A service relation model for web-based land cover change detection

Change detection with remotely sensed imagery is a critical step in land cover monitoring and updating. Although a variety of algorithms or models have been developed, none of them can be universal for all cases. The selection of appropriate algorithms and construction of processing workflows depend largely on the expertise of experts about the algorithm-data relations among change detection algorithms and the imagery data used. This paper presents a service relation model for land cover change detection by integrating the experts' knowledge about the algorithm-data relations into the web-based geo-processing. The algorithm-data relations are mapped into a set of web service relations with the analysis of functional and non-functional service semantics. These service relations are further classified into three different levels, i.e., interface, behavior and execution levels. A service relation model is then established using the Object and Relation Diagram (ORD) approach to represent the multi-granularity services and their relations for change detection. A set of semantic matching rules are built and used for deriving on-demand change detection service chains from the service relation model. A web-based prototype system is developed in. NET development environment, which encapsulates nine change detection and pre-processing algorithms and represents their service relations as an ORD. Three test areas from Shandong and Hebei provinces, China with different imagery conditions are selected for online change detection experiments, and the results indicate that on-demand service chains can be generated according to different users' demands. (C) 2017 Published by Elsevier B.V.