Evaluation Remote sensing of land use effects on land surface temperature gradient using Landsat images: Case study: Kharestan Watershed

Subject Areas : Environmental planning

Abbasali vali ¹ , abolfazl ranjbar ² , marzieh mokarram ³ , farideh taripanah ⁴

1 - Associate Professor at Desert Management Department, University of Kashan, Iran;
2 - Assoc. Prof. Desert Management Department, University of Kashan, Iran
3 - Assis. Prof. Range and Watershed Management Department, Darab Compass, Shiraz University, Iran.
4 - Ph.D. Student of Desertification Combating, Desert Control and Management Department, University of Kashan, Iran.

Received: 2019-05-24 Accepted : 2019-06-10 Published : 2019-05-22

Keywords: land use, Vegetation, Land surface temperature, remote sensing, Detection of changes,

Abstract :

Several factors affect the temperature gradient of the Land surface, one of the factors affecting human activities is land use changes that can lead to global temperature changes. Land surface temperature changes affect the natural climate of the region, so understanding its changes and balancing it is essential to understand the indirect effects of human intervention on ecosystems and their management. The aim of this study is to investigate land use, land surface temperature characteristics in each land use as well as correlation between land surface temperature variations and normalized difference index (NDVI). In this study, land use, land temperature and NDVI analysis was used from Landsat 5TM in 1990, 2010, ETM7 2000, and 8OLI for 2017. Land use was studied using supervised classification method. The results showed that the amount of land surface temperature in each land use was different and the maximom amount was found in the bare soil and in the built areas and the lowest in the garden. The difference in land surface temperature between built areas with vegetation in the years 1990, 2000, 2010, and 2017 was 3.58, 2.27, 3.20 and 2.12 ° C, respectively. Also, the difference in temperature between bare soil with vegetation cover in these four periods was 3/3, 0.8, 0.81 and 2.38 ° C respectively. In this study, the relationship between NDVI and surface temperature showed a negative correlation, so that areas with low NDVI had higher temperatures than those with high NDVI. The relationship between vegetation changes and surface temperature changes showed a significant correlation between these two parameters (R = 0.63). Therefore, it can be stated that land uses with more vegetation have lower temperatures than land uses with less cover.