Seasonal Flooding Impact on Land Surface Temperature(LST) in Response to Vegetation Index Using Spectral Radiance Model in Kirkuk, Iraq

Abstract

Change detection of land use is essential in management and planning decisions. Land Surface Temperature (LST) has a significant importance in many geoscience aspects, such as heat transportation between land and atmosphere, state of corps, heat flux, greenhouse effect both locally and regionally, surface moisture and surface energy budget estimation, the monitoring of urban heat island, evapotranspiration and environmental biogeochemistry process simulation. A geographic information system was efficiently utilized to observe the changes in land use different categories and to map annual and seasonal LST variations. In this study, Land sat 5 and 8 images for the years 2010, 2017 and 2019 were used to study the flooding imact on the LST. The Mono-Window algorithm and sepectral rediance model on Landsat-5 TM and OLI were used to estimate LST. Taking 2010 as a reference, an empirical study shows that the No-vegetation category percentage was 9.28 % and 11.03% in the 2017 and 2019 summer seasons, respectively, while it was -1.48% and -0.46% in winter. Vegetation change was -60.9% and -50.04% in the 2017 and 2019 summer seasons, respectively, while it was 28.28% and -6.11% in winter. Water area change was -65.8% and 84.1% in the 2017 and 2019 summer seasons, respectively, while it was -38.5% and 59.89% in winter. The results indicate that the water area had greatly decreased during 2017 which led to increase the LST and the floods in 2019 led to decrease the LST by 5-8 degrees. The temperature trend analysis reveals a definite negative association between LST and flooded area, representing this study’s significant finding.