Shadow detection and building-height estimation using IKONOS data
Abstract:
The spectral confusion between shadow and water (or other dark surfaces) often results in suboptimal urban classification performances, especially from highresolution 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. © 2011 Taylor & Francis.
Año de publicación:
2011
Keywords:
Fuente:
Tipo de documento:
Article
Estado:
Acceso restringido
Áreas de conocimiento:
- Simulación por computadora
- Sensores remotos
Áreas temáticas:
- Estructuras públicas
- Física aplicada
- Geografía matemática