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Emissivity Determination for Land Surface Temperature estimation of Iran using AVHRR Thermal Infrared Data
2. Data Description AVHRR images of NOAA-14 of Iran that cover approximately 40.16 to 24.80 latitudes and 43.41 to 63.89 longitudes have been used in this study (Table 1). The daily temperature at 5 cm subsurface measured at ground meteorological stations, by Islamic Republic of Iran Meteorological Organization (IRIMO) corresponding to images have been used as reference data. A plot of distribution of the stations is shown in Figure 1. The images were geometrically corrected using ground control points. Then they were radiometrically enhanced using histogram modifications. Since the time of ground data did not match exactly with the time of images, they have been made simultaneous by linear interpolating.
 Figure 1: Distribution of meteorological stations 3. Emissivity determination Lack of knowledge of emissivity introduces an LST error to temperature maps. Most methods for LST estimation assume the emissivity is known and has a constant value. But actually, emissivity in most cases is dynamic and has to be determined in the time of LST calculations. Land Surface Emissivity (LSE) affects satellite measurements in three ways (Prata, 1993):
 Figure 2: Geological map of Iran In general, the effective emissivity of a pixel should be estimated by summing up the contributions from its surface type. Van de Griend and Owe (1993) found a high correlation between measured e and ndvi. The following equation describes the relation between measured e and ndvi: e = a+b*ln (ndvi) (3) where a=1.0094 and b=0.047 were derived from regression analysis for ndvi values from 0.2 to 0.7. Therefore using AVHRR data, for vegetation cover areas in Iran, a vegetation map has been constructed from ndvi values first and then emissivity values are calculated for those pixels containing ndvi values greater than 0.2 and smaller than 0.7. The emissivity values extracted for these areas are around 0.93 and 0.99 respectively. In order to determine emissivity values for non-vegetated areas, geological maps have been used and five types of land surface have been identified. They are Ultra Basic, Gabbro and Basic Igneous, Diorite and Acid Igneous, Dolomite and Lime, and Sand rock and Conglomerate. The emissivity values for these land types are around 0.856, 0.934, 0.877, 0.958 and 0.912 respectively. The emissivity values have been extracted from tables presented in Nerry et al. (1990), and Wan and Dozier (1989). As an example, a sample of relevant emissivities based on geological map is shown in Figure 3. For each class (surface type) shown in the fingure, an emissivity value has been related from tables presented in other studies.  Figure 3: Emissivity map has been extracted from geological map There are other land cover types that were not possible to be identified using ndvi and geological maps. These include areas having ndvi values greater than 0.7, seasonal lakes, bedrocks, sandy bare soils and loamy bare soils. In order to find these classes, land cover classification was performed on AVHRR data. The emissivity values for ndvi (greater than 0.7), seasonal lakes, bed rocks, sandy bare soils and loamy bare soils are 0.989, 0.97, 0.959, 0.93 and 0.914 respectively. The emissivity values have been extracted from tables presented in Label and Stoll (1991), and Humes et al. (1994) .The extend of each one of the five classes have not been considered constant, as they are extracted dynamically, and the emissivity values are assigned for each type when the LST map is being produced. Therefore, emissivity values of around 40% of land have been determined dynamically from ndvi and classification maps. |
