Articles
Publication Date: 2024
Atmosfera (01876236)38pp. 409-419
Heat island characteristics depend on the background climate of the site where the city is located. Therefore, an index was defined for the Isfahan metropolitan area to quantify the surface urban heat island intensity. This new index is based on the representative pixels of urban and non-urban areas. For this purpose, MODIS land cover type product (MCD12Q1) data were used to distinguish between urban and non-urban areas. Also, data from the MODIS/Terra land surface temperature product (MOD11A1) from 2000 to 2018 were utilized for daytime and nighttime to study the surface heat island intensity. Then, the representative pixels of urban and non-urban areas were identified using the spatial correlation method, and the heat island index was calculated for the metropolitan area of Isfahan. The study showed that the frequency distribution of the nighttime heat island index follows a normal distribution and is often 3.5 to 4ºK above the temperature of the surrounding areas of the city. The 365-day floating mean of the surface urban heat island reveals that this index has increased in recent years. The research of temporal behavior showed that the intensity of the surface urban heat island reaches its maximum in January and becomes weaker in summer, while the survey of spatial behavior showed that the core of the surface urban heat island extends towards downtown areas, where the oldest part of the city is located. © 2024 Universidad Nacional Autónoma de México, Instituto de Ciencias de la Atmósfera y Cambio Climático.
Publication Date: 2023
Journal of the Indian Society of Remote Sensing (09743006)51(6)pp. 1297-1307
Environmental changes such as ablation of ice and snow, drying of lakes, deforestation, desertification and urbanization may affect the thermal properties of the land surface, and hence, it affects the land surface temperature (LST). MODIS LST data, make it possible to investigate the variations in the frequency distribution of LST. In this research, 16 years of MODIS\Aqua LST data (2002–2022) have been analyzed using principal component analysis. This study shows that the frequency distribution of LST in Iran depends to a great extent on altitude and then depends on the terrain surface features. Lakes, river systems, sand dunes, deserts, woodlands, forests and metropolitan areas are among the terrain surface features that affect the frequency distribution of LST. Hence, analysis of the frequency distribution of LST may be considered as a tool for identifying the geographical boundaries of these terrain features. Additionally, it could be a robust tool for tracking the changes in the boundaries of such geographical phenomena over time. Frequency analysis of LST in Iran reveals many natural and anthropogenic environmental changes. For example, the analysis shows that the drying out of Zayanderud downstream and Urmia Lake is related to man-made changes in the upstream. The comparison of the interdecadal of LST shows that the frequency of LST has increased in some temperature categories and decreased in some other temperature categories. In general, the frequency shift of LST both during the day and at night has been toward higher temperatures. © 2023, Indian Society of Remote Sensing.
