The Research Of Mountains Ontology And Digital Classification In The Framework Of "Digital Mountains"

"Digital Mountains", which was made from the "Digital Earth", aims to promote the sustainable mountains development in the mountains, to provide data, information and methods of support for the coordination of regional development and environmental protection. It plays an important role in the development of Mountains resources, the protection of Mountains environments, Mountains disaster prevention, security and development of Mountains areas in decision-making support for the development and utilization of Mountains resources, monitoring and evaluation Mountains hazards, Mountains eco-environmental protection and socio-economic construction of the Mountains. The Mountains is a multi-element, multi-level, multi-resources and multi-field system, it is complex and giant. The cognition and understanding of the Mountains is helpful for the construction of the scientific and reasonable "Digital Mountains" platform. From this, this paper presents the scientific concept of the Mountains ontology, to express the concept, properties, and spatial data organization with the form of formal language, and establish the conceptualization of ontology model in "Digital Mountains". Moreover, this paper also discuss the logic structure and building methods of the Mountains ontology thoroughly , put forward a integrated spatial data classification program in three level ontology structure. Finally, in the Mountains ontology framework, this paper classifies the lithologic characteristics of the Mountains systematically. In addition, we do profound study of digital classification schemes of Mountains which is based on multi-factor data. The main content and fruit of this paper is as follows:(1) With the concept of Mountains characteristics and attributes, this paper analyze the field of geographic features and characteristics of Mountains with profound research and analysis, then analyze the cognitive level of the Mountains with ontological theory of thinking, and create the expression of the ontological concept of Mountains. The connection and difference of space ontology, domain ontology and Mountains ontology was also analyzed. From the construction of "Digital Mountains", we introduce the classification system and the semantic field's characteristics of geographical ontology in "Digital Mountains". Furthermore, we analyze the spatial entity and the concept of expression of Mountains. Finally, we design the construction form of Mountains spatial database.(2 ) This paper analyzes the logical structure of Mountains ontology, and put forward the construction methods of Mountains ontology. It analyzes the logical structure of Mountains ontology with two aspects of internal factors—spatial data and logical description, which is based on the detailed analysis of the logical language and structure of ontology and geographical ontology. So we put forward conceptual logical structure prototypes of Mountains ontology in macro-level and micro-level. This paper sums up the research of the existing construction methods of geographical ontology, and put forward the method of three-dimensional spatial analysis of Mountains, which is based on ontology. Finally, we also build conceptual model of Mountains ontology with the ontology modeling theory.(3 ) This paper constructs three level integrated program of ontology with hybrid structure. The theoretical study realizes the integration of spatial data classification of "Digital Mountains". To solve the problem of the semantic integration of spatial data heterogeneity in GIS, this paper sums up the concept, types and problems of Geo-spatial data integration by means of the classified applications of Geo-spatial data. It analyzes and compares some different integrated framework which is based on the existing ontology structures. On this basis, we put forward a three-level integrated program in the hybrid structure. Meanwhile, we design the spatial data integrated framework of "Digital Mountains" by the program, and study the classified methods of spatial and geographical information data. We discuss the realized process of classification of the Mountains lithologic factors by the means of the macro-concept prototype of the Mountains ontology.(4 ) By means of Hutchinson algorithm, this paper makes 1:250000 DEM in Sichuan Province from the topographic contour data. To realize the specific applied target, we carefully analyze and descript some factors, such as absolute elevation, relative elevation, slope, aspect, topographic characteristics and hydrology. They are made from the DEM by relative means. Based on the detailed summary of various conception of Mountains, this paper builds a classified system of Mountains and non-Mountains, which is worked comprehensively by three factors of relative elevation, absolute elevation and slope. Then it gets the distinction of Mountains and non-Mountains in Sichuan Province. In the extraction process of gully density, this paper builds a data model which could get gully density automatically. In Sichuan Province, 122 counties are regard as test plots so that the factor layer of gully density in Sichuan Province is yielded.(5 ) There is a variety of projection information of spatial data in GIS classified data. To solve the problem, this paper sums up a new method of spatial projection. To take that the Beijing 54 coordinate transform to the Xi'an 80 coordinate as an example, we analyze and practice with detailed theory. The method resorts to the parameter conversion tools which are developed by Delphi language. It gets seven parameters according to the corresponding coordinates of four points in ArcGIS desktop.(6) I t builds the classification system by the four classified factors of elevation, relative elevation, slope, surface roughness,It provide a new method of the Mountains and un- Mountains. It classifies the Mountains topography grading systematically by means of the formula of Mountains comprehensive evaluation. The five classified factors of relative elevation, slope, surface roughness, gully density and surface relief are chosen to overlay by means of AHP and multi-factor rating weighted method so that 7 different types of data of Mountains terrain relief was gain. The research classifies geomorphology type and relief by means of the overlay analysis of two factors; it gets 50 kinds of comprehensive data of Mountains. It achieves a new method of Mountains digital classification.