Abstract
Abstract. Determination of the maximum ability for feature extraction from satellite imageries based on ontology procedure using cartographic feature determination is the main objective of this research. Therefore, a special ontology has been developed to extract maximum volume of information available in different high resolution satellite imageries and compare them to the map information layers required in each specific scale due to unified specification for surveying and mapping. ontology seeks to provide an explicit and comprehensive classification of entities in all sphere of being. This study proposes a new method for automatic maximum map feature extraction and reconstruction of high resolution satellite images. For example, in order to extract building blocks to produce 1 : 5000 scale and smaller maps, the road networks located around the building blocks should be determined. Thus, a new building index has been developed based on concepts obtained from ontology. Building blocks have been extracted with completeness about 83 %. Then, road networks have been extracted and reconstructed to create a uniform network with less discontinuity on it. In this case, building blocks have been extracted with proper performance and the false positive value from confusion matrix was reduced by about 7 %. Results showed that vegetation cover and water features have been extracted completely (100 %) and about 71 % of limits have been extracted. Also, the proposed method in this article had the ability to produce a map with largest scale possible from any multi spectral high resolution satellite imagery equal to or smaller than 1 : 5000.
Highlights
It is a fact that high spatial resolution satellite imagery is an alternative for aerial photography due to its advantages over aerial photogrammetry such as globally availability, low cost, including hyper or multi spectral bands and so on
Main image was subtracted from shadow-free image to produce the image with maximum amount of pixels related to road networks, and there were few pixels related to water features, shadows and vegetation cover (Figure 8A)
A new ontological and morphological approach for 1:5000 and smaller scale map production was proposed in this article
Summary
It is a fact that high spatial resolution satellite imagery is an alternative for aerial photography due to its advantages over aerial photogrammetry such as globally availability, low cost, including hyper or multi spectral bands and so on. A recent research developed an automatic object rule-based approach to extract features from high resolution multi spectral satellite images (Bouziani et al, 2010). This method consists of pixel-based, object-based and rule-based techniques. Some rules were created using ontology and a set of morphological operations of different sizes and orientations performed on the initial image to build the Differential Morphological Profile (DMP) to provide image structural information Resulted image in this level contained maximum data of roads, blocks of buildings, vegetation covers and shadows. Results showed a better performance for feature extraction in proposed method
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
