Utilizing ArcGIS Pro Deep Learning Models to Perform Land Cover Classification for use within Civil Engineering Design

Authors

Presenter(s)

Daniel M. Deddens

Comments

Presentation: 10:45-12:00, Kennedy Union Ballroom

Files

Description

This project aims to develop a workflow for existing deep learning models to perform land cover classification on high resolution satellite imagery that can be used in conjunction with the Arc Hydro toolkit, both developed by ESRI for ArcGIS Pro. By performing land cover classification on high resolution imagery, and reclassifying the data with land cover-related hydrologic parameters, a watershed can be delineated, assigned a curve number, and a report can be constructed to provide engineers with pertinent information to the design process. The use of GIS tools within Civil Engineering design is sparse, by developing a workflow for engineers and designers to utilize, I hope to increase the use of GIS within engineering design to construct reproducible and accurate results.

Publication Date

4-17-2024

Project Designation

Capstone Project

Primary Advisor

Chia-Yu Wu

Primary Advisor's Department

Geology

Keywords

Stander Symposium, College of Arts and Sciences

Recommended Citation

"Utilizing ArcGIS Pro Deep Learning Models to Perform Land Cover Classification for use within Civil Engineering Design" (2024). Stander Symposium Projects. 3651.
https://ecommons.udayton.edu/stander_posters/3651