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The application potential of remotely sensed optical imagery is boosted through the increase in spatial resolution, and new analysis, interpretation, classification, and change detection methods are developed. Together with all the advantages, shadows are more present in such images, particularly in urban areas. This may lead to errors during data processing. The task of automatic shadow detection is still a current research topic. Since image acquisition is influenced by many factors such as sensor type, sun elevation and acquisition time, geographical coordinates of the scene, conditions and contents of the atmosphere, etc., the acquired imagery has highly varying intensity and spectral characteristics. The variance of these characteristics often leads to errors, using standard shadow detection methods. Moreover, for some scenes, these methods are inapplicable. In this paper, we present an alternative robust method for shadow detection. The method is based on the physical properties of a blackbody radiator. Instead of static methods, this method adaptively calculates the parameters for a particular scene and allows one to work with many different sensors and images obtained with different illumination conditions. Experimental assessment illustrates significant improvement for shadow detection on typical multispectral sensors in comparison to other shadow detection methods. Examples, as well as quantitative assessment of the results, are presented for Landsat-7 Enhanced Thematic Mapper Plus, IKONOS, World-View-2, and the German Aerospace Center (DLR) 3K Camera airborne system.

The in-¯ight absolute calibration of spaceborne instruments working in the solar re¯ective region ( 0´4± 2´5 mm) has often been performed with large uniform ground areas, such as White Sands, U.S.A., or La Crau, France. The method presented here describes an alternative for high spatial resolution sensors employing arti® cial small ground targets. The required target size is seven times the size of the sensor's spatial resolution, the ground projected instantaneous ® eld-of-view (GIFOV ), if the Gaussian full width 2s of the image point spread function (PSF), atmospheric blurring removed, is less or equal to 1´5 Ö GIFOV. For near-future multispectral instruments with a spatial resolution of 1 to 10 m the required ground reference areas with very homogeneous re¯ectance properties will be sized 7 m Ö 7 m to 70 m Ö 70 m, respectively. The proposed method can also be employed for panchromatic sensors. In-¯ight calibration methodsThe spectral and radiometric properties of optical space sensors are usually measured in the laboratory environment before launch. However, the radiometric sensitivity of sensors can change during the lifetime of a mission, requiring an update of the calibration (Singh et al. 1985, Slater et al. 1987. Several options for determining the relationship between the recorded digital number (DN ) and the at-sensor radiance for orbiting instruments are available: $ pointing the sensor at a known light source (Sun, moon) and dark space, where dark space is employed to obtain the digital number for zero radiance; $ use of an on-board solar re¯ectance panel (di user); $ ground re¯ectance measurements of homogeneous targets and collection of atmospheric data at the time of the satellite overpass. These data are used in combination with a radiative transfer model to calculate the radiance at the spaceborne instrument. This radiance corresponds to the average DN of the target.This last option will be discussed here. It has been employed for the Landsat TM and SPOT HRV instruments (Slater et al. 1987, Santer et al. 1992, Moran et al. 1995. The accuracy of the calibration coe cients obtained with this method typically is in the 5± 10 per cent range. It depends on the spatial uniformity of the ground re¯ectance targets and the accuracy of ground measurements, the accuracy of the atmospheric data, and the accuracy of the radiative transfer code.

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