【摘要】：在經(jīng)濟(jì)、社會(huì)快速發(fā)展的大背景下，人們對(duì)空間信息的需求不斷增加，空間信息時(shí)效性作用日益突出。時(shí)態(tài)GIS的發(fā)展進(jìn)一步拓寬了空間信息應(yīng)用的范圍，在時(shí)空范圍內(nèi)研究空間信息的變化成為GIS發(fā)展的新內(nèi)容。對(duì)時(shí)空變化信息的研究，是空間分析在時(shí)間軸上拓展以進(jìn)行時(shí)空分析的需要。自動(dòng)檢測(cè)出不同時(shí)期數(shù)據(jù)庫(kù)之間的差異，將發(fā)生變化的地理信息數(shù)據(jù)插入己有數(shù)據(jù)庫(kù)中，實(shí)現(xiàn)空間信息增量式更新是時(shí)空變化檢測(cè)的重要應(yīng)用方面。對(duì)時(shí)空數(shù)據(jù)變化檢測(cè)的研究，，本文從矢量時(shí)空數(shù)據(jù)方面簡(jiǎn)要地討論了進(jìn)行變化檢測(cè)的基本理論和方法，主要內(nèi)容如下： （1）從時(shí)空變化的連續(xù)性和變化內(nèi)容兩個(gè)方面，總結(jié)了時(shí)空變化的20種基本類型。從時(shí)空數(shù)據(jù)的空間特征、時(shí)間特征、屬性特征三個(gè)方面的討論了時(shí)空變化分析需要解決的9類基本問(wèn)題。分層次定義了單實(shí)體時(shí)空變化類型，在單實(shí)體變化結(jié)果的基礎(chǔ)上，采用集合論思想定義了多實(shí)體時(shí)空變化類型。 （2）以同名實(shí)體匹配技術(shù)為基礎(chǔ)，從實(shí)體空間特征的四個(gè)方面——距離（位置）、形狀、尺寸、方向——討論了對(duì)空間點(diǎn)、線、面要素進(jìn)行幾何特征相似度計(jì)算的方法，分析、比較了各方法的特點(diǎn)及適用范圍。針對(duì)線要素相似度計(jì)算提出了改進(jìn)的結(jié)點(diǎn)距離相似度算法。 （3）從線要素的整體和細(xì)節(jié)兩方面進(jìn)行了相似度差異的比較，該方法比單一使用其中一種的相似度計(jì)算結(jié)果有更高的準(zhǔn)確度。由于面要素空間復(fù)雜性較高，對(duì)于面要素的變化檢測(cè)，通過(guò)計(jì)算多特征相似度來(lái)比較不同時(shí)態(tài)要素之間的各種差異，并對(duì)各相似度加權(quán)平均來(lái)計(jì)算總相似度值。這種方法計(jì)算總相似度具有一定的靈活性，并且可依據(jù)空間數(shù)據(jù)的尺度和精度選擇不同的相似度計(jì)算方法。 （4）對(duì)多要素之間的的復(fù)雜變化檢測(cè)，將1:1變化檢測(cè)結(jié)果進(jìn)行綜合，通過(guò)查找變化關(guān)系中的重復(fù)要素來(lái)組合新的復(fù)雜變化關(guān)系。 （5）基于COM組件設(shè)計(jì)思想，設(shè)計(jì)實(shí)現(xiàn)了矢量時(shí)空數(shù)據(jù)幾何變化檢測(cè)系統(tǒng)原型。闡述了針對(duì)點(diǎn)、線、面矢量時(shí)空數(shù)據(jù)進(jìn)行幾何變化檢測(cè)的算法流程。以不同時(shí)態(tài)（1980年和1990年）的道路和居民地要素為實(shí)驗(yàn)數(shù)據(jù)進(jìn)行了幾何變化檢測(cè)試驗(yàn)，結(jié)果表明，該幾何變化檢測(cè)模型的具有一定的可行性與合理性，可以為時(shí)空數(shù)據(jù)庫(kù)的更新及變化檢測(cè)分析提供支撐。
[Abstract]:Under the background of rapid economic and social development, the demand for spatial information is increasing, and the timeliness of spatial information is becoming more and more important. The development of temporal GIS further widens the scope of spatial information application, and it becomes a new content of GIS to study the change of spatial information in time and space. The research of spatiotemporal variation information is the need of spatial analysis expanding on the time axis for spatiotemporal analysis. Automatically detecting the differences between databases in different periods, inserting the changed geographic information data into the existing databases, and realizing incremental updating of spatial information is an important aspect of space-time change detection. In this paper, the basic theories and methods of change detection are briefly discussed in terms of vector spatio-temporal data. The main contents are as follows: (1) from the continuity and change content of spatio-temporal change, Twenty basic types of temporal and spatial variations are summarized. From three aspects of spatial feature, time feature and attribute feature of spatio-temporal data, 9 kinds of basic problems need to be solved in spatio-temporal change analysis are discussed. On the basis of the result of the change of single entity, this paper defines the type of spatio-temporal change of multi-entity by means of set theory. (2) based on the matching technology of entity with the same name, This paper discusses the methods of calculating the similarity of geometric features of spatial points, lines and surfaces from four aspects of physical spatial features: distance (position), shape, dimension and direction. The characteristics and application range of these methods are compared. An improved algorithm of node distance similarity is proposed for line element similarity calculation. (3) the similarity differences are compared in terms of the whole and the details of line elements. This method has a higher accuracy than using one of them alone. Because of the high spatial complexity of surface elements, for the change detection of surface elements, the differences between different temporal elements are compared by calculating multi-feature similarity, and the total similarity value is calculated by weighted average of each similarity. This method has some flexibility to calculate the total similarity, and it can select different similarity calculation methods according to the scale and precision of spatial data. (4) detecting the complex change between multiple elements. The 1:1 change detection results are synthesized and the new complex change relations are combined by searching the repeated elements in the change relationship. (5) based on the COM component design idea, the prototype of the geometric change detection system for vector space-time data is designed and implemented. The algorithm flow of geometric change detection for point, line and plane vector spatiotemporal data is described. Based on the experimental data of different temporal (1980 and 1990) roads and inhabitants, the results show that the geometric change detection model is feasible and reasonable. It can provide support for update and change detection analysis of time-space database.
【學(xué)位授予單位】：蘭州交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：P208

【參考文獻(xiàn)】

相關(guān)期刊論文 前4條

1 范大昭,張永生,雷蓉,郭海濤;GIS數(shù)據(jù)自動(dòng)更新技術(shù)的研究[J];測(cè)繪科學(xué);2005年03期

2 汪匯兵;唐新明;洪志剛;;版本差量式時(shí)空數(shù)據(jù)模型研究[J];測(cè)繪科學(xué);2006年05期

3 吳長(zhǎng)彬;閭國(guó)年;;一種改進(jìn)的基于事件-過(guò)程的時(shí)態(tài)模型研究[J];武漢大學(xué)學(xué)報(bào)(信息科學(xué)版);2008年12期

4 張橋平,李德仁,龔健雅;城市地圖數(shù)據(jù)庫(kù)面實(shí)體匹配技術(shù)[J];遙感學(xué)報(bào);2004年02期

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