USF St. Petersburg campus Master's Theses (Graduate)

First Advisor

Major Professor: Barnali Dixon, Ph.D

Second Advisor

Christopher A. Brown, Ph.D

Third Advisor

Henry Alegria, Ph.D

Publisher

University of South Florida St. Petersburg

Document Type

Thesis

Publication Date

2019

Date Issued

June 27, 2019

Abstract

Digital elevation model (DEM) resolution and accuracy are critical to any geographic information system (GIS) terrain and hydrological modeling application. Changes in DEM resolution will impact modeled elevation, slope and curvature spatial location, fractal properties, statistical parameters and accuracy in modeling real-world terrain conditions. As hydrological modeling relies on statistical and spatial terrain parameters as inputs, changes in DEM resolution will also, in turn, impact stream delineation and stream spatial location, fractal properties, statistical parameters, and accuracy in modeling real-world stream conditions. These impacts may manifest differently in flat or mountainous terrains and certain DEM resolutions will model real-world conditions better than others. Theoretically, higher-resolution data are preferred to model elevations, slopes, curvatures and delineate streams, but many regions do not have access to high-resolution data. Since the spatial location of elevations, slopes, curvatures and streams matter in terrain and hydrological modeling, it is necessary to evaluate the application of spatial location analysis of streams versus traditional statistical methods at different resolutions of DEMs. A comprehensive multiscale sensitivity study applying statistical indexes of complexity to characterize geospatial and statistical changes in modeled elevations, slopes, curvatures and delineated streams may provide insight into impacts of varying DEM resolution and implications for modeling accuracy. Original and resampled 1.5, 10, 30 and 90m LiDAR (Light Detection and Ranging), USGS (United States Geological Survey) and SRTM (Shuttle Radar Topography Mission) DEMs were compared to determine spatial and statistical impacts of DEM resolution on DEM surface fractal complexity and complexity of delineated streams, evaluating accuracy of DEM elevation, slope and curvature via root-mean-square error (RMSE) and accuracy in stream delineation through percent error. Results showed fractal complexity in terrain and modeled streams decreased, while RMSE and percent error increased with coarser resolution. Original and resampled DEMs of identical cell size produced comparable surface fractal complexities and RMSE values in flatter terrain. Statistical comparability decreased as terrain became more mountainous, however, suggesting greater sensitivity to DEM resolution than flat terrain. Both flat and mountainous terrain generated cases of comparable DEM fractal complexities and RMSE values between original and resampled DEM resolution of identical cell size, but contained spatially different elevation, slope, curvature and error when mapped. Likewise, original and resampled DEMs of identical cell size, in both flat and mountainous terrains, delineated modeled stream networks with comparable statistical results, but displayed spatially different locations when mapped. This mismatch suggests that in a hydrological modeling context, where spatial location matters, application of traditional statistical indexes of complexity characterizing spatial change or measuring spatial accuracy of DEM surfaces and their delineated streams may prove limited and problematic because statistical results may not indicate spatial sensitivity of the results.

Comments

A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science Department of Environmental Science, Policy and Geography College of Arts and Science University of South Florida, St Petersburg

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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