顧及上下級空間關(guān)系相似性的道路網(wǎng)聯(lián)動匹配方法
發(fā)布時間:2018-05-26 21:26
本文選題:聯(lián)動匹配 + 空間關(guān)系 ; 參考:《測繪學(xué)報(bào)》2016年11期
【摘要】:現(xiàn)有道路網(wǎng)匹配方法中,大多利用道路自身結(jié)點(diǎn)和弧段特征進(jìn)行匹配,而較少注意道路鄰域要素在道路網(wǎng)匹配中的重要定位參考作用,從而影響匹配效率和正確率的進(jìn)一步提高。針對上述問題,本文提出了一種顧及上下級空間關(guān)系相似性的道路網(wǎng)聯(lián)動匹配方法,即模仿人在讀圖時通過特征地物和空間關(guān)聯(lián)尋找目標(biāo)地物的思維過程,將匹配看作是一種特征目標(biāo)尋找、信息關(guān)聯(lián)傳遞的推理過程。首先,運(yùn)用Stroke技術(shù)將復(fù)雜道路網(wǎng)進(jìn)行等級劃分。其次,通過道路骨架關(guān)聯(lián)關(guān)系樹構(gòu)建道路網(wǎng)聯(lián)動匹配模型。最后,選取高等級骨干道路作為起始特征對象,計(jì)算道路間的上下級空間關(guān)系相似性,逐級迭代使匹配信息在道路網(wǎng)聯(lián)動匹配模型中傳遞,從而得到匹配結(jié)果。試驗(yàn)表明,本文算法縮小了待匹配數(shù)據(jù)的搜索范圍,能夠有效提高匹配正確率和效率,尤其在數(shù)據(jù)位移較大、存在非系統(tǒng)性幾何位置偏差的情況下優(yōu)勢明顯。
[Abstract]:In the existing road network matching methods, most of them use the road node and arc feature to match, but less attention is paid to the important location reference role of the road neighborhood elements in road network matching. Thus, the matching efficiency and accuracy are further improved. In order to solve the above problems, this paper proposes a road network matching method which takes into account the similarity between upper and lower spatial relations, that is, imitating the thinking process of finding target objects by means of feature objects and spatial association while reading maps. Matching is regarded as a kind of reasoning process of feature target finding and information association transmission. Firstly, the complex road network is classified by Stroke technology. Secondly, the road network linkage matching model is constructed by the road skeleton correlation tree. Finally, the high-level backbone road is selected as the starting feature object, the similarity of the upper and lower spatial relations between roads is calculated, and the matching information is transmitted in the road network linkage matching model step by step, and the matching result is obtained. The experimental results show that the algorithm reduces the search range of the data to be matched and can effectively improve the accuracy and efficiency of the matching, especially in the case of large data displacement and the existence of non-systematic geometric position deviation.
【作者單位】: 信息工程大學(xué)地理空間信息學(xué)院;
【基金】:國家自然科學(xué)基金(41171305;41571442)~~
【分類號】:P208
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