Identification of Geothermal Regions by Examining Vegetation Changes Under Stress By Using of ETM + Sensor and ASTER Sensor (Case Study, Khoy Township)

Thermal remote sensing, as a branch of remote sensing science plays an important role in environmental studies. Thermal sensing is one of the new and low cost methods against ground surveys in remote areas, which provides valuable information from the study area to researchers in the shortest time. It is possible to prepare a surface temperature map to identify areas prone to geothermal and plant stress by using an infrared thermal band. Which provides the basis for further exploratory studies. In this research, we used the ETM + and ASTER sensors to map the vegetation anomalies using the NDVI index of Khoy city. And plant seasonal variations were examined. Two datasets, one in early summer 2002 and the other in late summer and fall 2002, were derived from Landsat 7 data. By calculating the LST for the ETM + sensor, in this study, changes beyond the normal seasonal changes were considered as thermal anomalies. Also, by calculating the surface temperature by ASTER data, the surface manifestations of these anomalies under dense vegetation were revealed. MODIS sensor images were used to validate LST calculated by ASTER sensor and NDVI and ALI were calculated using it. The results of the present study showed that the identification of geothermal regions has a good spatial correlation with plant stress in Khoy city. ETM + and ASTER sensors, due to their high resolution in the infrared thermal band, 60 meters and 90 meters, respectively, are suitable sensors for calculating the surface temperature and detecting thermal anomalies. Therefore, the image difference method in this study was not a suitable method and did not show good results.