Date of Award

Summer 7-17-2023

Document Type

Geospatial Analysis Masters Capstone

Degree Name

Master of Science

Department

Geography

Department Chair or Program Director

Gallagher, Jackie

First Advisor

Dr. Marco Millones Mayer

Second Advisor

Dr. Jackie Gallagher

Third Advisor

Dr. Scott Allen

Fourth Advisor

Dr. Elsa Nickl

Major or Concentration

Geospatial Analysis

Abstract

Surface urban heat islands (SUHIs) are land surfaces with high concentrations of impervious surfaces like roofs, roads, sidewalks and other infrastructures that trap, absorb, and re-emit heat throughout the day/night and typically present higher temperatures than their surrounding rural areas. In this study, I evaluate how presence of and distance to SUHIs are associated with water temperature in the lower Chesapeake Bay watershed for the summer of 2019. When heavy precipitation events occur, flooding creates stormwater runoff, which is exposed to the hotter temperatures in urban areas. This introduces thermal pollution to nearby rivers and streams disrupting aquatic ecosystems. The hypothesis for this research is that the closer water temperature points are to SUHIs, the warmer the temperature measured will be. To assess this, I processed Landsat 8 and 9 scenes in order to derive land surface temperature (LST), normalized difference vegetation index (NDVI), and normalized difference build-up index (NDBI). I also processed land cover from the national land cover dataset (NLCD) and a digital elevation model (DEM) from which I derived flow direction (FD) and flow accumulation (FA). I used water temperatures measured by water quality stations from 25 sources as well. If areas with a surface temperature were half a standard deviation above the agricultural land cover LST average, they were defined as SUHIs, following Kaplan et al. (2018). The other datasets were used to extract other factors that can impact temperature or the relationship between distance to SUHIs and temperature. In addition, I also processed local climate zones (LCZs) to validate the identified SUHIs. To extract distance from SUHI areas and the water temperature datapoints, I used ArcGIS’s Euclidean Distance and Direction Distance tools. These were calculated for various cases, including; no-distance (contained within SUHI), omni-directional distance, and upstream/downstream distance. Some of these methodological attempts were more successful 2 than others. Overall results do not show a strong relationship between warmer water temperatures and proximity to SUHIs; therefore, in general terms, the hypothesis is not supported. However, there are some noteworthy findings; a) there are warmer water temperatures near urban centers where most of the SUHIs are located; b) elevation has the strongest influence and highest significance on water temperature with the trends of the variables explored (i.e., at higher elevations, the water temperature is cooler while at lower elevations, the water temperature is warmer); and, c) Euclidean distance to SUHIs and NDVI are other significant factors. With more time and resources, I would include more data on environmental confounding factors and use improved methods to calculate various distance measures, which would likely help tease out more specific relationships between water temperature and SUHIs as well as to interpret their correlations.

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