The footprint of urban heat island effect in China

Abstract

Urban heat island (UHI) is one major anthropogenic modification to the Earth system that transcends its physical boundary. Using MODIS data from 2003 to 2012, we showed that the UHI effect decayed exponentially toward rural areas for majority of the 32 Chinese cities. We found an obvious urban/rural temperature “cliff”, and estimated that the footprint of UHI effect (FP, including urban area) was 2.3 and 3.9 times of urban size for the day and night, respectively, with large spatiotemporal heterogeneities. We further revealed that ignoring the FP may underestimate the UHI intensity in most cases and even alter the direction of UHI estimates for few cities. Our results provide new insights to the characteristics of UHI effect and emphasize the necessity of considering city- and time-specific FP when assessing the urbanization effects on local climate.

Urbanization Effects on Vegetation and Surface Urban Heat Islands in China’s Yangtze River Basin

“…We further compared the urban area extracted using nighttime data with that from Landsat data (maximum likelihood classification method). The results showed that the urban area extracted using the method in this study was larger than that from Landsat data ( Table 2); however, it is appropriate for this study due to these reasons: (a) the footprint of SUHI was larger than the actual urban size according to previous studies [40,48,49]; (b) the urbanization primarily occurred in the suburban areas according to previous studies [26,36]; (c) the study period in this study was 2001-2016, the land cover maps used were during 2001-2013, and the urban area may expand during 2014-2016. Finally, we generated the buffer zone between 20 and 25 km from the urban areas, and we excluded the pixel with DN > 10 (SNLD) in the 20-25 km buffer and defined it as rural area [5,41].…”

“…Finally, we generated the buffer zone between 20 and 25 km from the urban areas, and we excluded the pixel with DN > 10 (SNLD) in the 20-25 km buffer and defined it as rural area [5,41]. The rural areas in this study were set larger than previous studies, since the footprint of UEs was much larger than the urban areas in previous studies [5,40,48,49]. We did not select larger buffer zones for reducing the uncertainties due to different climate conditions and topography [48].…”

“…The rural areas in this study were set larger than previous studies, since the footprint of UEs was much larger than the urban areas in previous studies [5,40,48,49]. We did not select larger buffer zones for reducing the uncertainties due to different climate conditions and topography [48]. The accuracy of this method of defining urban area may be lower than those using the higher spatial resolution images (e.g., Landsat data), but it is fast and enough for matching the 1 km spatial resolution of MODIS EVI (MOD13A2) and LST (MOD11A2) data.…”

“…However, the SNLD data has a blooming effect; the urban area extracted from SNLD was usually larger than the real urban area [44,47]. Figures 2c and 3c showed that the urban areas at WH extracted from SNLD contained the Yangtze River and some lakes, which should be removed in SUHI's study [3,10,48]. In addition, MODIS LCD can extract the water body accurately (Figures 2d and 3d).…”

Forest Management Challenges for Sustaining Water Resources in the Anthropocene

“…By 2025 it is projected that there will be 50 Mega Cities with the fastest growth occurring in Africa and Asia. Urban expansion is usually characterized as increasing impervious surface areas and losing agricultural and forest lands bring many well-recognized environmental consequences such as water shortages [21,22], water and air pollution [23], and urban heat island [24]. In particular, urbanization affects watershed microclimate, surface water dynamics, groundwater recharge, stream geomorphology, biogeochemistry, and stream ecology [23,25].…”