupyter

```sh
cd /mnt/c/my_dir/
jupyter notebook
```

A new jupyter session will start and a new browser tab will be open.&#x20;

</details>

{% hint style="warning" %}
Sections 2 through 4 contain \*.ipynb files to download.

Data is not provided, but you can download it using links in the 'Data source' section.
{% endhint %}


---

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