模式识别的空间数据联动更新技术研究
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摘要
针对多尺度空间数据联动更新技术体系不完善的问题,该文提出了一套系统完善的多尺度空间数据联动更新技术体系。该技术体系以模式识别理论为基础,以"更新信息检测—自适应增量更新—更新信息多尺度匹配与传递"为主线,实现了模式识别理论技术与多尺度空间数据联动更新应用的深度融合,为空间数据快速更新提供了重要的技术支撑和保障。基于广州市增城区空间数据联动更新的实验结果表明:该文提出的方法对于复杂城市区域多尺度空间数据联动更新是非常有效的。
Aiming at the problem which the technical system of multi-scale spatial data linkage updating is imperfect,this paper puts forward a technical system for multi-scale spatial data linkage updating.The technical system is based on pattern recognition theory and takes"updating information detection-adaptive incremental updating-updating information multi-scale matching and transmission"as the main line,which realizes the deep integration of pattern recognition technology and multi-scale spatial data linkage update application and can provide important technical support and guarantee for the rapid updating of spatial data.The experimental results in Zengcheng district,guangzhou shows that the method proposed in this paper is very effective for multi-scale spatial data linkage updating in complex urban areas.
Aiming at the problem which the technical system of multi-scale spatial data linkage updating is imperfect,this paper puts forward a technical system for multi-scale spatial data linkage updating.The technical system is based on pattern recognition theory and takes"updating information detection-adaptive incremental updating-updating information multi-scale matching and transmission"as the main line,which realizes the deep integration of pattern recognition technology and multi-scale spatial data linkage update application and can provide important technical support and guarantee for the rapid updating of spatial data.The experimental results in Zengcheng district,guangzhou shows that the method proposed in this paper is very effective for multi-scale spatial data linkage updating in complex urban areas.
引文
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[8]张志强,张新长,辛秦川,等.结合像元级和目标级的高分辨率遥感影像建筑物变化检测[J].测绘学报,2018,47(1):102-112.(ZHANG Zhiqiang,ZHANG Xinchang,XIN Qinchuan,et al.Combining the pixel-based and object-based methods for building change detection using high-resolution remote sensing images[J].Acta Geodaetica et Cartographica Sinica,2018,47(1):102-112.)
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[10]TONG X,JIN Y,LI L,et al.Area-preservation simplification of polygonal boundaries by the use of the structured total least squares method with constraints[J].Transactions in GIS,2015,19(5):780-799.
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[12]罗国纬.多尺度居民地、道路网的自适应匹配与级联关系研究[D].广州:中山大学,2017.(LUO Guowei.Research on adaptive matching and cascade relationship of multi-scale residential area and road network[D].Guangzhou:Sun Yat-sen University,2017.)
[13]ZHANG X,LUO G,HE G,et al.A multi-scale residential areas matching method using relevance vector machine and active learning[J].ISPRS International Journal of Geo-Information,2017,6(3):70.
[14]HE X,ZHANG X,YANG J.Progressive amalgamation of building clusters for map generalization based on scaling subgroups[J].ISPRS International Journal of Geo-Information,2018,7(3):116.
[15]HE X,ZHANG X,XIN Q.Recognition of building group patterns in topographic maps based on graph partitioning and random forest[J].ISPRS Journal of Photogrammetry and Remote Sensing,2018,136:26-40.
[16]郭泰圣.基于人工神经网络的城市居民地更新信息检测与多尺度制图传递研究[D].广州:中山大学,2015.(GUO Taisheng.Research on the detection and multiscale cartographical transmission of urban residential area updating information based on artificial neural network[D].Guangzhou:Sun Yat-sen University,2015.)
[2]陈军,李志林,蒋捷,等.基础地理数据库的持续更新问题[J].地理信息世界,2004(5):1-5.(CHEN Jun,LIZhilin,JIANG Jie,et al.Key issues of continuous updating of geo-spatial databases[J].Geomatics World,2004(5):1-5.)
