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(HS 17) Automate Workflows using Jupyter notebook to create Large Spatial Sample Datasets

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Created: May 13, 2021 at 10:38 p.m.
Last updated: May 21, 2021 at 8:10 a.m.
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For the automated workflows, we create Jupyter notebooks for each state. In these workflows, GIS processing to merge, extract and project GeoTIFF data was the most important process. For this process, we used ArcPy which is a python package to perform geographic data analysis, data conversion, and data management in ArcGIS (Toms, 2015). After creating state-scale LSS datasets in GeoTIFF format, we convert GeoTIFF to NetCDF using xarray and rioxarray Python packages. Xarray is a Python package to work with multi-dimensional arrays and rioxarray is rasterio xarray extension. Rasterio is a Python library to read and write GeoTIFF and other raster formats. We used xarray to manipulate data type and add metadata in NetCDF file and rioxarray to save GeoTIFF to NetCDF format. Through these procedures, we created three composite HyddroShare resources to share state-scale LSS datasets.
Due to the limitation of ArcGIS Pro license which is a commercial GIS software, we developed this Jupyter notebook on Windows OS.

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Related Resources

This resource belongs to the following collections:
Title Owners Sharing Status My Permission
(HS 1) Creating and Sharing Interoperable and Reusable Large Spatial Sample Datasets Online for Open and Reproducible Seamless Hydrological Modeling: RHESSys Use Case Iman Maghami · Linnea Saby · Zhiyu/Drew Li · Young-Don Choi  Public &  Shareable Open Access

How to Cite

Choi, Y. (2021). (HS 17) Automate Workflows using Jupyter notebook to create Large Spatial Sample Datasets, HydroShare,

This resource is shared under the Creative Commons Attribution CC BY.


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