Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/38964
Title: Quantitative analysis of shadow effects in high-resolution images of urban areas
Authors: Zhan, Q
Shi, WZ 
Xiao, Y
Keywords: Shadow
Object
Extraction
High resolution
Classification
Land cover
LIDAR
Issue Date: 2005
Source: Proceedings of The 3nd International Symposium on Remote Sensing and Data Fusion Over Urban Areas, Tempe, Arizona, USA, 14-16 March 2005 How to cite?
Abstract: Shadow effects have drawn much attention by researchers with increasing use of high-resolution remote sensing images of urban areas. For correction or compensation to pixels that falling in shadow areas due to the existence of vertically standing objects such as buildings and trees, quantitative analysis of shadow effects is essential. In this paper, we proposed an object-based approach for predicting, identifying shadow areas and their corresponding surrounding areas based on airborne laser scanner (ALS) data. Quantitative analysis of shadow effects is followed based on high-resolution multi-spectral (MS) images. In the case study, we use 4 m-resolution multi-spectral IKONOS image and 1 m-resolution digital surface model (DSM), which is derived from airborne laser scanning data. We predict shadow areas of a multi-spectral image by using the hillshade algorithm based on meta data of the image (sun angle azimuth and sun angle elevation) and the DSM data of the same area. Building relief displacement caused by slightly oblique viewing in imaging is derived too, based on the DSM, nominal collection azimuth and nominal collection elevation to avoid mixture of predicted shadow areas and displaced areas of buildings. An object-based approach has been applied to identify shadow areas as objects instead of pixels so that adjacency relationships with surrounding areas can be derived. The differences of spectral values between shadow areas and their surrounding areas are quantitatively measured and compared. Per-object comparison between shadow areas and their corresponding surroundings is considered much more robust as compared with per-pixel approach. A shadow correction model is proposed that is based on quantitative comparison of different sites with different configurations. The experimental results show that local setting and configuration have to play an important role in shadow correction due to complexity of shadow effects. The detailed descriptions of methods, experimental results are presented in this paper, as well as the proposed shadow correction model.
URI: http://hdl.handle.net/10397/38964
Appears in Collections:Conference Paper

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