TITLE:
Development of a Generic Model for the Detection of Roof Materials Based on an Object-Based Approach Using WorldView-2 Satellite Imagery
AUTHORS:
Ebrahim Taherzadeh, Helmi Z. M. Shafri
KEYWORDS:
Urban; Object-Based; Discriminant Analysis; Roof Materials; Very High Resolution Imagery; WorldView-2
JOURNAL NAME:
Advances in Remote Sensing,
Vol.2 No.4,
December
16,
2013
ABSTRACT: The detection of impervious surface (IS) in heterogeneous urban
areas is one of the most challenging tasks in urban remote sensing. One of the
limitations in IS detection at the parcel level is the lack of sufficient
training data. In this study, a generic model of spatial distribution of roof
materials is considered to overcome this limitation. A generic model that is
based on spectral, spatial and textural information which is extracted from available training data is proposed. An object-based
approach is used to extract the information inherent in the image. Furthermore,
linear discriminant analysis is used for dimensionality reduction and to
discriminate between different spatial, spectral and textural attributes. The
generic model is composed of a discriminant function based on linear
combinations of the predictor variables that provide the best discrimination
among the groups. The discriminate analysis result shows that of the 54
attributes extracted from the WorldView-2 image, only 13 attributes related to
spatial, spectral and textural information are useful for discriminating
different roof materials. Finally, this model is applied to
different WorldView-2 images from different areas and proves that this model
has good potential to predict roof materials from the WorldView-2 images
without using training data.