Quantifying the effect of surface parameters and climatic conditions on land surface temperature using reflective and thermal remote sensing data

Subject Areas : Geospatial systems development

Naeim Mijani ¹ , Saeid Hamzeh ² , Mohammad Karimi Firozjaei ³

1 - MSc. Student of Remote Sensing and GIS, Faculty of Geography, University of Tehran
2 - Assoc. Prof. Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran
3 - PhD Student of Remote Sensing and GIS, Faculty of Geography, University of Tehran

Received: 2017-01-07 Accepted : 2019-04-30 Published : 2019-04-21

Keywords: Normalized difference vegetation index (NDVI), Climate condition, remote sensing, Land surface temperature (LST), Kerman,

Abstract :

The land surface temperature (LST) plays a vital role in a wide range of scientific researches including climatology, hydrology, natural resources and etc. There are some determining factors which affect the land surface temperature, such as the kind of surface elements, topography and environmental conditions and also the amount of incoming radiation to the surface. The objective of this study is to investigate the effect of topographic parameters, climatic conditions and downward radiation on land surface temperature using remote sensing data. For this purpose, the Landsat 8 satellite image, ASTER digital elevation model, MODIS water vapor product (MOD07) on 24 July 2018, topography and climate map of Kerman province were used. To calculate the LST and downward shortwave and longwave radiation to surface the single channel and SEBAL energy balance algorithms were used, respectively. Finally, using statistical analysis the relationship between LST and independent variables, including elevation, slope, aspect, vegetation cover index and downward radiation to the surface were studied. The results of the study shown that the correlation coefficient between the LST and each of the independent parameters is more than 0.7. Also, the relationship between LST and topographic, normalized difference vegetation index (NDVI) and downward radiation parameters at the 95% level was significant. The results of the mean of LST values in climatic conditions, including extra-dry, dry, semi-dry, Mediterranean, semi-wet and wet indicate that climates classes with higher LST relative to climates classes with lower LST have means of elevation, NDVI lower and mean longwave downward radiation to surface higher.

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