Evaluation of split‐window and dual‐angle correction methods for land surface temperature retrieval from Envisat/Advanced Along Track Scanning Radiometer (AATSR) data

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 μm, and the dual‐angle (DA) method, using one single channel (11 μm) 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.