Analisis Hubungan Variasi Land Surface Temperature Dengan Kelas Tutupan Lahan Menggunakan Data Citra Satelit Landsat (Studi Kasus : Kabupaten Pati)

Abstract

The continued development of remote sensing technology is characterized by the increasing by number of satellites used for purposes of study that encourages utilization in a variety of fields. NASA Landsat satellite in its development has resulted in several generations, including the most recent Landsat 7 and Landsat 8. Satellite Landsat 8 is a continuation of the Landsat 7 mission, characteristics of the both satellites are almost the same in terms of spatial resolution, spectral and temporal as well as the characteristics of the sensor. Sensors on the satellite is equipped with thermal infrared that can detect surface temperatures.This research conducted in Pati regency. The data used are Landsat 7 and Landsat 8. The purpose of this research was to determine correlation between the variations of land surface temperature with the land cover classes by utilizing remote sensing technology that the method is supervised classification and surface temperature using mono-window brightness temperature method. The results of the processing will be analyzing spatial with zonal statistics, where the output is a minimum value, maximum, average, standard deviation and range of the surface temperature on each unit generated land cover mapping. The results of that value be conducted a comparison between the standard deviation of the range, so the results of these comparisons can be used to determine variations in the surface temperature of the processed results of each land cover generated. The results showed that the surface temperature in the area of research for the month of May 2016 ranged between 29,02°C; in June 2016 ranged between 23,00°C and in July 2016 ranged from 20,92°C. While the correlation between land surface temperatures with land cover classes is performed at the highest temperature encountered on building area and the lowest temperature in the non-agricultural classes. For the lowest surface temperature variations found in waters class, this is indicated by the value of the average ratio between 2σ of the range is 17.16%. While variations in surface temperature is highest on Non-Agricultural class, it is based on the results of the average ratio of between 2σ of the range is 22.23%