Assessing scaling effect in downscaling land surface temperature in a heterogenous urban environment

It is confirmed that there exists a scaling effect in downscaling land surface temperature (DLST) processes. However, a literature review indicates that quantifying and fully understanding scaling effect in DLST processing remains unclear. In this study, a main goal is to quantify, assess and understand scaling effect in downscaling LST product processes at different higher spatial resolutions and spatial extents. A machine leaning model and a traditional multivariate regression model were adopted with corresponding scaling factors extracted from ASTER 15-30 m optical multispectral data and Airborne Imaging Spectrometer for Different Applications (AISA) 2 m hyperspectral visible-near infrared data. MODIS 990 m LST and ASTER 90 m LST products were downscaled to high and very high resolution LST maps. In addition, ETM+ 60 m retrieved LST and Thermal Airborne Broadband Imager (TABI) 2 m retrieved LST and its upscaled LSTs were used to verify higher resolution DLST maps. The experimental results demonstrate that scaling effect in downscaling LST processes is significant, especially downscaling LST to high and very high resolution LST maps. One innovation point derived from findings by assessing the scaling effect in DLST processing is that when DLST processes are at spatial resolutions beyond a range (20-30 m in this study) measured from semivariograms, the processes are safe and their results are reasonable and reliable, and thus their scaling effect may be ignored, but when spatial resolutions and spatial extent lag distance within the range, the DLST processes are not safe, and their results are not reliable and thus the scaling effect has to be considered. Therefore, it is recommended that before conducting a DLST processing project, a range needs to be calculated by plotting semivariograms with high or very high resolution images (better to include three visible and one NIR bands), then DLST processes may be conducted at spatial resolutions lower than and equal to the range.

Automated summary

This study aims to quantify, assess, and understand the scaling effect in downscaling land surface temperature (DLST) processes at different higher spatial resolutions and spatial extents. Experimental results show that the scaling effect is significant in downscaling LST to high and very high resolution LST maps. When DLST processes are at spatial resolutions beyond a certain range, the processes are safe and their results are reliable, but within the range, the scaling effect needs to be considered.