(HS 2) Automate Workflows using Jupyter notebook to create Large Extent Spatial Datasets

We implemented automated workflows using Jupyter notebooks for each state. The GIS processing, crucial for merging, extracting, and projecting GeoTIFF data, was performed using ArcPy—a Python package for geographic data analysis, conversion, and management within ArcGIS (Toms, 2015). After generating state-scale LES (large extent spatial) datasets in GeoTIFF format, we utilized the xarray and rioxarray Python packages to convert GeoTIFF to NetCDF. 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. Xarray facilitated data manipulation and metadata addition in the NetCDF file, while rioxarray was used to save GeoTIFF as NetCDF. These procedures resulted in the creation of three HydroShare resources (HS 3, HS 4 and HS 5) for sharing state-scale LES datasets. Notably, due to licensing constraints with ArcGIS Pro, a commercial GIS software, the Jupyter notebook development was undertaken on a Windows OS.

本团队采用了基于 Jupyter 笔记本的自动化工作流程，针对每个州进行处理。地理信息系统（GIS）处理，对于合并、提取和投影 GeoTIFF 数据至关重要，通过 ArcPy（一个用于在 ArcGIS 中进行地理数据分析、转换和管理的 Python 包）进行操作，ArcPy 由 Toms 在 2015 年提出。在生成以 GeoTIFF 格式表示的州级大范围空间（LES）数据集后，我们使用了 xarray 和 rioxarray 这两个 Python 包将 GeoTIFF 转换为 NetCDF 格式。xarray 是一个用于处理多维数组的 Python 包，而 rioxarray 则是 rasterio xarray 扩展。Rasterio 是一个 Python 库，用于读取和写入 GeoTIFF 以及其他栅格格式。xarray 促进了 NetCDF 文件中的数据处理和元数据添加，而 rioxarray 则用于将 GeoTIFF 保存为 NetCDF 格式。这些流程最终创建了三个 HydroShare 资源（HS 3、HS 4 和 HS 5），用于共享州级 LES 数据集。值得注意的是，由于商业 GIS 软件 ArcGIS Pro 的许可限制，Jupyter 笔记本的开发是在 Windows 操作系统上进行的。