Impacts of Thermal Time on Land Surface Phenology in Urban Areas

Cole Krehbiel,Geoffrey Henebry,Xiaoyang Zhang

doi:10.3390/rs9050499

Abstract

Urban areas alter local atmospheric conditions by modifying surface albedo and consequently the surface radiation and energy balances, releasing waste heat from anthropogenic uses, and increasing atmospheric aerosols, all of which combine to increase temperatures in cities, especially overnight, compared with surrounding rural areas, resulting in a phenomenon called the “urban heat island” effect. Recent rapid urbanization of the planet has generated calls for remote sensing research related to the impacts of urban areas and urbanization on the natural environment. 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. Here we use the 30 m normalized difference vegetation index (NDVI) product from the Web-Enabled Landsat Data (WELD) project to analyze the impacts of urban areas and their surface heat islands on the seasonal development of the vegetated land surface along an urban–rural gradient for 19 cities located in the Upper Midwest of the United States. We fit NDVI observations from 2003–2012 as a quadratic function of thermal time as accumulated growing degree-days (AGDD) calculated from the Moderate-resolution Imaging Spectroradiometer (MODIS) 1 km land surface temperature product to model decadal land surface phenology metrics at 30 m spatial resolution. 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 areas outside of the urban extent. We found an exponential relationship in the difference of duration of growing season between urban and surrounding rural areas as a function of distance from urban core areas for perennial vegetation, with an average magnitude of 669 AGDD (base 0 °C) and the influence of urban areas extending greater than 11 km from urban core areas. 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. The distance and magnitude that urban areas exert influence on vegetation in and near cities is relatively uniform.

Highlights

Recent increases in population have largely been concentrated in urban areas, increasing from only 13% of total global population in 1900 to 54% by 2014 [1,2]
Using Landsat data for phenology studies allows for local to regional scale analyses, offering a spatial resolution that is useful for exploring factors that influence phenology including land use and urban heat islands [24]
accumulated growing degree-days (AGDD) was equivalent between green core areas (GCAs) and urban extent (UE) areas and higher than areas the 19 cities exhibits this pattern based on the equivalence testing analysis (Lincoln, NE)

Summary

Introduction

Recent increases in population have largely been concentrated in urban areas, increasing from only 13% of total global population in 1900 to 54% by 2014 [1,2]. Urban land expansion has irreversible impacts on the natural environment, including the loss of agricultural lands, fragmentation of Remote Sens. 2017, 9, 499 ecosystems, reduction of biodiversity, and alteration of local climate [3]. Urban land cover/land use and change can potentially alter local to regional climate on daily, seasonal, and even annual scales [4]. The clearest example of urban climate modification is the phenomenon where urban temperatures are generally higher than the surrounding countryside, or the urban heat island (UHI) effect [5]. UHI intensity is related to patterns of land use/land cover changes, including the composition of water, vegetation, and built-up areas [6]. The effects of the UHI and land use/land cover change are linked to modified surfaces that affect the transfer and storage of airflow, water, and heat [7]

Methods

Results

Discussion

Conclusion