People, landscape, and urban heat island: dynamics among neighborhood social conditions, land cover and surface temperatures
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Urban heat island studies have found that land cover, neighborhood social conditions and temperatures are correlated. This received great academic attention because of potential ecological, social and health impacts. However, the processes and causalities behind such correlations remain unclear, which impede designing effective heat mitigation approaches.
Our study aims to answer two questions: (1) Do social conditions influence temperature independent of land cover? (2) Is land cover more closely associated with temperature than neighborhood social conditions or vice versa?
The analysis is for the year 2000 and the Gwynns Falls watershed in Baltimore, Maryland. Census data for 297 block groups and remote sensed data for land cover and surface temperature were used. To answer question 1, we used structural equation modeling to build and compare model fitness. We conducted partial correlation and regression analysis to answer question 2.
Land cover (building and trees) leads both social conditions (race and income) and temperature to vary across space. When holding land cover constant, social conditions significantly contribute to temperature variation.
This study extends understanding beyond simple correlation and determined that land cover influences the spatial variation in neighborhood social conditions and temperature.
KeywordsUrban heat island Neighborhood social condition Land cover Land surface temperature Structural equation modeling Baltimore
This research was supported by funding from the National Science Foundation Long-Term Ecological Research (LTER) Program (0423476), and the National Natural Science Foundation of China (41301645).
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