Abstract
Urban Heat Islands (UHIs) at the surface and canopy levels are major issues in urban planification and development. For this reason, the comprehension and quantification of the influence that the different land-uses/land-covers have on UHIs is of particular importance. In order to perform a detailed thermal characterisation of the city, measures covering the whole scenario (city and surroundings) and with a recurrent revisit are needed. In addition, a resolution of tens of meters is needed to characterise the urban heterogeneities. Spaceborne remote sensing meets the first and the second requirements but the Land Surface Temperature (LST) resolutions remain too rough compared to the urban object scale. Thermal unmixing techniques have been developed in recent years, allowing LST images during day at the desired scales. However, while LST gives information of surface urban heat islands (SUHIs), canopy UHIs and SUHIs are more correlated during the night, hence the development of thermal unmixing methods for night LSTs is necessary. This article proposes to adapt four empirical unmixing methods of the literature, Disaggregation of radiometric surface Temperature (DisTrad), High-resolution Urban Thermal Sharpener (HUTS), Area-To-Point Regression Kriging (ATPRK), and Adaptive Area-To-Point Regression Kriging (AATPRK), to unmix night LSTs. These methods are based on given relationships between LST and reflective indices, and on invariance hypotheses of these relationships across resolutions. Then, a comparative study of the performances of the different techniques is carried out on TRISHNA synthesized images of Madrid. Since TRISHNA is a mission in preparation, the synthesis of the images has been done according to the planned specification of the satellite and from initial Aircraft Hyperspectral Scanner (AHS) data of the city obtained during the DESIREX 2008 capaign. Thus, the coarse initial resolution is 60 m and the finer post-unmixing one is 20 m. In this article, we show that: (1) AATPRK is the most performant unmixing technique when applied on night LST, with the other three techniques being undesirable for night applications at TRISHNA resolutions. This can be explained by the local application of AATPRK. (2) ATPRK and DisTrad do not improve significantly the LST image resolution. (3) HUTS, which depends on albedo measures, misestimates the LST, leading to the worst temperature unmixing. (4) The two main factors explaining the obtained performances are the local/global application of the method and the reflective indices used in the LST-index relationship.
Highlights
Canopy Urban Heat Islands (UHIs), defined as the higher air temperatures of urban areas compared to surrounding countryside [1], have been shown to influence human health [2,3], to affect urban air pollution [4], and to alter the energy consumption needs [5,6]
It has been shown that Surface Urban Heat Islands (SUHIs) should be measured during the night to be informative on the urban heat islands at canopy level [12], since surface and canopy heat islands are more decorrelated during day
This paper focuses on the study of SUHIs with TRISHNA-like [13] multispectral satellite
Summary
Canopy Urban Heat Islands (UHIs), defined as the higher air temperatures of urban areas compared to surrounding countryside [1], have been shown to influence human health [2,3], to affect urban air pollution [4], and to alter the energy consumption needs [5,6]. Spaceborne remote sensing can cover the city together with rural areas around, it presents revisit times from some days to some weeks, and it allows to measure Land Surface Temperatures (LSTs) by using the Thermal InfraRed (TIR) bands of the sensors. These LSTs can be used to estimate Surface Urban Heat Islands (SUHIs). These SUHIs are defined as the higher surface temperatures in urban areas than in surrounding rural ones [11,12]. It has been shown that SUHI should be measured during the night to be informative on the urban heat islands at canopy level [12], since surface and canopy heat islands are more decorrelated during day
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