Monitoring of the Night Time land Surface Temperature in Iran Based on Output of the MODIS

The estimation of land surface temperature (LST) is useful for a wide range of applications such as agriculture, urban heat island (UHI), Energy Management, climate related extreme and climate change studies. The MODIS LST products are created as a sequence of products beginning with a swath (scene) and progressing, through spatial and temporal transformations, to daily, eight-day and monthly global gridded products. The purpose of this study is to analyze the output data of MODIS in order to manage the night time temperature of both night and day in the geographical area of Iran. For this purpose, the MODIS data on land surface temperature which were generated using the day-night algorithm, were extracted for the 2001- 2015 period based on the output of the product called MOD11C3 (V5). Then a matrix with the dimensions of 62258 × 4855 was formed. 62,258 in the array of cells with a spatial resolution of 5 km and 4855 representative designated days, which in the next step were reduced to 62 258 × 12 arrays. 12 being the representative of the months of the year. The final analysis of surface temperatures was evaluated using kriging. The results show that the coldest overnight temperatures of land surface happen in December through February, reaching to -20 degrees Celsius. Also regarding geographical locations, the pattern matches the ripples, especially the western half, North and North-West and North-Khorasan. September is the transition period from warm to cold nocturnal land surface temperature, and March is the transition period from cold to warm temperature. A focus of warm temperature of land surface could be observed in different months of the year. These warm temperatures are dominant in warm areas from April through September. The variety of nocturnal land surface temperature in Iran is high. Heights and ripples are significant factors in determining the nocturnal land surface temperature in different areas of Iran.