Abstract
Abstract. Residential area detection is extremely important for supervision of rush-built and illegal construction behavior to protect arable land and basic farmland. Traditional manual recognition of illegal construction is simple but time-consuming. The specific research work in the thesis includes: the proposition and designing of a multi-scale segmentation method based on watershed segmentation combined with region merging algorithm, comparative experiments of the new algorithm and traditional algorithm. Then, architecture extraction experiment based on the multi-scale segmentation method is carried out and analysis of the precision of comparative experiment results of pixel-based and object-oriented extraction methods is made, all these steps facilitate the automatic mapping of the architecture.
Highlights
Urban land ministry requires timely acquisition and analysis of spatial and temporal information for making informed decisions on land utilization and land supervision
Object extraction method brings similar pixels into the same feature space according to spectral information and spatial information
In object-oriented extraction method, the spectral attributes, such as homogeneity, contrast, angular second moment, entropy, correlation, standard deviation and adjacent boundary length are features to be introduced in objectoriented extraction based on the following improved image segmentation
Summary
Urban land ministry requires timely acquisition and analysis of spatial and temporal information for making informed decisions on land utilization and land supervision. Object extraction method brings similar pixels into the same feature space according to spectral information and spatial information. In this way, buildings do not need to be drawn respectively through digging the whole high-resolution satellite image, they can be extracted into several categories, such as permanent ones, temporary ones, independent ones, continuous ones according to different spectral, shape, texture, topological attributes. In object-oriented extraction method, the spectral attributes, such as homogeneity, contrast, angular second moment, entropy, correlation, standard deviation and adjacent boundary length are features to be introduced in objectoriented extraction based on the following improved image segmentation
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