Geographic Information Services is the services for geographic information, including its geographic data services and
geographic information systems information processing services. Geographic Information Services, its key is to realize
the standardization of geographical information, as well as geographic information processing versatility, just not far
from the conversion of geographic data to share information, only at a higher level of different applications and systems
asked to cooperate with each other to achieve interoperability, in order to achieve the real purpose of geographic
information services.A research on geo-ontology is the important content of Geographic Information Science and Digital
Earth. The ontological foundation for Geographic Information Science is one of four new research fields that were
proposed by UCGIS (University Consortium for Geographic Information Science) in 2000. In 2002 Research Agenda,
the spatial ontology is the first topic of the ten Long-term Research Challenges. By the geo-spatial information semantic
expression and semantic share based on ontology, the concepts of single community are expanded to more wide range
gradually and are linked with Internet. Through the semantic description of service based on ontology, Web services can
be automatic found out, composed, implemented and supervised. In this paper, based on the existing GIS database and
having established geographic information field ontology, we will establish an application ontology database which is
suitable for geographic data. Description Logic designating the corresponding rules knowledge, between the spatial
database and ontology database, the difference ontology database building a definite correlation, the paper will propose a
method on ontology-driven spatial data query. When inquiring a spatial entity, through the logic computation of ontology
database, we can gain the query results, and return the final results. In the last, we will take tobacco planting query of
digital tobacco as an example to test the method whether is feasible and effective.
In the process of remote-sensed image fusion with wavelet packet transform, wavelet basis with different properties can
exhibit different fusion performance. It is significant to find the best wavelet packet basis and apply it in the process.
However, for image fusion, best basis searching algorithm must works within two wavelet packet trees, in the case that
the present algorithm only works within one tree. The paper firstly proposes a new searching algorithm working in two
trees, then realizes a new image fusion method using wavelet packet transform with the best basis that is developed from
the new algorithm. Experiment testifies: under the fusion rule based on texture, the method develops more advantage of
wavelet packet transform, and gains a better fusion performance compared with other image fusion method using
wavelet packet transform (including wavelet transform).
Tobacco is one of important crops in our country, and brings the significant irreplaceable effect into playing in
countrywide economic growth. So the monitoring and scientific management of tobacco fields show especially important
to us. To monitor growing crops in a large scale is a complicated problem and a satisfied method to know what the way a
crop is growing has been sought by the scientists in the field. At present, the study of tobacco remote sensing monitoring
is less both at home and abroad. In this paper, we try to obtain tobacco field and area by remote sensing with Yunan
Province Honghe State Tobacco County as example. We adopt rejecting interfering tobacco field information
classification method of supervision while monitoring and get an ideal result. Simultaneity, we also offered the
suggestion of further improving classification precision.
To monitor growing crops in a large scale is a complicated problem and a satisfied method to know what the way a crop is growing has been sought by the scientists in the field. Remote Sensing was rarely used to monitor growing tobacco with satellitic data. With the development of the sensor, MODIS (Moderate-resolution Imaging Spectroradiometer) could do well in the field. In this paper, the researched subject is the tobacco planted in the province of Yunnan , China. A method to monitor growing tobacco was experimented with modern spatial technology, which integrated MODIS data and the observation of agronomic parameters of crop growth in order to obtain more exact results. The intergraded method were used to analyze the patterns of normalized vegetation index (NDVI) and leaf area index (LAI) for tobacco from planting to harvest, which proved that the MODIS-LAI was consistent with the measured LAI, and the variety of MODIS-LAI was consistent with the variety of the growth of tobacco. It showed that tobacco growth monitoring using intergraded method is practical, which should be extensively applied in arid land in the Southwest China.
Scale is an important factor when people acquire laws of geographical phenomena and processes. Generalized scale
includes not only spatial scale and time scale but also semantic scale in geographic information science. Semantic scale
describes semantic change amplitude and hierarchy of attribute contents of geographic entities. Semantic change
amplitude represents attribute character changes in the unit time, the while hierarchy means classification and rank of
attribute description. Scale is in inverse proportion to detailed degree of geographic entities when GIS displays
multi-scale geographical spatial data. It is difficult that existing GIS display features of different semantic scale. As for
the classified or ranked geographical spatial data the optimal solution is the hierarchy or rank of geographic entities
displayed is higher when scale becomes small, so the generalization degree of detailed feature is higher.
Ontology is a kind of modeling tool of concept model that is able to represent information system at the semantics and
knowledge level. Geoontology is a kind of domain ontology and offers glossaries and relationships among concepts in
the geographic spatial information domain. As far as the geographical hierarchy and classification system is concerned
the relationships among the geographical concepts is hierarchy relationship, namely the relationship between the parent
concepts and the child concepts or between hypernyms and hyponyms. Geoontology can represent formally this
hierarchy relationship. A geographical concept can be navigated to its parent concept or child concept, and implements
the automatic generalization of geographic spatial data by merging the features in the geographical feature classes
corresponding to all child concepts of the some geographical concept in geoontology. However the automatic
generalization method based on the geoontology cannot smooth the linear features and the boundary of polygon features,
which should be implemented by resorting to other automatic generalization algorithms.
KEYWORDS: Databases, Data storage, Raster graphics, Geographic information systems, Data modeling, Binary data, Complex systems, System integration, Space operations, Remote sensing
With increasing demands of GIS applications system in a complex, integrated, and other areas, the spatial data are required rapid growth for the systems, and users are more and more on the demand spatial data. The method which traditional documents express spatial data is obviously unable to meet these needs. The SDE is at present the widespread application intermediate technology in the system integration, and is one kind of realization in the spatial database application. The spatial data can be expressed by vector data structure and raster one which may be managed thought ArcSDE. In this paper, regarding ArcSDE as the space data engine and using the large-scale relation database (RDBMS), we has set up three layers system structure, realized the effective organization and management to spatial data, and gotten very good application in practice.
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