Authors:

Connor Durkin

Date Created:

Not specified

Course Title:

Professor:

Not specified

About Paper:

The 3D Elevation Program (3DEP) managed by the U.S. Geological Survey (USGS) made publicly available the elevation data at any geospatial point in the nation. Similarly, the U.S. Department of Agriculture (USDA) has the Soil Survey Geographic Database (SSURGO) providing data such as drainage class and soil type. The USGS 3DEP data was collected via Light Detection and Ranging (LiDAR) while the USDA SSURGO data was collected on foot, meaning they have different data types. Both researchers and farmers alike struggle to make use of datasets such as these as they differ in source and in data types. We will develop an open-source Python package that automates the transformation of low-level data into high-level data, allowing both researchers and farmers to easily interpret it. The package will use Network Mapper's Application Programming Interface (Nmap's API) to contact USGS 3DEP and USDA SSURGO and will transform the data using GeoPandas. The result of which will allow the user to more efficiently analyze the elevation and soil data of a specified geospatial point, increasing throughput and accuracy of later statistical analysis.

Source:

Purdue University / 2023

Topics:

No topics listed

Co-authors:

Connor Durkin