A python project to use satellite LiDAR data and satellite imagery to create a 3D reconstruction of an area of interest (AOI)
For the environment setup using conda makes it easier to setup everything. The project uses Python version 3.7. Create a conda environment and install following libraries.
- h5py
- shapely
- geopandas
- pandas
- geoviews
- holoviews
You can use the following command to create a new conda environment and install the required libraries.
conda create -n GEDI -c conda-forge --yes python=3.7 h5py shapely geopandas pandas geoviews holoviews
Activate the environment.
conda activate GEDI
If you do not have Jupyter Notebook installed, you may need to run:
conda install jupyter notebook
the same setup and dependencies can be achieved by using another package manager such as pip
GEDI Orbit granules over a certion region can be found using a GEDI Finder. A bounding box can be defined using Longitude and Lattitude and the script query the base CMR granule search url to get a list of all the orbit granules over Area of interest.
You can use another script DAACDataDownload.py to download all the data files. The execution command to data downloader script is as below
python DAACDataDownload.py -dir <insert local directory to save files to> -f <insert a single granule URL, or the location of a csv or text file containing granule URLs>
The GEDI level 1B data contains the processed waveform data. These waveforms can be used get the elevation information. A jupyter notebook to process level 1B data is in the directory 'GEDI_Level_1B_Data'
The file 'RIT.geojson' stores the geographical boundries of the Rochester Institute of Technology, Rochester New York campus. We will use this file as our area of interest.
💡 You can use data downloader script from GEDI Finder to get required data. Alternatively you can visit the NASA Earthdata Search website to download the required data