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The urban heat island effect poses a growing threat to human society, especially in densely populated and developed megacities. With the introduction of the Local Climate Zones (LCZ) framework, new perspectives and findings have been brought to urban heat island studies. This study investigated the cooling effect of vegetation and albedo on the surface urban heat island (SUHI) in the classification system of LCZ during different seasons, using three Chinese megacities as case study areas. Single-factor linear regression and Pearson's correlation coefficient were applied to analyze the seasonal cooling effect of both albedo and the NDVI on the SUHI within different LCZs. The results show that (1) the variability of the SUHI is reflected in its dominance and intensity within certain LCZs in different cities and in the efficiency of cooling factors; (2) the cooling effect of vegetation is dominant in each season, and the cooling effect produced by albedo within specific seasons can be differentiated by LCZs. This study provides valuable information for the mitigation of the SUHI magnitude in specific regions and at specific times of the year. [ABSTRACT FROM AUTHOR]

Harmonization of satellite imagery provides a good opportunity for studying land surface temperature (LST) as well as the urban heat island effect. However, it is challenging to use the harmonized data for the study of LST due to the systematic bias between the LSTs from different satellites, which is highly influenced by sensor differences and the compatibility of LST retrieval algorithms. To fill this research gap, this study proposes the comparison of different LST images retrieved from various satellites that focus on Hong Kong, China, by applying diverse retrieval algorithms. LST images generated from Landsat-8 using the mono-window algorithm (MWAL8) and split-window algorithm (SWAL8) would be compared with the LST estimations from Sentinel-3 SLSTR and Himawari-8 using the split-window algorithm (SWAS3 and SWAH8). Intercomparison will also be performed through segregated groups of different land use classes both during the daytime and nighttime. Results indicate that there is a significant difference among the quantitative distribution of the LST data generated from these three satellites, with average bias of up to −1.80 K when SWAH8 was compared with MWAL8, despite having similar spatial patterns of the LST images. The findings also suggest that retrieval algorithms and the dominant land use class in the study area would affect the accuracy of image-fusion techniques. The results from the day and nighttime comparisons revealed that there is a significant difference between day and nighttime LSTs, with nighttime LSTs from different satellite sensors more consistent than the daytime LSTs. This emphasizes the need to incorporate as much night-time LST data as available when predicting or optimizing fine-scale LSTs in the nighttime, so as to minimize the bias. The framework designed by this study will serve as a guideline towards efficient spatial optimization and harmonized use of LSTs when utilizing different satellite images associated with an array of land covers and at different times of the day. [ABSTRACT FROM AUTHOR]

Satellite-derived rugged land surface temperature (LST) is an important parameter indicating the status of the Earth's surface energy budget and its seasonal/temporal dynamic change. However, existing LST products from rugged areas are more prone to error when supporting applications in mountainous areas and Earth surface processes that occur at high spatial and temporal resolutions. This research aimed to develop a method for generating rugged LST with a high temporal and spatial resolution by using an improved ensemble LST model combining three regressors, including a random forest, a ridge, and a support vector machine. Different combinations of high-resolution input parameters were also considered in this study. The input datasets included Moderate Resolution Imaging Spectroradiometer (MODIS) LST datasets (MxD11A1) for nighttime, temporal Sentinel-2 Multispectral Instrument (MSI) datasets, and digital elevation model (DEM) datasets. The 30 m rugged LST datasets derived were compared against an in situ LST dataset obtained at Saihanba Forest Park (SFP) sites and an ASTER-derived 90 m LST, respectively. The results with in situ measurements demonstrated significant LST details, with an R2 higher than 0.95 and RMSE around 3.00 K for both Terra/MOD- and Aqua/MYD-based LST datasets, and with slightly better results being obtained from the Aqua/MYD-based LST than that from Terra/MOD. The inter-comparison results with ASTER LST showed that over 80% of the pixels of the difference image for the two datasets were within 2 K. In light of the complex topography and distinct atmospheric conditions, these comparison results are encouraging. The 30 m LST from the method proposed in this study also depicts the seasonality of rugged surfaces. [ABSTRACT FROM AUTHOR]

Sensible heat exchange has important consequences for urban meteorology and related applications. Directional radiometric surface temperatures of urban canopies observed by remote sensing platforms have the potential to inform estimations of urban sensible heat flux. An imaging radiometer viewing the surface from nadir cannot capture the complete urban surface temperature, which is defined as the mean surface temperature over all urban facets in three dimensions, which includes building wall surface temperatures and requires an estimation of urban sensible heat flux. In this study, a numerical microclimate model, Temperatures of Urban Facets in 3-D (TUF-3D), was used to model sensible heat flux as well as radiometric and complete surface temperatures. Model data were applied to parameterize an effective resistance for the calculation of urban sensible heat flux from the radiometric (nadir view) surface temperature. The results showed that sensible heat flux was overestimated during daytime when the radiometric surface temperature was used without the effective resistance that accounts for the impact of wall surface temperature on heat flux. Parameterization of this additional resistance enabled reasonably accurate estimates of urban sensible heat flux from the radiometric surface temperature. [ABSTRACT FROM AUTHOR]