Showing 6 results for Land Surface Temperature
Chenoor Mohammadi, Manouchehr Farajzadeh, Yousef Ghavdel Rahimi, Abbas Ali Aliakbar Bidokhti,
Volume 18, Issue 48 (3-2018)
Abstract
This study is aimed at estimating monthly mean air temperature (Ta) using the MODIS Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), latitude, altitude, slope gradient and land use data during 2001-2015. The results showed that despite some spatial similarities between annual spatial patterns of Ta and LST, their variations are significantly different, so that the Ta variation coefficient is four times the one of the LST. Our analysis indicated that while in winter latitude is the key factor in explaining the distribution of the differences LST-Ta, in other seasons the role of slope and vegetation become more prominent. After obtaining the spatial patterns of LST and Ta, we estimated Ta using regression models in spatial resolution of 0.125˚. The lowest estimation error was found in the months of November and December with a high explanatory coefficient (R2) of 70% and a standard error of 1 ° C. On the other hand, the maximum error was obtained from May to August with R2 between 59 to 63% and a standard error of 1.6 ° C which is significant at the 0.05 level. In addition, result of evaluation of individual months showed that estimation of Ta is more accurate at the cold months of the year (November, December, January, February, and March). With considering different land uses, the highest R2 was related to waters and urban areas (96 to 99%) in warm months, and the lowest R2 was for mixed forest and grassland (between 15 and 36%) in cold months.
Dr Sayyad Asghari, Hadi Emami,
Volume 19, Issue 53 (6-2019)
Abstract
Earth surface temperature is an important indicator in the study of energy equilibrium models at the ground level on a regional and global scale. Due to the limitation of meteorological stations, remote sensing can be an appropriate alternative to the Earth's surface temperature. The main objective of this study is to monitor the surface temperature and its relationship with land use, which is monitored using satellite imagery. For this purpose, the images were first obtained and the necessary pre-processing was applied to each one. Then it was compared to modeling and classification of images. Firstly, in order to investigate the changes in user-orientation, a user-defined classification map for each object was extracted using the object-oriented method. Then, to investigate the land use change, a map of user-landing changes map was extracted in an 18-year time period (2000-2017). Finally, in order to monitor the surface temperature, the surface temperature map of Ardebil was extracted. The results showed that there is a strong relationship between land use and surface temperature. As a user, urban users have a temperature of about 41 ° C (2017), which is also due to heat-absorbing urban temperatures. This is despite the fact that the use of hydrocarbons is due to a lower heat absorption of 34 ° C (2017). This shows the role of different uses in determining surface temperatures. Also, the relationship between surface temperature and vegetation cover was investigated in this study. The results showed that areas such as soil and urban areas with a lower coverage than areas such as agriculture and pasture, have a higher temperature. Because the coating is always an obstacle to the entry of heat, it has an inverse relationship with superficial heat.
Musa Abedin, Ehsan Ghale, Nazfar Aghazadeh, Maryam Mohamadzadeh Sheshegaran,
Volume 22, Issue 67 (12-2022)
Abstract
Studies have shown that the role of thermal temperature measurement in studying and estimating surface temperature is very important. Earth surface temperature is an important indicator in the study of equilibrium energy models on the ground at the regional and global scale. Due to the limitation of meteorological stations, remote sensing can be a good alternative to earth surface temperature estimation. The main objective of this study is to monitor the surface temperature of the Earth using satellite imagery and a relationship that can have a surface temperature with land use. For this purpose, the relevant images were first obtained and the necessary pre-processes were applied to each one. Then it was compared to modeling and classification of images. Firstly, in order to study land use change, land use classification map was extracted for each two years using a controlled classification method. Then, to study the land use change, the land use change map was extracted for a period of 28 years (1987-2015). Became finally, in order to monitor the surface temperature, the surface temperature map of Meshginshahr was extracted. The results showed that there is a strong relationship between land use and surface temperature. High-vegetation areas and low-temperature blue areas. Also, rainfed farming has the highest average temperature relative to adjacent areas, which indicates the dryness of agricultural products in the Meshginshahr city.
Mohsen Pourkhosravani, Ali Mehrabi, Behnaz Shaikhshariati,
Volume 23, Issue 68 (3-2023)
Abstract
Solar energy is receiving lots of attention because it is one of the cleanest, cheapest and most available energies in the world.but solar radiation in different parts is changing, thus, identifying appropriate locations for implementation of solar energy is necessary. Accordingly the aim of this study was to analyze the potential of solar radiation and land surface temperature on the Loot desert using remote sensing and geo statistical technique. Results show that Earth's surface temperature fluctuates between 29 and 79 degrees Celsius in the Lut Plain. So that Earth's temperature increases to the east and north-east of the region. Also, the radiation energy reaching the surface in the Lut plain varies from 232.77 to 237.61w/m² in different parts of the Lut plain. So that the maximum amount of energy is related to the south of the plain, and the further we move to the north reduces the amount of energy.
Mohammad Kazemi Garajeh, Behnam Salmani, Mohammad Hossein Rezaei Moghaddam,
Volume 24, Issue 74 (9-2024)
Abstract
The purpose of the present study is to assess the land surface temperature in relation to landuse for the city of Tabriz using remote sensing technology and GIS. Landsat 8 satellite image was used to map the land surface temperature for the study area. Atmospheric correction was applied to the desired image using the FLAASH method and the land surface temperature was estimated using the split-window algorithm for the study area with an accuracy of 1.51 degrees. Landuse map of Tabriz city in 6 classes was obtained using the object-based approach in eCognition software with an accuracy of 90/03. The results of studying the relationship between land surface temperature and landuse indicate that agricultural lands with a temperature of 18.22 °C have the highest land surface temperature. Also, water areas (rivers) have the lowest (10.30 °C) land surface temperature, because of their radiant power close to one. The research results also indicate that the split-window algorithm provides reliable results for land surface temperature estimation that can be used in environmental studies and earth sciences.
Hamed Heidari, Darush Yarahmadi, Hamid Mirhashemi,
Volume 24, Issue 75 (12-2024)
Abstract
Human interventions in natural areas as a change in land use have led to a domino effect of anomalies and then environmental hazards. These extensive and cumulative changes in land cover and land use have manifested themselves in the form of anomalies such as the formation of severe runoff, soil erosion, the spread of desertification, and salinization of the soil. The main purpose of this study is to reveal the temperature inductions of the land cover structure of Lorestan province and to analyze the effect of land use changes on the temperature structure of the province. In this regard, the data of land cover classes of MCD12Q2 composite product and ground temperature of MOD11A2 product of MODIS sensor were used. Also, in order to detect the temperature inductions of each land cover during the hot and cold seasons, cross-analysis matrix (CTM) technique was used. The results showed that in general in Lorestan province 5 cover classes including: forest lands, pastures, agricultural lands, constructed lands and barren lands could be detected. The results of cross-matrix analysis showed that in hot and cold seasons, forest cover (IGBP code 5) with a temperature of 48 ° C and urban and residential land cover (IGBP code 13) with a temperature of 16 ° C as the hottest land use, respectively. They count. In addition, it was observed that the thermal inductions of land cover in the warm season are minimized and there is no significant difference between the temperature structure of land cover classes; But in the cold season, the thermal impulses of land cover are more pronounced. The results of analysis of variance test showed that in the cold period of the year, unlike the warm period of the year, different land cover classes; Significantly (Sig = 0.026) has created different thermal impressions in the province. Scheffe's post hoc analysis indicated that this was the difference between rangeland cover classes and billet up cover.
