Analysis of spatial variation of land surface temperature over Zayanderoud River Basin based on MODIS sensor

Document Type : Full length article

Authors

1 Associate Professor, Geography Department, Payame Noor University, Tehran, Iran

2 Ph.D. Candidate in Climatology, Isfahan University, Iran

Abstract

Introduction
Soil temperature and its changes both in space and time is one of the most important factors that not only affect matter and energy transfer in soil but also influence the direction and amount of all physical processes in soil. Soil temperature depends on several factors including topography, sun radiation, air temperature, amount of soil moisture, the thermal properties such as heat capacity, coefficient of thermal conduction and specific heat. By the advent of satellite measurements in the last decades, there have been some studies focusing on the use and validation of remote sensing measurement of land surface temperature data mainly MODIS products. MODIS land surface data have been validated over different land types like lake (Want et al., 2002; Hook et al., 2004; Wan, 2008) and rice (Want et al., 2004; Galve et al., 2007).
 
Materials and Methods
In this research, the land surface temperature data of MODIS Terra in the spatial resolution of 1×1 km was exploited from NASA web site. These kinds of data are available in sinusoidal projection system. To investigate the role of elevation on land surface temperature, the digital elevation model (Dem) of the region was also obtained from NASA web site. Terra data are available from the year 2000 to 2015. These data are available in hdf format. As the first step only the pixels that felled into the Zayanderoud River Basin were selected from the data. This extraction was done using the inpolygon function in Matlab. By applying this function in Matlab there were exactly 48347 pixels that were the corner stone of our judgment about land surface temperature. In the second step, the daily matrix of temperature was constructed for each calendar day and based on the daily time series of the seasonal data were based on the daily data. Then, we calculated the rate of trend over each of the pixels for each season by applying regression equation on each of the 48347 pixels.
Results and Discussion
Analysis of trend in land surface temperature for each of the seasons indicated that there has been trend whether positive or negative in each of the seasons. The examination of trend for the season of spring showed that most of the territories of the Basin have experienced a negative trend but in central parts of the Basin a very marked positive trend dominates this region. The investigations for the summer season indicated that in many parts of the Basin negative trend has occurred but in the central parts of the Basin a distinguished positive trend can be seen. The analysis for the fall season showed that in this time many parts of the Basin like the other seasons have had a downward trend in the land surface temperature. But similar to the other seasons, central parts of the Basin have experienced a positive trend. The analysis for the winter season showed that in this period the areas that have had negative trend are less than the areas that have had positive trend in extent. The surprising note about this season is that there is a positive and direct relation between the rate of trend and elevation. Greater is the elevations, the greater the rate of trend. This means that in this season the highlands of the western parts of the Basin that are basically regarded as the valuable source for keeping snow covers and snow glaciers can’t have snow covers like before, due to the dominating positive trend occurring in these regions.
 
Conclusion
In this study, the daily time series of MODIS Terra was applied to explore the spatial trend of land surface temperature over Zayanderoud River Basin. The smallest resolution of 1×1 km of these data was used to get a better picture of the trend. As the first step, only the pixels that fell into the natural border of the Basin were extracted by using Matlab functions. In the next step, the daily values of land surface temperature were aggregated to monthly and seasonal time scales. The analysis of the trend for each of the seasons indicated that in all of the seasons positive and negative trends have occurred but in general negative trend has had a greater domination. In the spring season only central parts of the basin has represented a positive trend but in the other parts decreasing trend prevailed. In the summer and fall like spring only the central parts of the Basin have had a positive trend. But in the winter the highland of western parts of the Basin has had a very marked positive trend that can be hazardous for this region due to this fact that these mountainous regions of the Basin is regarded as the source of snow cover of the Basin. 

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