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Poster Session P
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Elimination and simulation of Terrain Effects on Remote Sensing images using DTM
Weiqing Zhang,Runsheng Wang
Center for Remote Sensing in Geology
29 College Road, Beijing, 100083, China
Abstract
The paper presents an approach of using three parameters (slope, aspect and viewfield factor) and a shadow map derived from DTM to produce the apparent reflectance image from the satellite image at visible and reflecting-infrared spectrum, then reconstruct the simulated image at any given sunshine direction based on it. The results of comparative analyses reveal that the influence of incident angle, slope, viewfield factor on the satellite image is decreasing sequently. In this approach to produce the apparent reflectance image, only three suppositions are made in advance: 1. the atmosphere is homogeneous over the entire image. 2. the sunlight is parallel. 3. the intensity of scattered space light is same at all directions and in any places. The only limit to this approach is the data accuracy of DTM.
Introduction
Remotely sensed data, as well as many geodata, are obtained from space about the earth surface, therefore are influenced by the terrain undulation. The original satellite image at visible and reflecting-infrared spectrum contains two kinds of information: the terrain characteristics and the surface reflectance. The terrain effect on the image, for some applications such as target discrimination and classification, is a kind of noise and should be gotten rid of; while for others such as visual interpretation of geological structures, is some useful information which gives the interpreter the perspective view. images usually southeast-illuminated (in the northern hemisphere) make the northeast—southeast structure emphasized and the northwest—southeast structure depressed. It will be very useful for geological structural researchers if we can simulate images at different azimuthes and elevation angles of the sunlight to enhance different directions of structures.
Kiyonari Fukue (1981) introduced a function exp(-nx) in his attempt to remove the shadow on the Landsat image which would be discussed later. Li Xianhua (1986) selected the special pixels, such as the one without the illumination of sunlight and space light, to computer the parameters used to correct the terrain effect one remotely sensed images. As a result the results were influence heavily by the pixels selected or the human factor. Here we theoretically developed two formulations to calculate the apparent reflectance of pixels within and outside the shadow using parameters computed by statistical processing, with little human influence.
Factor Analysis
The radiance a pixels received can be divided into sunlight and space light. The intensity of the sunlight is much higher than the space light. The major terrain factors influencing satellite images are shadow, slope, aspect and viewfield factor, all of which can be derived from Digital Terrain Model (DTM). The shadow map depicts the pixels that the sunlight can not reach. It is obvious that in a satellite image the intensity values of the pixels in shadow which are only due to the space light are much lower than those out of shadow with contributions from both sunlight and space light, and those two pixel sets should be processed separately. The terrain slope determines the real area of a pixel surface, because the areas of the pixel projection on the horizontal plane are the same. The higher is the slope, the more is the real area, as a result, the higher is the pixel value on the image if the amount of radiance a unit receives is the same. The incident sunlight angle of a pixel is the angle between the pixel normal and the sunlight direction. The less is the incident angle, the more sunlight the pixel receives.
While the sunlight direction is the same over the entire image because the sunlight is considered to be parallel, the pixel normal is a function of the slope and aspect of the pixel. The incident angle is irrelevant to the space light. In opposite, the viewfield factor influences only the space light. The viewfield factor is defined as the ratio of the space light a actural pixel receives to that a pixel in horizontal plane receives supposing the intensity of scattered space light is same at all directions and in any spaces, the viewfield factor is the ratio of the solid angle at the pixel over that on the plane. Because the computation of the solid angle is rather complex, it is computed actually in simplication by the product of the included angles of the earth surface in south—north and east—west directions.
Based on the above analysis, an approach is designed to remove the terrain effects on the satellite image to produce the apparent reflectance image. In the inverse process, the terrain effects of different sunlight directions are added to the apparent reflectance image to simulate the real satellite image. The influence of the incident angle, slope and viewfield factor can be analysized individually when we add each of the parameters into the constant reflectance image which is artificially made to produce the simulated images and comparing these outputs.
The real ground objects are neither diffuse reflector nor mirror reflector. The reflectance varies with the observing direction. It can be expressed as: R = F * R . R. is the reflectance measured under certain standard conditions. Function F describes the reflecting property of the object which varies with different qualities, shapes, surface roughness etc. of the object. Kiyonari Fukue [1986] used exp(-nx) to approximate the function F. Where x is the included angle between the observing direction and the reflecting light and n is a parameter. For diffuse reflector, n – 0; for mirror reflector, n = ¥. It is a good approximation for a single object. But for different objects, n varies. It is not reasonable to assume that all the pixels on the satellite image have the same n value. Because the satellite image is recorded under certain sunlight and observation direction, we can only get the reflectance under that sunlight and observation direction from the image. Therefore it is unrealistic and senseless to separate
the function F and R. from reflectance R by setting the same reflectance property to all the pixels of the image. in the following discussion, all the reflectances refer are the ones under certain sunlight and observation direction, R.
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