Abstract
TRUST (Thermal Remote sensing Unmixing for Subpixel Temperature) is a spectral unmixing method developed to provide subpixel abundances and temperatures from radiance images in the thermal domain. By now, this method has been studied in simple study cases, with a low number of endmembers, high spatial resolutions (1 m) and more than 30 spectral bands in the thermal domain. Thus, this article aims to show the applicability of TRUST on a highly challenging study case: the analysis of a heterogeneous urban environment with airborne multispectral (eight thermal bands) images at 8-m resolution. Thus, this study is necessary to generalize the use of TRUST in the analysis of urban thermography. Since TRUST allows linking intrapixel temperatures to specific materials, it appears as a very useful tool to characterize Surface Urban Heat Islands and its dynamics at high spatial resolutions. Moreover, this article presents an improved version of TRUST, called TRUST-DNS (Day and Night Synergy), which takes advantage of daytime and nighttime acquisitions to improve the unmixing performances. In this study, both TRUST and TRUST-DNS were applied on daytime and nighttime airborne thermal images acquired over the center of Madrid during the DESIREX (Dual-use European Security IR Experiment) campaign in 2008. The processed images were obtained with the Aircraft Hyperspectral Scanner (AHS) sensor at 4-m spatial resolution on 4 July. TRUST-DNS appears to be more stable and slightly outperforms TRUST on both day and night images. In addition, TRUST applied on daytime outperforms TRUST on nighttime, illustrating the importance of the temperature contrasts during day for thermal unmixing.
Highlights
Global warming influences every region of the world
Since Thermal Remote sensing Unmixing for Subpixel Temperature (TRUST) has been shown to outperform other thermal unmixing techniques [11,16], this study focused on comparisons between TRUST applied on day and night images and TRUST-DNS
It was shown that both TRUST and TRUST-DNS can be applied on eight-band airborne images of urban environments at 8-m resolution
Summary
Global warming influences every region of the world. Its effects have been visible for a long time: ice loss in the poles with a consequent increase of the sea level, extreme meteorological events with an increase in rainfalls, more frequent droughts, increase in the frequency and intensity of heat waves [1], etc. It has been well documented that urban environments suffer sharper increases of their temperatures than rural areas [2]. This is known as Urban Heat Island (UHI) effect [2]. During the summer of 2019, the heat waves in France reached up to 45 ◦C, corresponding to 4.5 ◦C higher than the heat waves of 2003, which have been estimated to have killed around 70,000 people in Europe [3] Solutions to stop this increase of heat wave frequencies and intensities are required. For the solutions to be adapted to deal with the problem, a good understanding of the sources, causes, and dynamics of urban warming is necessary
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