Journal article
Shadow detection and building-height estimation using IKONOS data
International Journal of Remote Sensing, Vol.32(22), pp.6929-6944
2011
Abstract
The spectral confusion between shadow and water (or other dark surfaces) often results in suboptimal urban classification performances, especially from high-resolution satellite imagery (e.g. IKONOS). A classification method was developed to incorporate spatial indices of image objects to improve the shadow/water detection. A number of spatial indices, such as size, shape and spatial neighbour of image objects, were characterized to differentiate water and shadow objects. This generated superior shadow/water detection performance compared to a traditional per-field Extraction and Classification of Homogeneous Objects (ECHO) classification method. The user's accuracies for shadow and water classes were increased to 88% and 92%, compared to 80% and 76% obtained from the traditional ECHO classification approach. Furthermore, an automated approach was developed for shadow-length and corresponding building-height estimation. The accuracy assessment suggested good results for very high buildings, especially for isolated high-rise buildings.
Details
- Title
- Shadow detection and building-height estimation using IKONOS data
- Authors
- Yang Shao (Author) - University of North Carolina, United StatesGregory N Taff (Author) - University of Memphis, United StatesStephen J Walsh (Author) - University of North Carolina, United States
- Publication details
- International Journal of Remote Sensing, Vol.32(22), pp.6929-6944
- Publisher
- Taylor & Francis Ltd.
- Date published
- 2011
- DOI
- 10.1080/01431161.2010.517226
- ISSN
- 0143-1161
- Organisation Unit
- University of the Sunshine Coast, Queensland
- Language
- English
- Record Identifier
- 99449504702621
- Output Type
- Journal article
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- Domestic collaboration
- Web Of Science research areas
- Imaging Science & Photographic Technology
- Remote Sensing
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Source: InCites