Along with the development of earth observation technology, large amounts of geospatial information are accessible.
There are also a lot of geospatial data and services which are shared on the Internet. However they vary in formats and
are stored at various organizations leading to problems of data discovery, data interoperability and usability. The Open
Geospatial Consortium (OGC) has developed standard service called catalogue in order to overcome this problem. The
goal of a geospatial catalogue is to support a wide range of users in discovering relevant geographic data and services
from heterogeneous and distributed repositories. But in most of geospatial catalogue services, the search functionality is
limited to the direct match of keywords from metadata, the OGC catalogues may not return useful results as the used
keywords often do not match with the meta-information stored in the catalogues. In this paper, we propose a geospatial
semantic catalogue services that aims at overcoming this limitation.
In this paper, a multi-level image representation model is developed and used for multi-spectral remote sensing image
retrieval in order to narrow the gap between the low-level feature and high-level semantic. This model consists of an
image segmentation part, a feature extraction part and semantic extraction part. The first two parts aim at the extraction
of primitive region feature of an image. In these two steps, an improved JSEG algorithm is used to segment the image
stored in the database, then spectral feature and texture feature are extracted for each region. In semantic extraction part,
the semantic information hidden in different regions of different images is extracted by Bayesian method and expectation
maximization (EM) method. At last, positive example and negative example concept is used in image retrieval instead of
relevant feedback. Experiment shows that this method not only improves the accuracy of the result but also decreases the
complexity of retrieval.
Nowadays, huge volumes of geospatial data and services are available and accessible to people all over the world.
However, they are searched mostly based on keyword, which is inherently restricted by the ambiguities of natural
language, which can lead to low precision and recall. In this paper, semantic share of geospatial data and services are
studied based on ebXML registry. But ebXML registry specification doesn't take into account the registration of the
semantic information. So we define how OWL DL constructs are mapped to ebXML registry information model
(ebRIM) constructs without causing any changes in the core ebXML registry specification. After that, predefined stored
procedures are provided in the ebXML registry for semantic search, which provide necessary means to exploit the
enhanced semantics stored in the Registry. Then, geospatial ontologies in change detection application of remote sensing
based on Global Change Master Directory, ISO19119 and ISO19115 are established. Finally, a prototype system is
developed based on an open source-ebxmlrr to demonstrate the proposed model and approach.