An enhanced vegetation cover method for automatic generation of land surface emissivity maps

Automatic Generation of Land Surface Emissivity Maps

“…Their bias, which can be introduced if the approaches of the model are not fulfilled exactly. For that reason, an enhanced mathematically simple method (Caselles et al, 2009) was defined, without important bias, to obtain the surface emissivity from satellite images, inspired by the results of Valor & Caselles (1996), who purposed a relation between thermal emissivity and the Normalized Difference Vegetation Index (NDVI). The general philosophy of this new method is similar to some extent to the algorithm for LSE estimation used by the LST product of Terra-MODIS (Snyder et al 1998), and for LSE estimations in Meteosat-SEVIRI (Peres & DaCamara 2005;Trigo et al 2008) 2.1 Enhanced land surface emissivity model As we have already mentioned, to produce the emissivity maps, we used an improved geometric model based on the one described in Valor & Caselles (1996).…”

“…The validation of the whole system was carried out by comparing the data of the generated emissivity maps (as the one in figure 6) with the values obtained in previous campaigns (Coll et al 2005) carried out in the area of rice fields of Valencia, Spain (Caselles et al 2009). In order to compare them, we took all the measures data and the corresponding (by geographical coordinates) emissivity pixels and calculated the mean and the range of error for all, in each channel, as shown in Table 3.…”

“…In this chapter, this new method is presented, with its algorithm, and it is applied to several different types of vegetation in AATSR images of Europe, making all the calculations automatically with the developed software. Eventually, an on field validation of the method was carried out by comparing the data of the generated emissivity maps (as the one in figure 6) with the values obtained in previous campaigns (Coll et al 2005) carried out in the area of rice fields of Valencia, Spain (Caselles et al, 2009). An error of less than ±0.01 in the land surface emissivity assessment was successfully obtained.…”

“…The most innovative part of our method is that we provide it with the resources and the capability to calculate the most accurate coefficients according to the specific characteristics of each area (vegetation cover fraction, vegetation type, season, etc.). This allows the method to be applied to generate large-scale maps of this magnitude (Caselles et al, 2009). On the other hand, the current procedure (global, fully operational and supported by ESA) for obtaining the emissivity from an AATSR pixel (Noyes et al 2007) causes systematic errors when calculating the temperature of 2 to 5 K (Coll et al 2005), showing that the current classification and the vegetation cover maps made with a resolution of 0.5º x 0.5º could be highly improved and provided with the same spatial resolution of the AATSR images (1km x 1km).…”