Relationship between Terra/ASTER Land Surface Temperature and Ground-observed Air Temperature

Abstract

This study estimated near-ground air temperature (T a) from Terra/ASTER-obtained land surface temperature (LST) for different land cover categories in a hilly region under a clear and calm night in winter. Temperature differences (ΔT) between LST and T a were related to the land cover categories and their spatial extents. In the extended area of forest land, spatially averaged ΔT in the area (ΔT m) was −0.1°C, and the relationship between LST and T a showed less variability (standard deviation of ΔT (SD)=0.8°C) and high correlation (coefficient of determination between T a and LST (R 2)=0.70). This result suggests we can evaluate T a directly from LST in this area. In the extended area of bare land, ΔT m , SD and R 2 were −1.5°C, 0.9°C and 0.85, respectively, which indicated that accurate estimation of T a is possible by correcting LST by ΔT m. In the extended area of artificial land, ΔT m showed statistically non-significant trend. In the case of intermingled area of more than one type of land cover, ΔT m, SD and R 2 were −0.8°C, 0.9°C and 0.71 in the forest land of the intermingled area, which suggested that we can estimate T a in this area precisely by correcting LST by ΔT m. In the bare land of the intermingled area, though ΔT m was −1.4°C, large variations (SD=1.4°C) and low correlations (R 2 =0.33) were found.

Evaluation of the Effect of Urban Redevelopment on Surface Urban Heat Islands

“…The latter is often a few degrees higher than the former given optimal conditions for surface-temperature measurement [9,10]. In addition, areas with the highest LSTs may not exactly correspond to those with the highest ambient air temperature, and the linear relationship between these two parameters is sometimes not obvious [8,11,20]. Furthermore, more qualitative UHI measurements can be obtained by collecting data in situ, involving asking users about their thermal sensitivity and site practice through questionnaires, interviews, or mental maps, for example [21][22][23].…”

“…Previous studies have mainly focused on studying differences in ground temperatures as a function of land-use land cover and its evolution at the city level [16,16,20,[33][34][35], temporal trends in urban SUHI in urban areas [18,36,37], the refreshing impact of parks on their surroundings [15,38,39], the evolution of SUHI as a function of day and night [9,34,40,41], the impact of vegetation on LST at the urban scale [12,36,37,42], comparison of surface temperatures and air temperature [8][9][10]20,43,44], the impact of surface temperatures on health [30,41] and transversely at surface temperatures at moderate resolutions (MODIS 1 km) [16,20,[34][35][36]42,45] but, to our knowledge, there are no similar studies such as ours that analyze the thermal monitoring of site redevelopment at such a detailed spatial and temporal resolution.…”

Spatio-Temporal Evolution Analysis of the Urban Heat Island: A Case Study of Zhengzhou City, China

“…Rao (1972) [9] first applied remote sensing images to land surface temperature (LST) retrieval. Since then, NOAA (National Oceanic and Atmospheric Administrat)/AVHRR (Advanced Very High Resolution Radiometer) [10,11], MODIS (Moderate-resolution Imaging Spectroradiometer) [12,13], Aster [14][15][16][17], HJ-1 (HJ-1 Satellite) [18,19], Landsat series [20][21][22] and other satellite images with various temporal and spatial scales have been widely applied to the study of LST retrieval. Compared with other images, the Landsat series has many advantages, such as high spatial resolution, rich spectral information, archived data and free access.…”

Integrating Satellite-Derived Data as Spatial Predictors in Multiple Regression Models to Enhance the Knowledge of Air Temperature Patterns

“…Twenty-eight explanatory variables are used to estimate the air temperature over the study area. They have been selected from the literature [22][23][24][25][26]29,[32][33][34][35][36][37][38][39][40][41][42][43][44][45]. The variables belong to various categories and can directly be obtained from the supplying organizations or produced by geomatics or remote sensing ( Table 3).…”