一种众源车载GPS轨迹大数据自适应滤选方法
P228; 基于同步高低精度GPS轨迹数据的空间特征和GPS误差分布原理，提出了一种众源GPS车载轨迹大数据自适应分割-滤选模型。该模型首先通过角度、距离约束将完整的车载 GPS 轨迹数据进行分割，以轨迹分割段作为基本滤选单元；然后通过对比轨迹分割段内 GPS 轨迹向量与其参考基线间的相似度，按照相似度与GPS定位精度之间的量化关系指导滤选。试验结果表明，该方法可以实现车载轨迹大数据按信息提取精度需求的滤选。...
Saved in:
| Published in | 测绘学报 Vol. 45; no. 12; pp. 1455 - 1463 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
深圳大学 土木工程学院 空间信息智能感知与服务深圳市重点实验室，广东 深圳 518060
2016
武汉大学测绘遥感信息工程国家重点实验室,湖北 武汉,430079%武汉大学测绘遥感信息工程国家重点实验室，湖北 武汉 430079 |
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| Abstract | P228; 基于同步高低精度GPS轨迹数据的空间特征和GPS误差分布原理，提出了一种众源GPS车载轨迹大数据自适应分割-滤选模型。该模型首先通过角度、距离约束将完整的车载 GPS 轨迹数据进行分割，以轨迹分割段作为基本滤选单元；然后通过对比轨迹分割段内 GPS 轨迹向量与其参考基线间的相似度，按照相似度与GPS定位精度之间的量化关系指导滤选。试验结果表明，该方法可以实现车载轨迹大数据按信息提取精度需求的滤选。 |
|---|---|
| AbstractList | 基于同步高低精度GPS轨迹数据的空间特征和GPS误差分布原理,提出了一种众源GPS车载轨迹大数据自适应分割-滤选模型。该模型首先通过角度、距离约束将完整的车载GPS轨迹数据进行分割,以轨迹分割段作为基本滤选单元;然后通过对比轨迹分割段内GPS轨迹向量与其参考基线间的相似度,按照相似度与GPS定位精度之间的量化关系指导滤选。试验结果表明,该方法可以实现车载轨迹大数据按信息提取精度需求的滤选。 P228; 基于同步高低精度GPS轨迹数据的空间特征和GPS误差分布原理，提出了一种众源GPS车载轨迹大数据自适应分割-滤选模型。该模型首先通过角度、距离约束将完整的车载 GPS 轨迹数据进行分割，以轨迹分割段作为基本滤选单元；然后通过对比轨迹分割段内 GPS 轨迹向量与其参考基线间的相似度，按照相似度与GPS定位精度之间的量化关系指导滤选。试验结果表明，该方法可以实现车载轨迹大数据按信息提取精度需求的滤选。 |
| Abstract_FL | Vehicles’GPS traces collected by crowds have being as a new kind of big data and are widely applied to mine urban geographic information with low-cost,quick-update and rich-informative.However, the growing volume of vehicles’GPS traces has caused difficulties in data processing and their low quality adds uncertainty when information mining.Thus,it is a hot topic to extract high-quality GPS data from the crowdsourced traces based on the expected accuracy.In this paper,we propose an efficient partition-and-filter model to filter trajectories with expected accuracy according to the spatial feature of high-precision GPS data and the error rule of GPS data.First,the proposed partition-and-filter model to partition a trajectory into sub-trajectories based on the constrained distance and angle,which are chosen as the basic unit for the next processing step.Secondly,the proposed method collects high-quality GPS data from each sub-trajectory according to the similarity between GPS tracking points and the reference baselines constructed using random sample consensus algorithm.Experimental results demonstrate that the proposed method can effectively pick up high quality GPS data from crowdsourced trace data sets with the expected accuracy. |
| Author | 唐炉亮 杨雪 牛乐 常乐 李清泉 |
| AuthorAffiliation | 武汉大学测绘遥感信息工程国家重点实验室;深圳大学土木工程学院空间信息智能感知与服务深圳市重点实验室 |
| AuthorAffiliation_xml | – name: 武汉大学测绘遥感信息工程国家重点实验室,湖北 武汉,430079%武汉大学测绘遥感信息工程国家重点实验室，湖北 武汉 430079; 深圳大学 土木工程学院 空间信息智能感知与服务深圳市重点实验室，广东 深圳 518060 |
| Author_FL | YANG Xue CHANG Le LI Qingquan TANG Luliang NIU Le |
| Author_FL_xml | – sequence: 1 fullname: TANG Luliang – sequence: 2 fullname: YANG Xue – sequence: 3 fullname: NIU Le – sequence: 4 fullname: CHANG Le – sequence: 5 fullname: LI Qingquan |
