Document Type

Thesis - Open Access

Award Date


Degree Name

Master of Science (MS)



First Advisor

Xiaoyang Zhang

Second Advisor

Geoffrey Henebry


land surface phenology, land surface temperature, MODIS, NDVI, remote sensing, urbanization, urban environmental change, urban heat island, Web-Enabled Landsat Data


Between one-third and one-half of Earth’s land surface has been directly altered by humans, with the remainder comprised of “human-dominated ecosystems” (Vitousek et al. 2008). Earth’s population has surpassed seven billion, projected to increase by 2.5 billion by 2050 in urban areas alone (United Nations 2014). The rapid urbanization of our planet drives global environmental changes in hydrosystems, biodiversity, biogeochemical cycles, land use and land cover, and climate (Grimm et al. 2008). Urban areas alter local atmospheric conditions by modifying surface albedo and consequently evapotranspiration, releasing energy through anthropogenic heat sources, and increasing atmospheric aerosols, leading to increased temperatures in cities compared with surrounding rural areas, known as the “urban heat island” effect (Arnfield 2003). Recent urbanization of our planet has generated calls for remote sensing research related to the impacts of urban areas and urbanization on the natural environment (Herold 2009; Seto, Güneralp, and Hutyra 2012). Spatially extensive, high spatial resolution data products are needed to capture phenological patterns in regions with heterogeneous land cover and external drivers such as cities, which are comprised of a mixture of land cover/land uses and experience microclimatic influences, namely the UHI effect (Fisher, Mustard, and Vadeboncoeur 2006; Melaas, Friedl, and Zhu 2013). Here I use the normalized difference vegetation index (NDVI) product provided by the Web-Enabled Landsat Data (WELD) project to analyze the impacts of urban areas and urban heat islands on the seasonal development of the vegetated land surface on an urban-rural gradient for six regions located in the Upper Midwest of the United States. I fit NDVI observations from 2003-2012 as a convex quadratic function of thermal time as accumulated growing degree-days (AGDD) calculated from the Moderate-resolution Imaging Spectroradiometer (MODIS) land surface temperature product to model decadal land surface phenology metrics. In general, duration of growing season measured in AGDD in green core areas is equivalent to duration of growing season in urban extent areas, but significantly longer than duration of growing season in regions outside of the urban extent. I found an exponential relationship in the difference of duration of growing season between urban and surrounding rural regions as a function of distance from urban core areas in perennial vegetation land cover types, with an average magnitude of 669 AGDD and the influence of urban areas extending over 11 km from urban core areas. A linear relationship exists between the modeled rate of vegetation green up and maximum NDVI for perennial forests, but not for annual croplands. At the regional scale, relative change in duration of growing season does not appear to be significantly related to total area of urban extent, population, or latitude, with the distance and magnitude that urban areas influence vegetation in and near cities being relatively uniform, although larger urban areas have a greater impact on duration of growing season in terms of total area.


Includes bibliographical references (pages 71-82)



Number of Pages



South Dakota State University


Copyright © 2015 Cole Krehbiel