本文選題：空間數(shù)據(jù)庫 + 空間數(shù)據(jù)管理��； 參考：《首都師范大學》2013年碩士論文

【摘要】：近年來隨著遙感技術、地理信息系統(tǒng)技術的不斷發(fā)展,GIS的應用領域越發(fā)廣泛,GIS中空間數(shù)據(jù)量呈指數(shù)級別增長,尤其是大數(shù)據(jù)和非結構化數(shù)據(jù)的大量出現(xiàn),對常用的關系型或對象關系型數(shù)據(jù)庫的空間數(shù)據(jù)管理能力提出了巨大挑戰(zhàn)。 隨著Web2.0時代的到來,為滿足爆炸式增長的互聯(lián)網的應用需求,非關系型數(shù)據(jù)庫這一全新的數(shù)據(jù)管理技術應運而生。非關系型數(shù)據(jù)庫在存儲、查詢和管理大數(shù)據(jù)和非結構化數(shù)據(jù)方面具有優(yōu)勢。本文對關系型和非關系型空間數(shù)據(jù)庫進行對比研究,從中選出MongoDB、ArcSDE(Oracle)和PostGIS作為代表,從體系架構、存儲機制和操作方式等方面進行了分析,通過選定定性和定量評價因子建立評價體系,并開展相關實驗,指出非關系和關系型數(shù)據(jù)空間數(shù)據(jù)庫空間數(shù)據(jù)管理的特點；在此基礎上,設計了非關系型和關系型數(shù)據(jù)庫協(xié)同應用方案,并基于OGC的簡單要素模型和面向對象和組件技術,對其中的關鍵技術進行實現(xiàn)；將協(xié)同應用方案在地震救援數(shù)據(jù)管理系統(tǒng)中進行了應用并對結果進行了評價分析。 本文主要的研究結論和成果如下： 1.通過建立的定量和定性的評價指標體系,對MongoDB、ArcSDE和PostGIS進行對比研究,得出在相同數(shù)據(jù)大小下MongoDB存儲空間矢量數(shù)據(jù)較ArcSDE和PostGIS消耗時間少,而存儲相同大小柵格數(shù)據(jù)ArcSDE的速率最快,且磁盤消耗少：在空間查詢時,相同數(shù)據(jù)范圍MongoDB的查詢效率高于其他兩者,范圍越大,優(yōu)勢越明顯。 2.根據(jù)對比分析的結果,提出MongoDB存儲管理矢量空間數(shù)據(jù)和空間元數(shù)據(jù),ArcSDE存儲管理柵格數(shù)據(jù)的協(xié)同應用方案；并對協(xié)同中的非關系型數(shù)據(jù)庫空間數(shù)據(jù)存儲,關系型和非關系型空間數(shù)據(jù)庫存儲數(shù)據(jù)的遷移和采用統(tǒng)一管理方式對兩者進行管理的關鍵技術進行了實現(xiàn)。 3.根據(jù)地震救援數(shù)據(jù)管理的需求,將非關系型數(shù)據(jù)庫和關系型數(shù)據(jù)庫協(xié)同方案應用于地震救援數(shù)據(jù)管理系統(tǒng)中。采用MongoDB和ArcSDE協(xié)同應用對系統(tǒng)進行了設計和實現(xiàn),實現(xiàn)結果表明非關系型和關系型數(shù)據(jù)庫協(xié)同提高了地震救援數(shù)據(jù)的存儲和查詢效率,降低了數(shù)據(jù)存儲的磁盤消耗,且使得數(shù)據(jù)庫的更新和擴展變的更加方便。能更好地滿足地震救援數(shù)據(jù)管理的需求。
[Abstract]:In recent years, with the development of remote sensing technology and the continuous development of GIS technology, the spatial data volume in GIS is increasing exponentially, especially the emergence of big data and unstructured data. This paper presents a great challenge to the spatial data management ability of relational or object-relational databases. With the arrival of Web2.0 era, in order to meet the demand of explosive growth of Internet application, non-relational database, a new data management technology, came into being. Non-relational databases have advantages in storing, querying and managing big data and unstructured data. This paper makes a comparative study of relational and non-relational spatial databases, and selects MongoDB ArcSDE Oracle and PostGIS as representatives to analyze the architecture, storage mechanism and operation mode of the database. By selecting qualitative and quantitative evaluation factors, the evaluation system is established, and relevant experiments are carried out. The characteristics of spatial data management in non-relational and relational data spatial databases are pointed out. The cooperative application scheme of non-relational and relational database is designed, and the key technologies are implemented based on the simple element model of OGC and object-oriented and component technology. The cooperative application scheme is applied to the seismic rescue data management system and the results are evaluated and analyzed. The main conclusions and results of this paper are as follows: 1. The quantitative and qualitative evaluation index system was established to compare MongoDBE ArcSDE and PostGIS. The results show that the storage time of MongoDB space vector data is less than that of ArcSDE and PostGIS under the same data size, but the rate of storing the same size raster data ArcSDE is the fastest. And the disk consumption is less: in spatial query, the query efficiency of MongoDB in the same data range is higher than that of the other two, the larger the scope, the more obvious the advantage. 2. According to the results of comparative analysis, this paper proposes a collaborative application scheme of MongoDB storage and management vector spatial data and spatial metadata storage and management raster data, and stores spatial data of non-relational database in collaboration. The key technologies of storing data in relational and non-relational spatial databases and using unified management are implemented. 3. According to the requirement of seismic rescue data management, the cooperative scheme of non-relational database and relational database is applied to the seismic rescue data management system. The system is designed and implemented by the cooperative application of MongoDB and ArcSDE. The results show that non-relational and relational databases can improve the storage and query efficiency of seismic rescue data and reduce the disk consumption of data storage. And make the update and expansion of the database more convenient. It can better meet the needs of earthquake rescue data management.
【學位授予單位】：首都師范大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：P208

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