[3]童小华,邓愫愫,史文中.基于概率的地图实体匹配方法[J].测绘学报,2007,36(2):210-217.(TONGXiaohua,DENG Susu,SHI Wenzhong.A probabilistic theory-based matching method[J].Acta Geodaetica et Cartographica Sinica,2007,36(2):210-217.)
[4]陈玉敏,龚健雅,史文中.多尺度道路网的距离匹配算法研究[J].测绘学报,2007(1):84-90.(CHEN Yumin,GONG Jianya,SHI Wenzhong.A distance-based matching algorithm for multi-scale road networks[J].Acta Geodaetica et Cartographica Sinica,2007(1):84-90.)
[5]BOBZIEN M,BURGHARDT D,PETZOLD I.Regeneralisation and construction-two alternative approaches to automated incremental updating in MRDB[C]//International Cartographic Conference:Mapping Approaches into a Changing World 2005.[S.l.:s.n.],2005.
[6]DUIN R P,PEKALSKA E.The science of pattern recognition.achievements and perspectives[M].Berlin:Springer,2007:221-259.
[7]郭泰圣,张新长,梁志宇.神经网络决策树的矢量数据变化信息快速识别方法[J].测绘学报,2013,42(6):937-944.(GUO Taisheng,ZHANG Xinchang,LIANGZhiyu.Research on change information recognition method of vector data based on neural network decision tree[J].Acta Geodaetica et Cartographica Sinica,2013,42(6):937-944.)
[8]张志强,张新长,辛秦川,等.结合像元级和目标级的高分辨率遥感影像建筑物变化检测[J].测绘学报,2018,47(1):102-112.(ZHANG Zhiqiang,ZHANG Xinchang,XIN Qinchuan,et al.Combining the pixel-based and object-based methods for building change detection using high-resolution remote sensing images[J].Acta Geodaetica et Cartographica Sinica,2018,47(1):102-112.)
[9]张新长,郭泰圣,唐铁.一种自适应的矢量数据增量更新方法研究[J].测绘学报,2012,41(4):613-619.(ZHANG Xinchang,GUO Taisheng,TANG Tie.An adaptive method for incremental updating of vector data[J].Acta Geodaetica et Cartographica Sinica,2012,41(4):613-619.)
[10]TONG X,JIN Y,LI L,et al.Area-preservation simplification of polygonal boundaries by the use of the structured total least squares method with constraints[J].Transactions in GIS,2015,19(5):780-799.
[11]MUSTIRE S,DEVOGELE T.Matching networks with different levels of detail[J].GeoInformatica,2008,12(4):435-453.
[12]罗国纬.多尺度居民地、道路网的自适应匹配与级联关系研究[D].广州:中山大学,2017.(LUO Guowei.Research on adaptive matching and cascade relationship of multi-scale residential area and road network[D].Guangzhou:Sun Yat-sen University,2017.)
[13]ZHANG X,LUO G,HE G,et al.A multi-scale residential areas matching method using relevance vector machine and active learning[J].ISPRS International Journal of Geo-Information,2017,6(3):70.
[14]HE X,ZHANG X,YANG J.Progressive amalgamation of building clusters for map generalization based on scaling subgroups[J].ISPRS International Journal of Geo-Information,2018,7(3):116.
[15]HE X,ZHANG X,XIN Q.Recognition of building group patterns in topographic maps based on graph partitioning and random forest[J].ISPRS Journal of Photogrammetry and Remote Sensing,2018,136:26-40.
[16]郭泰圣.基于人工神经网络的城市居民地更新信息检测与多尺度制图传递研究[D].广州:中山大学,2015.(GUO Taisheng.Research on the detection and multiscale cartographical transmission of urban residential area updating information based on artificial neural network[D].Guangzhou:Sun Yat-sen University,2015.)
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