海岸线变化的单链曼延编号快速匹配方法

doi:10.11947/j.AGCS.2022.20210291

测绘学报 ›› 2022, Vol. 51 ›› Issue (8): 1817-1825.doi: 10.11947/j.AGCS.2022.20210291

海岸线变化的单链曼延编号快速匹配方法

成思远^1,2, 张英^1,2, 翟亮^1,2

1. 中国测绘科学研究院自然资源调查监测研究中心, 北京 100036;
2. 自然资源部测绘科学与地球空间信息技术重点实验室, 北京 100036

收稿日期:2021-05-21 修回日期:2021-12-07 发布日期:2022-09-03
通讯作者: 翟亮 E-mail:zhailiang@casm.ac.cn
作者简介:成思远(1997-),男,硕士生,研究方向为典型地理要素变化检测。E-mail:chengsy422@163.com
基金资助:
2019年度自然资源部高层次科技创新人才培养工程杰出青年人才资助项目(12110600000018003908);中国测绘科学研究院基本科研业务费项目(AR2017;AR2001;AR2112)

A fast matching method of coastline changes using single-chain numbering

CHENG Siyuan^1,2, ZHANG Ying^1,2, ZHAI Liang^1,2

1. Research Center for Natural Resources Surveying and Monitoring, Chinese Academy of Surveying and Mapping, Beijing 100036, China;
2. Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of MNR, Beijing 100036, China

Received:2021-05-21 Revised:2021-12-07 Published:2022-09-03
Supported by:
The Project for High-Level-Innovation Talents in Science and Technology,Ministry of Natural Resources (No.12110600000018003908);The Research Projects of the Chinese Academy of Surveying and Mapping (Nos.AR2017;AR2001;AR2112)

摘要/Abstract

摘要： 受海岸带区域自然环境变迁与人类开发活动的综合影响,海岸线不断发生剧烈变化。发现海岸线变化并将变化前后的岸段进行匹配,对分析海岸线变化至关重要。针对传统空间分析工具难以直接确定不同时相变化岸段的对应关系的问题,本文引入单链曼延编号的思想对海岸线变化进行快速匹配,并按照"一对一"和"多对多"两种变化岸段匹配关系提出了位置变迁、类型转移、消失及新增等海岸线变化类型的判断公式,设计并实现了结合单链曼延编号的海岸线变化匹配与信息存储方法。试验证明,该方法能快速准确地实现海岸线变化匹配,并能很好地解决多对多变化岸段匹配的问题。

关键词: 单链蔓延编号, 海岸线变化, 匹配方法, 变化类型

Abstract: Affected by natural environment changes and human development activities in the coastal zone,coastline continues to change dramatically.Detecting coastline changes and matching the coastline change segments before and after changing are critical for analyzing coastline changes.As the traditional tools of spatial analysis lack of direct and effective matching function,this article introduced the single-chain numbering idea to match the coastline change segments quickly.The matching relationships of the coastline change segments were grouped into "one-to-one" and "multi-to-multi" .Besides,we also put forward a set of formula for determining the coastline change types such as position change,type change,disappearance and appearance.The matching and recording method of the coastline changes based on single-chain numbering has been designed and packed using python language.Experiments showed that the method proposed realized coastline changes matching quickly and accurately,which has solved the problem of matching the multi-to-multi coastline change segments.

Key words: single-chain numbering, coastline changes, matching method, change types

中图分类号:

P208

成思远, 张英, 翟亮. 海岸线变化的单链曼延编号快速匹配方法[J]. 测绘学报, 2022, 51(8): 1817-1825.

CHENG Siyuan, ZHANG Ying, ZHAI Liang. A fast matching method of coastline changes using single-chain numbering[J]. Acta Geodaetica et Cartographica Sinica, 2022, 51(8): 1817-1825.

