Semantic Description And Registry Mechanism Of Sharing Remote Sensing Image Processing Service Based On WSMO

Remote sensing images derived from multi-platform, multi-sensor, multi-angle, high spatial resolution, high spectral resolution and high phase resolution become an import part of spatial information, which are applied in many domains, including land-use survey, crop yield assessment, forest resources survey, basic mapping, urban planning, assessment of major disasters and environmental events, etc. The growing field of remote sensing applications and the deepening technology of remote sensing applications challenge the sharing of data-centric approach. User demand for remote sensing information is not only raw data and primary products but also advanced imaging products and knowledge which processing by specialized remote sensing digital image processing. The user’s individual requirements also decide complexity of processing and diversity of algorithm. Single remote sensing image processing software has been very difficult to cope with such a large number of user needs. Thus, providing remote sensing image processing by service, facilitating automated Web service discovery, composition, interoperation and invocation, deepening the level of service sharing and semantic interoperability become an important research topic in future.Semantic description supplies Web service providers with a core set of markup language constructs for describing the properties and capabilities of their Web services in unambiguous, computer-intepretable form, which is the prerequisite of semantic sharing and interoperability. OWL-S, WSMO and other methods provide a wide range of choices for the semantic description of remote sensing image processing services. OWL-S appears earlier and has a number of support tools, which are the most salient initiatives to describe Semantic Web Services and occupy the mainstream in semantic geospatial domain. However, OWL-S is based on OWL which has serious limitations both on a conceptual level and with respect to some of its formal properties. Therefore, the type of inputs and outputs can be semantically annotated but the relation between them cannot be captured. These unresolved issues were the main motivation to provide an alternative, uinified language for WSMO. WSMO provides a family of layered logical languages which combines conceptual modelling with rules. The various languages of the WSML family of ontology languages provide different expressiveness and different computational guarantees, which is more appropriate to describe the different levels of semantic description for the remote sensing image processing services and support different levels of sharing and semantic interoperability.In this paper, we choose the remote sensing image processing services as the research object. We fouce on the shortcomings of syntax description and combine the feature of remote sensing image processing, including types of diversity, the processing model are unique, the complexity of processing algorithms, etc. This paper researches on semantic description and registry mechanism of remote sensing image processing service based on WSMO. The study includes semantic description of remote sensing image processing service based on the WSMO, domain ontologies of remote sensing image processing based on WSMO, semantic registry mechanism based on WSMO, etc. The main contents of this paper are as follows:(1) We analysis the problems and shortcomings of syntax description for remote sensing image processing service, then point out that importance and necessity of semanctic description. After comparing various existing advantages and disadvantages of semantic web services framework, we choose WSMO as the semantic web services framework of remote sensing image processing service. Because WSMO provide a rich family of logic languages organised along two main branches, corresponding to description logics and logic programming and enables a better trade-off between expressiveness and tractability. It lays a theoretical foundation for semantic sharing of remote sensing image processing service.(2) According to the existing standards and norms in remote sensing domain and function module of some typical remote sensing image processing software. We divide the category of remote sensing image processing service, identify the process of remote sensing image processing service, extract input and output semantics from functional module. At the same time, in order to clarify the expression of input/output semantics, we extended ISO19115-2 standard, adding quality information, track information, sensor information, band information, calibration information and imaging supporting information, then this paper form a complete meta-data description model of remote sensing image. On this basis, we propose to build domain ontologies of remote sensing through the five stages of developmentand implement ontology standardization, conceptualization, formalization, as well as the maintenance of body. Then, we built the remote sensing image data type ontology and ISO19119-based classification of remote sensing image processing operations ontology firstly and implement the formalization based on WSML, which provide the support for semantic annotation of remote sensing image processing service,(3) In order to unify organization and management of multi-level semantic description of remote sensing image processing services based on WSMO, this paper researches on semantic registry mechanism based on WSMO. On the one hand, we analysis the mainstream method for semantic registry, propose the semantic registry information model which is used to organize the syntax metadata and semantic description which is formalized by WSML variant. On the other hand, in order to compatibility with existing interface of catalogue service, we extend the protocol of traditional catalogue service, including publishing and discovery message, then we implement publishing and discovery of different levels semantic description, or binding with syntax metadata.(4) Aiming at different types of semantic matching algorithm, we test discovery mechanism of remote sensing image processing services. Then, we propose a unified processing framework for different semantic matching algorithm, including Lightweight-DL, Lightweight-Rule, Heavyweight-Rule, which could support different User needs and different levels of semantic registration of sharing mechanism.(5) Based on the theoretical results of the study, this paper develops the semantic registration prototype system for sharing remote sensing image processing services, implements the organization and storage of semantic description of the services, and extends the semantic message protocol based on catalogue service criterion. Thus, this prototype system demonstrates scientific character and feasibility of our research.