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Remote Sens. 2013, 5(9), 4450-4469; doi:10.3390/rs5094450

Evaluating the Effects of Shadow Detection on QuickBird Image Classification and Spectroradiometric Restoration

1
Department of Geography, California State University, Fullerton, 800 North State College Boulevard, Fullerton, CA 92831, USA
2
Department of Forest Resources, University of Minnesota, 1530 Cleveland Avenue North, Saint Paul, MN 55108, USA
*
Author to whom correspondence should be addressed.
Received: 24 July 2013 / Revised: 6 September 2013 / Accepted: 6 September 2013 / Published: 11 September 2013
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Abstract

Shadows in high resolution imagery create significant problems for urban land cover classification and environmental application. We first investigated whether shadows were intrinsically different and hypothetically possible to separate from each other with ground spectral measurements. Both pixel-based and object-oriented methods were used to evaluate the effects of shadow detection on QuickBird image classification and spectroradiometric restoration. In each method, shadows were detected and separated either with or without histogram thresholding, and subsequently corrected with a k-nearest neighbor algorithm and a linear correlation correction. The results showed that shadows had distinct spectroradiometric characteristics, thus, could be detected with an optimal brightness threshold and further differentiated with a scene-based near infrared ratio. The pixel-based methods generally recognized more shadow areas and with statistically higher accuracy than the object-oriented methods. The effects of the prior shadow thresholding were not statistically significant. The accuracy of the final land cover classification, after accounting for the shadow detection and separation, was significantly higher for the pixel-based methods than for the object-oriented methods, although both achieved similar accuracy for the non-shadow classes. Both radiometric restoration algorithms significantly reduced shadow areas in the original satellite images. View Full-Text
Keywords: land use and land cover; pixel-based; object-oriented; high resolution; shadows land use and land cover; pixel-based; object-oriented; high resolution; shadows
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Wu, J.; Bauer, M.E. Evaluating the Effects of Shadow Detection on QuickBird Image Classification and Spectroradiometric Restoration. Remote Sens. 2013, 5, 4450-4469.

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