参考文献

[1] MUJABAR P S, CHANDRASEKAR N. Shoreline change analysis along the coast between Kanyakumari and Tuticorin of India using remote sensing and GIS[J]. Arabian Journal of Geosciences, 2013, 6(3):647-664.
[2] 许宁,高志强,宁吉才.基于分形维数的环渤海地区海岸线变迁及成因分析[J].海洋学研究, 2016, 34(1):45-51. XU Ning, GAO Zhiqiang, NING Jicai. Spatial-temporal variations of coastlines in Bohai Rim based on fractal dimension and their causes analysis[J]. Journal of Marine Sciences, 2016, 34(1):45-51.
[3] 毋亭,侯西勇.海岸线变化研究综述[J].生态学报, 2016, 36(4):1170-1182. WU Ting, HOU Xiyong. Review of research on coastline changes[J]. Acta Ecologica Sinica, 2016, 36(4):1170-1182.
[4] BOAK E H, TURNER I L.Shoreline definition and detection:a review[J]. Journal of Coastal Research, 2005, 21(21):688-703.
[5] 杨继文,刘欣岳,邓蜀江.基于多时相遥感影像的海岸线变化监测研究[J].测绘与空间地理信息, 2020, 43(3):107-108, 112. YANG Jiwen, LIU Xinyue, DENG Shujiang. Based on multi-temporal remote sensing images coastline change monitoring[J]. Geomatics&Spatial Information Technology, 2020, 43(3):107-108, 112.
[6] 张冲,孙钦帮,乌立国,等.基于矢量数据的海岸线分形计算方法探讨及实例应用[J].测绘与空间地理信息, 2019, 42(7):36-37, 45. ZHANG Chong, SUN Qinbang, WU Liguo, et al. Computation method and application for coastline based on fractal with vector data[J]. Geomatics&Spatial Information Technology, 2019, 42(7):36-37, 45.
[7] 杜佳威,武芳,李靖涵,等.一种河口湾海岸线渐进化简方法[J].测绘学报, 2018, 47(4):547-556. DOI:10.11947/j.AGCS.2018.20170440. DU Jiawei, WU Fang, LI Jinghan, et al. A progressive simplification method for the estuary coastline[J]. Acta Geodaetica et Cartographica Sinica, 2018, 47(4):547-556. DOI:10.11947/j.AGCS.2018.20170440.
[8] 孙晓宇,吕婷婷,高义,等. 2000-2010年渤海湾岸线变迁及驱动力分析[J].资源科学, 2014, 36(2):413-419. SUN Xiaoyu, LV Tingting, GAO Yi, et al. Driving force analysis of Bohai Bay coastline change from 2000 to 2010[J]. Resources Science, 2014, 36(2):413-419.
[9] ROMINE B M, FLETCHER C H. A summary of historical shoreline changes on beaches of Kauai, Oahu, and Maui, Hawaii[J]. Journal of Coastal Research, 2013, 29(3):605-614.
[10] 索安宁,曹可,马红伟,等.海岸线分类体系探讨[J].地理科学, 2015, 35(7):933-937. SUO Anning, CAO Ke, MA Hongwei, et al. Discussion on classification system of coastline[J]. Scientia Geographica Sinica, 2015, 35(7):933-937.
[11] 张立华,唐露露,贾帅东,等.多条海岸线协同化简的层次化三角网分区法[J].测绘学报, 2019, 48(4):520-531. DOI:10.11947/j.AGCS.2019.20180382. ZHANG Lihua, TANG Lulu, JIA Shuaidong, et al. A collaborative simplification method for multiple coastlines based on the hierarchical triangulation network partition[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(4):520-531. DOI:10.11947/j.AGCS.2019.20180382.
[12] 李成名,郭沛沛,殷勇,等.一种顾及空间关系约束的线化简算法[J].测绘学报, 2017, 46(4):498-506. DOI:10.11947/j.AGCS.2017.20160546. LI Chengming, GUO Peipei, YIN Yong, et al. A line simplification algorithm considering spatial relations between two lines[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(4):498-506. DOI:10.11947/j.AGCS.2017.20160546.
[13] ZHANG Lihua, TANG Lulu, JIA Shuaidong, et al. A collaborative simplification method for multiple coastlines based on the hierarchical triangulation network partition[J]. Journal of Geodesy and Geoinformation Science, 2020, 3(2):93-104.
[14] 刘闯.大比例尺城市道路和居民地数据联动匹配方法研究[D].郑州:信息工程大学, 2017. LIU Chuang. Research on linkage matching methods for binded big-scale road and habitation[D]. Zhengzhou:Information Engineering University, 2017.
