Quantifying the influences of various ecological factors on land surface temperature of urban forests

Abstract

a b s t r a c tIdentifying factors that influence the land surface temperature (LST) of urban forests can help improve simulations and predictions of spatial patterns of urban cool islands. This requires a quantitative analytical method that combines spatial statistical analysis with multi-source observational data. The purpose of this study was to reveal how human activities and ecological factors jointly influence LST in clustering regions (hot or cool spots) of urban forests. Using Xiamen City, China from 1996 to 2006 as a case study, we explored the interactions between human activities and ecological factors, as well as their influences on urban forest LST. Population density was selected as a proxy for human activity. We integrated multi-source data (forest inventory, digital elevation models (DEM), population, and remote sensing imagery) to develop a database on a unified urban scale. The driving mechanism of urban forest LST was revealed through a combination of multi-source spatial data and spatial statistical analysis of clustering regions. The results showed that the main factors contributing to urban forest LST were dominant tree species and elevation. The interactions between human activity and specific ecological factors linearly or nonlinearly increased LST in urban forests. Strong interactions between elevation and dominant species were generally observed and were prevalent in either hot or cold spots areas in different years. In conclusion, quantitative studies based on spatial statistics and GeogDetector models should be conducted in urban areas to reveal interactions between human activities, ecological factors, and LST.

Analytical study of land surface temperature with NDVI and NDBI using Landsat 8 OLI and TIRS data in Florence and Naples city, Italy

“…Urban hot spots (UHS), the special urban thermal features, experience extreme heat stress mainly developed by man-made activities within a UHI zone (Chen, Zhao, Li, & Yin, 2006;Coutts, White, Tapper, Beringer, & Livesley, 2016;Feyisa, Meilby, Jenerette, & Pauliet, 2016;Lopez, Heider, & Scheffran, 2017;Pearsall, 2017;Ren et al, 2016). So, identifying these UHS for mitigation purpose becomes an important task to maintain the ecological balance within a city.…”

Respective influence of vertical mountain differentiation on debris flow occurrence in the Upper Min River, China

“…Ju et al 60 applied GEO to the analysis of driving forces for land expansion. GEO is widely used in fields such as soil pollution, public health 61 , 62 , groundwater contamination, ecology 63 , 64 , and meteorology 65 , 66 . There are both qualitative data and quantitative data in the influencing factors of debris flow distribution, so GEO is very suitable for discussing the respective influence of vertical mountain differentiation on debris flow occurrence.…”

Analysis of Heavy Metal Sources in the Soil of Riverbanks Across an Urbanization Gradient

“…The strong combinations included the interaction between strong factors and weak factors, e.g., pH∩OM of Cu, and the interaction between two weak factors, e.g., SDi ∩ HD. The reason for this could be fewer human activities and the greater variation of the terrain [ 43 ]. Therefore, the strong interaction combinations were mainly between topography and topography, topography and soil, topography and green land characteristic.…”