Air temperature can be estimated from remote sensing by combining information in thermal infrared and optical wavelengths. The empirical TVX algorithm is based on an estimated linear relationship between observed Land Surface Temperature (LST) and a Spectral Vegetation Index (NDVI). Air temperature is assumed to be equal to the LST corresponding to the effective full vegetation cover, and is found by extrapolating the line to a maximum value of NDVI max. The algorithm has been tested and reported in the literature previously. However, the effect of vegetation types and climates and the potential variation in NDVI of the effective full cover has not been subject for investigation. The present study proposes a novel methodology to estimate NDVI max that uses observed air temperature to calibrate the NDVI max for each vegetation type. To assess the validity of this methodology, we have compared the accuracy of estimates using the new NDVI max and the previous NDVI max that have been proposed in literature with MSG-SEVIRI images in Spain during the year 2005. In addition, a spatio-temporal assessment of residuals has been performed to evaluate the accuracy of retrievals in terms of daily and seasonal variation, land cover, landscape heterogeneity and topography. Results showed that the new calibrated NDVI max perform well, with a Mean Absolute Error ranging between 2.8°C and 4°C. In addition, vegetation-specific NDVI max improve the accuracy compared with a unique NDVI max.
- Programområde 2: Vandressourcer