[15] MUSTIōRE S, DEVOGELE T. Matching networks with different levels of detail[J]. GeoInformatica, 2008, 12(4):435-453.
[16] 赵东保,盛业华.全局寻优的矢量道路网自动匹配方法研究[J].测绘学报, 2010, 39(4):416-421. ZHAO Dongbao, SHENG Yehua. Research on automatic matching of vector road networks based on global optimization[J]. Acta Geodaetica et Cartographica Sinica, 2010, 39(4):416-421.
[17] HUANG Bohua, ZHONG Wei, ZHAl Renjian, et al. Hierarchical area partitioning method of urban road networks matching[J]. Journal of Geodesy and Geoinformation Science, 2019, 2(3):55-67.
[18] 田文文,朱欣焰,呙维.一种VGI矢量数据增量变化发现的多层次蔓延匹配算法[J].武汉大学学报(信息科学版), 2014, 39(8):963-967,973. TIAN Wenwen, ZHU Xinyan, GUO Wei. A VGI vector road data increment distinguishing research based on multilevel spreading algorithm[J]. Geomatics and Information Science of Wuhan University, 2014, 39(8):963-967,973.
[19] ABDOLMAJIDI E, MANSOURIAN A, WILL J, et al. Matching authority and VGI road networks using an extended node-based matching algorithm[J]. Geo-Spatial Information Science, 2015, 18(2-3):65-80.
[20] 邵世维,刘辉,肖立霞,等.一种基于Fréchet距离的复杂线状要素匹配方法[J].武汉大学学报(信息科学版), 2018, 43(4):516-521. SHAO Shiwei, LIU Hui, XIAO Lixia, et al. A complex linear feature of Fréchet distance matching method[J]. Geomatics and Information Science of Wuhan University, 2018, 43(4):516-521.
[21] 刘闯,钱海忠,王骁,等.顾及上下级空间关系相似性的道路网联动匹配方法[J].测绘学报, 2016, 45(11):1371-1383. DOI:10.11947/j.AGCS.2016.20160062. LIU Chuang, QIAN Haizhong, WANG Xiao, et al. A linkage matching method for road networks considering the similarity of upper and lower spatial relation[J]. Acta Geodaetica et Cartographica Sinica, 2016, 45(11):1371-1383. DOI:10.11947/j.AGCS.2016.20160062.
[22] 罗国玮,张新长,齐立新.顾及地理要素变化过程的数据增量更新方法[J].中山大学学报(自然科学版), 2014, 53(4):131-135,141. LUO Guowei, ZHANG Xinchang, QI Lixin. A incremental updating method of spatial data considering the geographic features change process[J]. Acta Scientiarum Naturalium Universitatis Sunyatseni, 2014, 53(4):131-135,141.
[23] EFSTATHIADES C, EFENTAKIS A, PFOSER D. Efficient processing of relevant nearest-neighbor queries[J]. ACM Transactions on Spatial Algorithms and Systems, 2016, 2(3):1-28.
[24] 罗国玮,张新长,齐立新,等.矢量数据变化对象的快速定位与最优组合匹配方法[J].测绘学报, 2014, 43(12):1285-1292. LUO Guowei, ZHANG Xinchang, QI Lixin, et al. The fast positioning and optimal combination method of change vector object[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(12):1285-1292.
[25] 刘雄,李宇,陈刚. Arcpy支持下的线要素几何自动接边与属性检查[J].测绘通报, 2016(8):114-117. LIU Xiong, LI Yu, CHEN Gang. Automatic edge matching and attribute checking of line features based on Arcpy[J]. Bulletin of Surveying and Mapping, 2016(8):114-117.
[26] 蔡艳辉,程鹏飞,张莉,等.测绘地理信息产品抽样检验的两类错误概率[J].测绘学报, 2019, 48(8):954-959. DOI:10.11947/j.AGCS.2019.20180108. CAI Yanhui, CHENG Pengfei, ZHANG Li, et al. Probabilities of two types of errors in sampling inspection for surveying and mapping products[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(8):954-959. DOI:10.11947/j.AGCS.2019.20180108.

海岸线变化的单链曼延编号快速匹配方法

A fast matching method of coastline changes using single-chain numbering

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