An atmospheric correction method for the automatic retrieval of surface reflectances from TM images

• Published in: International journal of remote sensing 1994-07, Vol.15 (10), p.2065-2086
• Main Authors: GILABERT, M. A., CONESE, C., MASELLI, F.
• Format: Article
• Language: English
• Subjects: Areal geology. Maps; Earth sciences; Earth, ocean, space; Exact sciences and technology; External geophysics; Geologic maps, cartography; Geophysics. Techniques, methods, instrumentation and models
• ISSN: 0143-1161; 1366-5901
• DOI: 10.1080/01431169408954228

Most of the atmospheric correction methods proposed in the literature are not easily applicable in reaJ cases. The most sophisticated models frequently require inputs which are not commonly available, whilst traditional simple dark object subtraction techniques do not generally give real reflectance values. In the present work an atmospheric correction method applicable to Landsat-TM data is described, which requires only inputs that are commonly available and the presence in the imaged scenes of some dark surfaces in TM bands 1 (blue) and 3 (red). The method consists of an inversion algorithm based on a simplified radiative transfer model in which the characteristics of atmospheric aerosols are estimated by the use of the path radiance in two TM bands rather than a priori assumed. On the basis of this information, which is crucial for determining the atmospheric properties, the retrieval of real reflectances from TM images is possible. The method can be applied to all TM scenes in which some dark points can be realistically supposed to be present, which is particularly advantageous in retrospective studies. Several TM scenes taken from different landscapes and in different seasons were corrected using the model. The reflectance values found were tested against ground measurements and compared with data from the literature. The results show a substantial improvement in the accuracy of the reflectance estimates with respect to estimates without atmospheric correction. Given some care in the identification of dark values, the relative error in actual reflectance retrieval is always rather low (≅10-20 per cent); this error can be considered acceptable for most practical applications.