TY - JOUR
T1 - Assessment of the TsHARP method for spatial downscaling of land surface temperature over urban regions
AU - Sattari, Farshid
AU - Hashim, Mazlan
AU - Sookhak, Mehdi
AU - Banihashemi, Saeed
AU - Beiranvand Pour, Amin
N1 - Funding Information:
We are thankful to the Universiti Teknologi Malaysia (UTM) for financial supporting this research by International Doctoral Fellowship (IDF). We are also grateful to Institute of Oceanography and Environment (INOS), Universiti Malaysia Terengganu (UMT) to provide facility for editing and revising the manuscript. The authors would like to thank the NASA Land Processes Distributed Active Archive Center (LP DAAC) and Earth remote Sensing Data Analysis Center (ERSDAC) for releasing free ASTER data used in this study. The authors would like to thank Dr. Klemen Zakšek for his helpful comments and valuable suggestions to improve this manuscript.
Publisher Copyright:
© 2022
PY - 2022/9
Y1 - 2022/9
N2 - Nowadays, acquiring high spatial and temporal land surface temperature (LST) is one of the significant factors in urban climate studies. This study aims to assess the sharpening thermal imagery (TsHARP) method, which is developed for determining the LST in urban regions. Whereas the original TsHARP method correlates the Normalized Difference Vegetation Index (NDVI) with the LST, the current study seeks to evaluate the performance of the TsHARP method by correlating between the LST and NDVI over urban areas. Additionally, it is intended to investigate the relationship between the impervious surfaces (IS) and LST. At this point, the Advanced Spaceborne Thermal Emission and Reflection Radiometer ASTER image of the year 2003 was used to retrieve the IS as well as the LST of the Kuala Lumpur city, Malaysia. To retrieve the main LST, IS and NDVI, ASTER Level1B data were used. On the other hand, ASTER land surface temperature products (AST08) was utilized to evaluate the downscaled LST (DLST) image. With selection of the ~1/4 of the pixels with lowest coefficient of variation (CV), the LST has more correlation with the IS in comparison with the NDVI, while the correlation between the IS and LST was increased in this study. The IS index illustrates the most optimal correlation for the urban LST (R
2 = 0.59). Furthermore, the TsHARP
IS-based method depicted a good correlation between the DLST and the ASTER LST product (RMSE = 1.5 °C, R
2 = 0.83) compared to the NDVI (RMSE = 4 °C, R
2 = 0.73). Consequently, it is found that the application of TsHARP
IS-based method to ASTER remote sensing data is a robust/low-cost approach for spatial downscaling of the LST over urban regions.
AB - Nowadays, acquiring high spatial and temporal land surface temperature (LST) is one of the significant factors in urban climate studies. This study aims to assess the sharpening thermal imagery (TsHARP) method, which is developed for determining the LST in urban regions. Whereas the original TsHARP method correlates the Normalized Difference Vegetation Index (NDVI) with the LST, the current study seeks to evaluate the performance of the TsHARP method by correlating between the LST and NDVI over urban areas. Additionally, it is intended to investigate the relationship between the impervious surfaces (IS) and LST. At this point, the Advanced Spaceborne Thermal Emission and Reflection Radiometer ASTER image of the year 2003 was used to retrieve the IS as well as the LST of the Kuala Lumpur city, Malaysia. To retrieve the main LST, IS and NDVI, ASTER Level1B data were used. On the other hand, ASTER land surface temperature products (AST08) was utilized to evaluate the downscaled LST (DLST) image. With selection of the ~1/4 of the pixels with lowest coefficient of variation (CV), the LST has more correlation with the IS in comparison with the NDVI, while the correlation between the IS and LST was increased in this study. The IS index illustrates the most optimal correlation for the urban LST (R
2 = 0.59). Furthermore, the TsHARP
IS-based method depicted a good correlation between the DLST and the ASTER LST product (RMSE = 1.5 °C, R
2 = 0.83) compared to the NDVI (RMSE = 4 °C, R
2 = 0.73). Consequently, it is found that the application of TsHARP
IS-based method to ASTER remote sensing data is a robust/low-cost approach for spatial downscaling of the LST over urban regions.
KW - ASTER
KW - Impervious surfaces (IS)
KW - Land surface temperature (LST)
KW - TsHARP
KW - Urban areas
UR - http://www.scopus.com/inward/record.url?scp=85136553102&partnerID=8YFLogxK
U2 - 10.1016/j.uclim.2022.101265
DO - 10.1016/j.uclim.2022.101265
M3 - Article
SN - 2212-0955
VL - 45
SP - 1
EP - 17
JO - Urban Climate
JF - Urban Climate
M1 - 101265
ER -