Determining the Mechanisms that Influence the Surface Temperature of Urban Forest Canopies by Combining Remote Sensing Methods, Ground Observations, and Spatial Statistical Models

Shudi Zuo,Wang Man,Yaying Li,Chengdong Xu,Yin Ren,Yilan Liao,Weiyin Chang,Qi Chen,Xiaodong Song,Shaoqing Dai,Jianfeng Tang

doi:10.3390/rs10111814

Abstract

The spatiotemporal distribution pattern of the surface temperatures of urban forest canopies (STUFC) is influenced by many environmental factors, and the identification of interactions between these factors can improve simulations and predictions of spatial patterns of urban cool islands. This quantitative research uses an integrated method that combines remote sensing, ground surveys, and spatial statistical models to elucidate the mechanisms that influence the STUFC and considers the interaction of multiple environmental factors. This case study uses Jinjiang, China as a representative of a city experiencing rapid urbanization. We build up a multisource database (forest inventory, digital elevation models, population, and remote sensing imagery) on a uniform coordinate system to support research into the interactions that influence the STUFC. Landsat-5/8 Thermal Mapper images and meteorological data were used to retrieve the temporal and spatial distributions of land surface temperature. Ground observations, which included the forest management planning inventory and population density data, provided the factors that determine the STUFC spatial distribution on an urban scale. The use of a spatial statistical model (GeogDetector model) reveals the interaction mechanisms of STUFC. Although different environmental factors exert different influences on STUFC, in two periods with different hot spots and cold spots, the patch area and dominant tree species proved to be the main factors contributing to STUFC. The interaction between multiple environmental factors increased the STUFC, both linearly and nonlinearly. Strong interactions tended to occur between elevation and dominant species and were prevalent in either hot or cold spots in different years. In conclusion, the combining of multidisciplinary methods (e.g., remote sensing images, ground observations, and spatial statistical models) helps reveal the mechanism of STUFC on an urban scale.

Highlights

With the acceleration of urbanization, more and more urban forest distributed in highly populated environments has become an important part of urban landscapes [1]
Landsat 5 and 8 images from 2004 and 2014 were integrated with the corresponding forest-management planning inventory (FMPI) data. For each of these two years, a multisource dataset was generated from the same boundaries and coordinate system, in which the surface temperatures of urban forest canopies (STUFC) of patches corresponded to certain environmental factors
The quantitative analysis of the GeogDetector spatial statistical model shows that the dominant species factor explained more STUFC heterogeneity than the other environmental factors, which indicates that differences in transpiration and shading between different tree species are the dominant reasons for STUFC on the city scale

Summary

Introduction

With the acceleration of urbanization, more and more urban forest (definition: all the trees within the administrative boundaries of the city) distributed in highly populated environments has become an important part of urban landscapes [1]. Urban forest mainly includes urban forest land, trees in parks, trees along streets, and trees dispersed in residential land. In addition to their use for landscape decoration, residents appreciate the services provided by the branches and leaves of urban forest [2,3]. Water transpiration through leaves further reduces the radiant heat, and this cooling effect mitigates the urban heat island effect and improves the quality of the urban ecological environment [4]. The target of forest-resource surveys in China, India, Sweden, and the UK has expanded from traditional forests to urban forest [5,6]

Methods

Results

Discussion

Conclusion