TY - JOUR
T1 - Investigation and Prediction of the Land Use/Land Cover (LU/LC) and Land Surface Temperature (LST) Changes for Mashhad City in Iran during 1990–2030
AU - Mansourmoghaddam, Mohammad
AU - Rousta, Iman
AU - Cabral, Pedro
AU - Ali, Ashehad A.
AU - Olafsson, Haraldur
AU - Zhang, Hao
AU - Krzyszczak, Jaromir
N1 - info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04152%2F2020/PT#
Mansourmoghaddam, M., Rousta, I., Cabral, P., Ali, A. A., Olafsson, H., Zhang, H., & Krzyszczak, J. (2023). Investigation and Prediction of the Land Use/Land Cover (LU/LC) and Land Surface Temperature (LST) Changes for Mashhad City in Iran during 1990–2030. Atmosphere, 14(4), 1-21. [741]. https://doi.org/10.3390/atmos14040741 --- Funding: This study was supported by the Shanghai Municipal Science and Technology Commission within the international cooperation framework of the Youth Scientists from the “One Atmosphere 2023, 14, 741 18 of 21 Belt and One Road” countries (2020–2023), and partially supported by the FCT (Fundação para a Ciência e a Tecnologia) under the project UIDB/04152/2020—Centro de Investigação em Gestão de Informação (MagIC).
PY - 2023/4/19
Y1 - 2023/4/19
N2 - Studies on how cities are affected by urban heat islands (UHI) are critical nowadays for a better understanding of the connected effects and for providing helpful insights for sustainable city development planning. In this study, Landsat-5 Thematic Mapper (TM), Landsat-7 Enhanced Thematic Mapper+ (ETM+), and Landsat-8 Operational Land Imager (OLI) images were used to assess the dynamics of the spatiotemporal pattern of land use/land cover (LU/LC) and land surface temperature (LST) in the metropolitan city of Mashhad, Iran in the period between 1990 and 2019. The Markov chain model (MCM) was used to predict LU/LC and LST for 2030. In the analyzed LU/LC maps, three LU/LC classes were distinguished, including built-up land (BUL), vegetated land (VL), and bare land (BL) using the maximum likelihood (ML) classification method. The collected data showed different variations in the geographical pattern of Mashhad LST during the research period that impacted the LST in this metropolis. The study evaluated the variations in LU/LC classes and evaluated their impact on the LST. The value of the LST was positively correlated with the occurrence of the built-up land (BUL), and with the bare land areas, while it was negatively correlated with the occurrence of the VL areas. The analysis of changes observed over three decades with 10-year intervals and the prediction of the LU/LC and LST for 2030 constitute an important contribution to the delineation of the dynamics of long LU/LC and LST records. These innovative results may have an important impact on policymaking fostering environmental sustainability, such as the control and management of urban expansion of Mashhad in connection with UHI.
AB - Studies on how cities are affected by urban heat islands (UHI) are critical nowadays for a better understanding of the connected effects and for providing helpful insights for sustainable city development planning. In this study, Landsat-5 Thematic Mapper (TM), Landsat-7 Enhanced Thematic Mapper+ (ETM+), and Landsat-8 Operational Land Imager (OLI) images were used to assess the dynamics of the spatiotemporal pattern of land use/land cover (LU/LC) and land surface temperature (LST) in the metropolitan city of Mashhad, Iran in the period between 1990 and 2019. The Markov chain model (MCM) was used to predict LU/LC and LST for 2030. In the analyzed LU/LC maps, three LU/LC classes were distinguished, including built-up land (BUL), vegetated land (VL), and bare land (BL) using the maximum likelihood (ML) classification method. The collected data showed different variations in the geographical pattern of Mashhad LST during the research period that impacted the LST in this metropolis. The study evaluated the variations in LU/LC classes and evaluated their impact on the LST. The value of the LST was positively correlated with the occurrence of the built-up land (BUL), and with the bare land areas, while it was negatively correlated with the occurrence of the VL areas. The analysis of changes observed over three decades with 10-year intervals and the prediction of the LU/LC and LST for 2030 constitute an important contribution to the delineation of the dynamics of long LU/LC and LST records. These innovative results may have an important impact on policymaking fostering environmental sustainability, such as the control and management of urban expansion of Mashhad in connection with UHI.
KW - Maximum Likelihood Classification
KW - Markov chain
KW - Land-cover change forecast
KW - land surface temperature change forecast
KW - population shift
KW - Mashhad City
UR - http://www.scopus.com/inward/record.url?scp=85156197254&partnerID=8YFLogxK
UR - https://www.webofscience.com/wos/woscc/full-record/WOS:000979469500001
U2 - 10.3390/atmos14040741
DO - 10.3390/atmos14040741
M3 - Article
SN - 2073-4433
VL - 14
SP - 1
EP - 21
JO - Atmosphere
JF - Atmosphere
IS - 4
M1 - 741
ER -