Estimate Land Surface Temperature in Relation to Land Use Types and Geological Formations Using Spectral Remote Sensing Data in Northeast Jordan

• 作者: Haya Abu-Mallouh Majed Ibrahim
• 来源期刊: 地质学期刊(英文)
• 学科: 地球科学
• 关键词: LAND Surface Temperature MODIS LAND Use Type GEOLOGICAL Formation Remote Sensing
• 年，卷（期）: 2018,（2）
• 页码范围: 174-185
• 页数: 12页
• 分类号: P4

摘要

Land Surface Temperature (LST) is one of the important indicators to understand the spatial changes and surface processes on the earth surface that leads to actual assessment of environmental quality from local to global scales. The relation between spatial analysis of the land surface temperature and existing land use/land cover changes is important to evaluate the climate processes. Monitoring of this relation in the arid and semi-arid regions is necessary to make an appropriate decision about Land surface temperature and environmental status. In this paper, generally the split-window algorithm is used to estimate LST from thermal bands of the Landsat Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS) using remote sensing and Geographic Information System (GIS) techniques as well as meteorological data through Moderate Resolution Imaging Spectroradiometer (MODIS). The results show the relationships between land use types and land surface temperature. MODIS data were analyzed. The relationship between MODIS and Landsat data temperature is moderate relation and the (R2 = 0.5109) according on 200 random points were selected. This research concludes that the maximum temperatures of the land use types in MODIS and Landsat data for the rock formation are 59°and 45°respectively, whereas the maximum temperatures of the geological formation in MODIS and Landsat data for the basalt are 59°and 45°respectively. In conclusion, the MODIS and Landsat OLI and TIRS Data have high ability to distinguish the land use types. The correlation coefficient of the relation between the surface temperature with rock was (R2 = 0.6197). Therefore, it is found that there is an ability to monitor the spatial and temporal changes for land surface temperature and thus it can be useful to environmental studies.