| Author_xml | – sequence: 1 fullname: 唐炉亮 杨雪 牛乐 常乐 李清泉 |
| BookMark | eNotj81Kw0AUhWdRwVr7CC5dpt6bmWQyy1I0CgWFdl9mJkl_0FRbRN0FN-Ki4MLqCxQrLkRwY6vBl2lj-hbG1sW958D5uIe7QXJhN_QJ2UIoIQrGdzqlsluplUxAe7kAkedIHgHQQEtY66TY77cVgMUot6jIEzH7iH7Gg9nXYzK9S-OnNI7do1oaP6ffk_lonAzfksFrevOyiK7n0_vkc7SIbpOHSfI-3CRrgTzu-8V_LZD63m69sm9UD92DSrlqaM6E4QnNqabKN4PA8TwfbGSSoydszkxwJEotMRAiQPQVQwFcSaW0MFUWUQBaINursxcyDGTYbHS6570wK2zo1qX6exJNAJFxdMXpVjdsnrUz8rTXPpG9q4bNuek4tm0Bc5iwWDZLxxz6CyzhbTc |
| ClassificationCodes | P228 |
| ContentType | Journal Article |
| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
| Copyright_xml | – notice: Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
| DBID | 2RA 92L CQIGP ~WA 2B. 4A8 92I 93N PSX TCJ |
| DOI | 10.11947/j.AGCS.2016.20160117 |
| DatabaseName | 中文科技期刊数据库 中文科技期刊数据库-CALIS站点 中文科技期刊数据库-7.0平台 中文科技期刊数据库- 镜像站点 Wanfang Data Journals - Hong Kong WANFANG Data Centre Wanfang Data Journals 万方数据期刊 - 香港版 China Online Journals (COJ) China Online Journals (COJ) |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Astronomy & Astrophysics |
| DocumentTitle_FL | An Adaptive Filtering Method Based on Crowdsourced Big Trace Data |
| EndPage | 1463 |
| ExternalDocumentID | chxb201612009 67728866504849544950484948 |
| GrantInformation_xml | – fundername: 国家自然科学基金(41671442,41571430,41271442)Foundation support:The National Natural Science Foundation of China funderid: (.41671442,41571430,41271442) |
| GroupedDBID | -01 2B. 2C. 2RA 5VS 5XA 5XB 7X2 92E 92I 92L ACGFS AFKRA ALMA_UNASSIGNED_HOLDINGS ATCPS BBNVY BENPR BHPHI BKSAR CCEZO CCPQU CCVFK CQIGP CW9 GROUPED_DOAJ HCIFZ IPNFZ M0K M7P OK1 P2P PATMY PCBAR PIMPY PYCSY RIG TCJ TGP U1G U5K ~WA 4A8 93N ABJNI AEUYN PHGZM PHGZT PMFND PSX |
| ID | FETCH-LOGICAL-c749-d9c73c3be2ff8dde0614a71d9674208a1aca1f99f11eb41907babbc92ba1a3003 |
| ISSN | 1001-1595 |
| IngestDate | Thu May 29 04:11:08 EDT 2025 Wed Feb 14 09:58:09 EST 2024 |
| IsPeerReviewed | false |
| IsScholarly | true |
| Issue | 12 |
| Keywords | 众源轨迹数据 data filtering trajectories partition similarity model 轨迹分割 数据滤选 big data 相似度模型 crowdsourced trace 大数据 |
| Language | Chinese |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c749-d9c73c3be2ff8dde0614a71d9674208a1aca1f99f11eb41907babbc92ba1a3003 |
| Notes | 11-2089/P TANG Luliang;YANG Xue;NIU Le;CHANG Le;LI Qingquan;State Key Laboratory of Information Engineering in Surveying,Mapping,and Remote Sensing,Wuhan University;Shenzhen Key Laboratory of Spatial Smart Sensing and Services,College of Civil Engineering,Shenzhen University |
| PageCount | 9 |
| ParticipantIDs | wanfang_journals_chxb201612009 chongqing_primary_67728866504849544950484948 |
| PublicationCentury | 2000 |
| PublicationDate | 2016 |
| PublicationDateYYYYMMDD | 2016-01-01 |
| PublicationDate_xml | – year: 2016 text: 2016 |
| PublicationDecade | 2010 |
| PublicationTitle | 测绘学报 |
