DL, short for Description Logic, is aimed at getting a balance between describing ability and reasoning complexity.
Users can adopt DL to write clear and formalized concept description for domain model, which makes ontology
description possess well-defined syntax and semantics and helps to resolve the problem of spatio-temporal reasoning
based on ontology. This paper studies on basic theory of DL and relationship between DL and OWL at first. By
analyzing spatio-temporal concepts and relationship of spatio-temporal GIS, the purpose of this paper is adopting
ontology language based on DL to express spatio-temporal ontology, and employing suitable ontology-building tool to
build spatio-temporal ontology. With regard to existing spatio-temporal ontology based on first-order predicate logic, we
need to transform it into spatio-temporal ontology based on DL so as to make the best of existing research fruits. This
paper also makes a research on translating relationships between DL and first-order predicate logic.
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.
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.
Different geographical phenomena and processes take on diverse laws, this is to say, specific laws of geographical
phenomena and processes should be researched on a given spatial scale. In addition, geographical phenomena and
processes don't linearly change with spatial scale, which can't obtain by linear interpolation or extrapolation. As a result,
we must resolve the problem of multi-scale representation of geographical spatial data, which is also the key technique
of Multi-Scale GIS or Scale-Free GIS.
At the present time people have to adopt multi-ply representation for the sake of satisfying people's research and
production needs on different spatial scales. However, this method has such shortcomings as a good many data
redundancies, ensuring no the consistency of the same spatial entity on different spatial scales, low efficiency of
updating spatial database and bad real-time characteristic of spatial database. Ideal aim of multi-scale representation of
geographical spatial data is deriving desired spatial database of various scales or detail degrees from dominant
cartographic database, which is automatic generalization of geographical spatial data. Research fields of automatic
generalization of geographical spatial data include theory foundation, concept framework, solution and algorithms of
automatic generalization. Therein algorithms of automatic generalization are the technique basis of automatic
generalization of geographical spatial data.
Since the seventies of the last century people have already put continuously forward a large number of algorithms of
automatic generalization. Those algorithms have indeed resolved a good many important problems, but they have some
obvious shortcomings and application confines. This article makes a research on those algorithms of automatic
generalization, and research contents comprise classification, principle, application confines, merits and drawbacks of
algorithms of automatic generalization. This paper also brings forward the research orientation of algorithms of
automatic generalization for the future.
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.
With the singular development of Internet technique and 3DGIS as well as VR and the imminence demand of 3D
visualization from Groundwater information management field, how to display, roam, anatomize and analyze of 3D
structure of Groundwater system on Internet have become a research hotspot in hydrogeology field. We simulated the 3D
Groundwater resource structure of Taiyuan basin and implemented displaying, roaming, anatomizing and analyzing
functions on Internet by Java 3D.