Relative Surface Heat Capacity Mapping using the Day and Night Time Series of MODIS Images and Digital Elevation Models (Case study: Semnan Deserts, Iran)

Subject Areas : Geospatial systems development

Mohammad Azad ¹ , Mahdi Mokhtarzade ² , Alireza Safdarinezhad ³ , Alireza Siami ⁴

1 - MSc. Student of Photogrammetry, Department of Photogrammetry and Remote Sensing, Faculty of Surveying Engineering, K. N. Toosi University of Technology, Tehran, Iran
2 - Associate Professor, Department of Photogrammetry and Remote Sensing, Faculty of Surveying Engineering, K. N. Toosi University of Technology, Tehran, Iran
3 - Assistant Professor, Department of Geodesy and Surveying Engineering, Tafresh University, Tafresh, 39518-79611, Iran
4 - MSc.Soil Resource Management, Department of Soil Science, Faculty of Agriculture and Natural Resources, University of Islamic Azad Research Branch, Tehran, Iran

Received: 2022-08-15 Accepted : 2022-11-14 Published : 2022-11-14

Keywords: MODIS sensor, Land surface temperature, Digital Elevation Model, Keywords: Heat Capacity,

Abstract :

Heat capacity is a physical quantity of the surface that is directly related to the amount of heat energy required to change the surface temperature. Land surfaces with a high of thermal capacity are a sign of moderate climatic conditions and the presence of the low ones is known as a reason for the occurrence of desert climate conditions. When uniform heat energy absorption is occurred by different surfaces, their temperature changes can be inversely related to the heat capacity. However, due to obstacles and shadows, the sunlight as the most important factor in the reception of heat energy during the day does not receive uniformly to the surface of the earth. In this article, by adjusting the shadows effect the differences in sunlight energy received by different parts of land surfaces are modeled. Then, by calculating the day and night land surface temperatures a method has been proposed for estimation of relative heat capacity. In this method, the time series of MODIS images are used to reduce the destructive effects of atmospheric conditions in the estimation of land surface temperature. The percentage of shadow’s presence in each position is also estimated through the spatial analyses on digital elevation models. The proposed method has been calibrated through the ground truths identified with expert knowledge about the soil properties. The results demonstrate that the efficiency of the calibrated method reaches the overall accuracy of 93% in a relative assortment of land surfaces in terms of their heat capacities.