| PublicationTitleAlternate | Acta Geodaetica et Cartographica Sinica |
| PublicationTitle_FL | Acta Geodaetica et Cartographica Sinica |
| PublicationYear | 2016 |
| Publisher | 深圳大学 土木工程学院 空间信息智能感知与服务深圳市重点实验室，广东 深圳 518060 武汉大学测绘遥感信息工程国家重点实验室,湖北 武汉,430079%武汉大学测绘遥感信息工程国家重点实验室，湖北 武汉 430079 |
| Publisher_xml | – name: 武汉大学测绘遥感信息工程国家重点实验室,湖北 武汉,430079%武汉大学测绘遥感信息工程国家重点实验室，湖北 武汉 430079 – name: 深圳大学 土木工程学院 空间信息智能感知与服务深圳市重点实验室，广东 深圳 518060 |
| SSID | ssib005437539 ssib038074662 ssib051373695 ssib002263888 ssib000862384 ssj0058465 |
| Score | 2.071463 |
| Snippet | ... P228; 基于同步高低精度GPS轨迹数据的空间特征和GPS误差分布原理，提出了一种众源GPS车载轨迹大数据自适应分割-滤选模型。该模型首先通过角度、距离约束将完整的车载 GPS 轨迹数据进行分割，以轨迹分割段作为基本滤选单元；然后通过对比轨迹分割段内 GPS... |
| SourceID | wanfang chongqing |
| SourceType | Aggregation Database Publisher |
| StartPage | 1455 |
| SubjectTerms | 众源轨迹数据;轨迹分割;相似度模型;数据滤选;大数据 |
| Title | 一种众源车载GPS轨迹大数据自适应滤选方法 |
| URI | http://lib.cqvip.com/qk/90069X/201612/67728866504849544950484948.html https://d.wanfangdata.com.cn/periodical/chxb201612009 |
| Volume | 45 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnR3LbhMx0ArlwgXxVMujygFzCYF9eNf20dtsW4FAoAapt2i92TSXJkBSCXqKuCAOlThQ-IGKIg4IiQstRJz4k3ZJ_4IZ7ybdQ5AoUmtN_JgZ73g9Y69nTMgNbVvoruhXPQZvE0ssqyo1S6o8drknnWbUTNBR-P4Df_kxu7vqrZZKvwqnljb6-na8OdWv5H-kCnkgV_SSPYFkJ0ghA2CQL6QgYUj_ScY0ZDQQeFgh5FRxKmomZ4FKTkOfBopKKBI0qFHl50BQW3q4Ms4UBlikgaShRxVDJNBQejSwEACEKsQ6AvArGkqkJRysjMiZoRJgw7xImua-QQipS7O7Lcfmr8n0qAiQYWgohaGbsQfkFFXeeAhgCVCQpnNAE3EzJKvCiqGS8S-pBAZUxdQyP7AWAFbFsCnwr5BlGorQcAL98nI-sxuGxvsfmWNmPlnjcTAwx7ziOHUKszEGYS9odlAK7nStIRk3akMtLazgcT_fJBgu71hNTg4v-rAgERgmECY_WF4y-DcQE6fIaQcK8SKNe4-KVi7YmKJoRcGkV4gSB68JLBonViVeAcD84yiOnu1y15eTVR2ajJ75iJ93P3dMw17cmdYHDBvS7nbWnoIxZHzTOq2os1Ywo-rnyNl8_VNW2WA-T0qb7QtkVvXwi0x3_UX5ZtnA2YZb7yKRB98Gv3e3Dn68T_ffjIYfRsMhjN_R8OPo597hzm66_SXd-jx69elo8PJw_236fedo8Dp9t5d-3b5E6othfWG5ml_3UY05k9WmjLkbuzpxWi0BShe3KiJuN6XP8QhIZEdxZLekbNl2ohnYsVxHWsfS0VDkgnK6TGY63U4yS8q21AlPmo7mImJxZGkZxRZoUt9rgs5hzhy5NXkgjSdZVJfG38U6R-bzZ9bIX_5eI24_1_h8bfy6eOVk-K6SM9g028i7Rmb6zzaS62Da9vW8GTh_AFVeeps |
| linkProvider | Colorado Alliance of Research Libraries |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=%E4%B8%80%E7%A7%8D%E4%BC%97%E6%BA%90%E8%BD%A6%E8%BD%BDGPS%E8%BD%A8%E8%BF%B9%E5%A4%A7%E6%95%B0%E6%8D%AE%E8%87%AA%E9%80%82%E5%BA%94%E6%BB%A4%E9%80%89%E6%96%B9%E6%B3%95&rft.jtitle=%E6%B5%8B%E7%BB%98%E5%AD%A6%E6%8A%A5&rft.au=%E5%94%90%E7%82%89%E4%BA%AE+%E6%9D%A8%E9%9B%AA+%E7%89%9B%E4%B9%90+%E5%B8%B8%E4%B9%90+%E6%9D%8E%E6%B8%85%E6%B3%89&rft.date=2016&rft.issn=1001-1595&rft.issue=12&rft.spage=1455&rft.epage=1463&rft_id=info:doi/10.11947%2Fj.AGCS.2016.20160117&rft.externalDocID=67728866504849544950484948 |
| thumbnail_s | http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=http%3A%2F%2Fimage.cqvip.com%2Fvip1000%2Fqk%2F90069X%2F90069X.jpg http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=http%3A%2F%2Fwww.wanfangdata.com.cn%2Fimages%2FPeriodicalImages%2Fchxb%2Fchxb.jpg |