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THE DETECTION AND CHARACTERIZATION OF URBANIZATION, INDUSTRIALIZATION, AND LONGWALL MINING IMPACTS ON FOREST ECOSYSTEMS THROUGH THE USE OF GIS AND REMOTE SENSING TECHNIQUES

Pfeil-McCullough, Erin (2017) THE DETECTION AND CHARACTERIZATION OF URBANIZATION, INDUSTRIALIZATION, AND LONGWALL MINING IMPACTS ON FOREST ECOSYSTEMS THROUGH THE USE OF GIS AND REMOTE SENSING TECHNIQUES. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Abstract

Urbanization has far reaching and significant effects on forest ecosystems, directly through urban development and indirectly through supportive processes such as coal mining and agriculture. Urban processes modify the landscape leading to altered hillslope hydrology, increased disturbance, and the introduction of non-native forest pathogens. This dissertation addresses several challenges in our ability to detect these urbanization impacts on forests via geospatial analyses.
The role of forests in urban hydrological processes has been extensively studied, but the impacts of urbanized hydrology on forests remain poorly examined. This dissertation documented impacts to hydrology and forests at variety of temporal and spatial scales: 1) A geospatial comparison of the historic and contemporary forests of Allegheny County Pennsylvania revealed substantial shifts in tree species, but less change in the species soil moisture preference. These results document additional evidence that increased heterogeneity in urban soil moisture alters forest structure. 2) To examine soil moisture changes, impacts of longwall mine subsidence were assessed by using a Landsat based canopy moisture index and hot spot analysis tools at the forest patch scale. Declines in forest canopy moisture were detected over longwall mines as mining progressed through time, and results contradicted assumptions that the hydrological impacts overlying LMS recover within 4-5 years following subsidence. 3)Utilizing a landslide susceptibility model (SIMAP), increases in landslide susceptibility were predicted in Pittsburgh, PA based on several scenarios of ash tree loss to the emerald ash borer (EAB), a bark beetle that rapidly kills ash trees. This model provides a tool to predict changes in landslide susceptibility following tree loss, increasing the understanding of urban forest function and its role in slope stability. Detecting how urbanized hydrology impacts forest health, function, and development is fundamental to sustaining the services forests provide. Results from this dissertation will ultimately allow improvements in the management and protection of both trees and water resources in urban systems and beyond.


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Pfeil-McCullough, Erinekpfeil@gmail.comekp9
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairBain, Josefdbain@pitt.edudbain
Committee MemberElliott, Emilyeelliott@pitt.edueelliott
Committee MemberRamsey, Michaelmramsey@pitt.edumramsey
Committee MemberWerne, Josefjwerne@pitt.edujwerne
Committee MemberMcNeil, BrendenBrenden.McNeil@mail.wvu.edu
Date: 1 July 2017
Date Type: Publication
Defense Date: 17 March 2017
Approval Date: 1 July 2017
Submission Date: 7 April 2017
Access Restriction: 5 year -- Restrict access to University of Pittsburgh for a period of 5 years.
Number of Pages: 126
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Geology and Planetary Science
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: longwall mining, urbanization, industrialization, urban forests, GIS, remote sensing, satellite imagery
Date Deposited: 01 Jul 2017 21:51
Last Modified: 01 Jul 2017 21:51
URI: http://d-scholarship.pitt.edu/id/eprint/31334

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