Abstract—In this study, an application was carried out to determine the Volcanic Soils by using remote sensing. The study area was located on the Golcuk formation in Isparta-Turkey. The thermal bands of Landsat 7 image were used for processing. The implementation of the climate model that was based on the water index was used in ERDAS Imagine software together with pixel based image classification. Soil Moisture Index (SMI) was modeled by using the surface temperature (Ts) which was obtained from thermal bands and vegetation index (NDVI) derived from Landsat 7. Surface moisture values were grouped and classified by using scoring system. Thematic layers were compared together with the field studies. Consequently, different moisture levels for volcanic soils were indicator for determination and separation. Those thermal wavelengths are preferable bands for separation of volcanic soils using moisture and temperature models. Keywords—Landsat 7, soil moisture index, temperature models, volcanic soils. I. INTRODUCTION OIL moister is an significant characteristic as color, texture, structure, mineralogy, organic matter, free carbonates, and salinity in the study of soil description and determination of distribution [1]. These properties can be predicted by spectral reflections obtained from remote sensing data [2], used with multivariate calibrations [3]. All of these in addition to remote sensing methods facilitate thematically mapping soil properties by reducing the need for extensive time-consuming and costly field surveys. Soils moister content influences spectral signature of soils through the absorption processes in middle infrared (MIR) and thermal infrared region (TIR). Soil water exhibits absorption peaks at about 1450 nm, 1880 nm, and 2660 nm [4]. In recent years, satellite- based techniques with thermal infrared remote sensing methods, have been used in many studies for the determination of surface soil moisture by using different moisture index [5]. The most common remote sensing data used for this purpose are Landsat, ASTER, and MODIS images which have been used for retrieving the surface variables required as inputs for energy balance modelling [6]- [8]. A linear relationship between soil moisture and surface temperature [9] is at the basis of the studies. Similarly, SMI uses land surface temperature (LST) and vegetation density to L. Basayigit is with Süleyman Demirel University, Agriculture Faculty, Soil Science and Plant Nutrition Department, Isparta Turkey, (phone: +90- 246-2118589; fax: +90-246-2118696; e-mail: leventbasayigit@hotmail.com) M. Dedeoglu is with Selçuk University, Agriculture Faculty, Soil Science and Plant Nutrition Department, Konya Turkey. F. Özoğul is with Süleyman Demirel University, Graduate School of Natural and Applied Sciences, Isparta Turkey. determine soil moisture, thus different values have been obtained for different soils [10]. LST reflects the water effects of the soil properties, and the vegetation index shows the complex conditions of the underlying surface. Many studies applied these two variables to study the SMI calculated through different remotely sensed data sources [5], [11]. Although remote sensing and soil spectroscopy have been recognized as a potentially effective and cost-efficient technology, they are not yet routinely used in soil surveys [8]. Our purpose of this research is to develop a new approach for determination of volcanic soils using SMI map that produced Landsat 7 ETM+ image. For this purpose, volcanic and other geological properties of soils have been utilized. II. MATERIAL AND METHODS A. Study Area and Data The study area which is called Golcuk Formation was located in Isparta, Turkey, approximately 3450 hectares. Position of the area is upper left longitude 30° 27′ 27″ and latitude 37° 44′ 56″, lower right longitude 30° 31′ 47″and latitude 37° 42′ 2″ (Fig. 1), it includes different geological formations such as alluvion, limestone, volcanic tuff, and Golcuk Lake. The study was carried out on the LANDSAT-7 Enhanced TM data in 2011 August. The data include the spatial resolution of thermal band (1.040 – 1.250 µm) with 60 m also spatial resolution of visible (630 – 690 µm for Red) and NIR (770 – 900 µm) band with 30 m. B. SMI Calculation SMI (1) is based on empirical parameterization of the relationship between LST and normalized difference vegetation index (NDVI) and it is calculated using (1) [12]- [15]. SMI = (LSTmax – LST) / (LSTmax – LSTmin) (1) where LSTmax and LSTmin are the maximum and minimum surface temperature for a given Landsat 7 Thermal Band (Band 6), and LST is the LST (2), the surface temperature of a pixel calculated from using Landsat Product Equals [16]. LST = BT / 1 + w * (BT / p) * ln (e) (2) where, BT = At Satalite Temperature, w = wavelength of emitted radiance (λ → 11.45 µm), p = h * c / s (1.438 * 10 -2 mK) → p = 14380, c = light speed (c = 2.9979×10 8 m/s), h = Planck’ s Constant (6. 626 * 10 -34 Js), s = Boltzmann Constant Levent Basayigit, Mert Dedeoglu, Fadime Ozogul The Use of Thermal Infrared Wavelengths to Determine the Volcanic Soils S World Academy of Science, Engineering and Technology International Journal of Geological and Environmental Engineering Vol:11, No:9, 2017 837 International Scholarly and Scientific Research & Innovation 11(9) 2017 scholar.waset.org/1307-6892/10008090 International Science Index, Geological and Environmental Engineering Vol:11, No:9, 2017 waset.org/Publication/10008090