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Desarrollo y Validación de Algoritmos de Tempera-tura de la Superficie Terrestre

ABSTRACT RESUMEN Se ha generado una base de radiosondeos at-mosféricos sin nubes y globales para simular medidas radiométricas de sensores en el infra-rrojo térmico a bordo de satélites. El objetivo es generar algoritmos split-window (SW) para la obtención de la temperatura de la superficie te-rrestre (LST) para los sensores a bordo de saté-lite Terra/MODIS y Envisat/ AATSR. Esta base contiene 382 radiosondeos tomados en estacio-nes meteorológicas terrestres con una distribu-ción uniforme en el contenido de vapor de agua hasta los 5,5 cm. Los cálculos de transferencia radiativa se han realizado utilizando el modelo MODTRAN 4. Para las simulaciones se han uti-lizado diferentes ángulos de observación, consi-derando las características de cada sensor. Las bandas 31 y 32 del sensor MODIS, y las bandas 11 y 12 del sensor AATSR, son válidas para un algoritmo de tipo SW. Los algoritmos son cua-dráticos y con una dependencia explicita con la emisividad de la superficie. Se ha realizado un análisis de sensibilidad para estimar así el error de los algoritmos. Éstos se han validado con me-didas en tierra de LST tomadas coincidente-mente con el paso de los sensores MODIS y AATSR, en una gran extensión de arrozales si-tuada cerca de la ciudad de Valencia. Finalmente comparamos los resultados de nuestros algorit-mos con los productos estándar de LST de ambos sensores en la misma zona. Se obtuvieron resultados similares en todos los algoritmos con un error de ±0,5 K. ABSTRACT A database of global, cloud-free, atmospheric radiosounding profiles was compiled with the aim of simulating radiometric measurements from satellite-borne sensors in the thermal infra-red. The objective of the simulation is to generate split-window (SW) algorithms for the retrieval of land surface temperature (LST) from Terra/MODIS and Envisat/AATSR data. The da-tabase contains 382 radiosonde profiles acquired over land, with nearly-uniform distribution of precipitable water between 0 and 5.5 cm. Radia-tive transfer calculations were performed with the MOD-TRAN 4 code. Different viewing an-gles were considered in the simulation, taking into account the features of each sensor. The MODIS bands 31 and 32 and the AATSR bands 11 and 12 are suitable to use in a SW algorithm. These algorithms are quadratic in the brightness temperature difference, and depend explicitly on the land surface emissivity. A sensitivity analysis of the algorithms was made to obtain an estima-tion of the algorithms error. Furthermore the al-gorithms developed from the simulation database were validated with actual ground measurements of LST collected, concurrently to MODIS and AATSR observations, in a large area of rice crops located close to the city of Valencia, Spain. Ope-rational LST algorithms of both sensors were also validated in order to compare with the algo-rithms generated. Similar results are obtained in all algorithms with an error around ±0.5 K.

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    ABSTRACT: Land surface temperature (LST) can be derived from thermal infrared remote sensing data provided that atmospheric and emissivity effects are corrected for. In this paper, two correction methods were evaluated using a database of ground LST measurements and concurrent Envisat/Advanced Along Track Scanning Radiometer (AATSR) data. They were the split-window (SW) method, which uses two channels at 11 and 12 mum, and the dual-angle (DA) method, using one single channel (11 mum) at two observation angles (close to nadir and around 55° forward). The ground LST measurements were performed in a large, flat, and thermally homogeneous area of rice fields during the summers of 2002-2005, when the crop showed full vegetation cover. A total of 23 concurrences of ground measurements and AATSR data were obtained. Results showed that the SW algorithms worked satisfactorily provided that the characteristics of the area are correctly prescribed, either through the classification of the land cover type and vegetation cover fraction or with the surface emissivity. In this case the AATSR-derived LSTs agreed with the ground LSTs within +/-1.0°C for all the data of the comparison, with negligible average bias and a standard deviation of 0.5°C. The DA algorithms were less accurate than the SW algorithms for the data used in this study, yielding standard deviations of 1.0°C.
    Journal of Geophysical Research 01/2006; 111. · 3.17 Impact Factor
  • 07/1994; 370(6484):24-24.
  • A split-window algorithm for land surface temperature from advanced very high resolution radiometer data: Validation and algorithm comparison Ground measurements for the vali-dation of land surface temperatures derived from AATSR and MODIS data, Remote Sen-sing of Environment. C Y Coll, V Coll Caselles, C Caselles, V Galve, J M Valor, E Niclòs, R Sánchez . 16697-16713.

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Jun 10, 2014