2024 : 11 : 21
Mohammad Darand

Mohammad Darand

Academic rank: Professor
ORCID:
Education: PhD.
ScopusId: 26664517400
HIndex:
Faculty: Faculty of Natural Resources
Address: سنندج، دانشگاه کردستان، دانشکده منابع طبیعی، گروه آب و هواشناسی
Phone: 08736620551

Research

Title
Trend analysis of land surface temperature over Iran based on land cover and topography
Type
JournalPaper
Keywords
Land surface temperature , Trend analysis , Iran , Land cover , Topography
Year
2022
Journal International Journal of Environmental Science and Technology
DOI
Researchers Masoud Moradi ، Mohammad Darand

Abstract

The relationship between the features of the land surface and the atmosphere is well identified by its temperature. This parameter is a key tool in investigations of relevant energy equilibrium variations. The purpose of this research is to identify and analyze Land Surface Temperature (LST) variations over Iran using MODIS Aqua data. The modified non-parametric Mann–Kendall test is used for examination of trend significance, and Sen’s slope is used in the calculation of changes rate and direction. The results demonstrated that environmental factors including land cover and elevation have significant effects on LST trend. For inland waters and swamps, positive daytime trends have occurred during the warm months of the year, and negative nighttime trends have occurred during the cold months. The highest frequency of variation per decade corresponds to that between −5 and + 5 degrees Celsius per decade (°C/Decade). The mountainous regions have experienced severe positive daytime variations in the cold months and similar changes in the warm months. The findings also indicate that changes in land cover and use have resulted in LST variations. There have been greater daytime than nighttime such variations, and have occurred at far higher rates for four land covers: the bodies of water, cropland, urban areas, and barren land. The overall results of the research demonstrated that MODIS Aqua LST data are capable of accurately monitoring spatiotemporal variations over Iran.