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Spatial Dataset of 312 Historical and Cultural Towns and Scenic Spots in China


YU Liang1QIU Yuchen1TANG Mingjie1HAN Sen1FU Meng1LIU Zhitao1
1 Sino-Portugal Joint Laboratory in Science of Cultural Heritage Conservation Supported by The Belt and Road Initiative,School of Architecture,Soochow University,Suzhou 215123,China

DOI:10.3974/geodb.2022.03.04.V1

Published:Mar. 2022

Visitors:9566       Data Files Downloaded:1239      
Data Downloaded:47.00 MB      Citations:

Key Words:

Historical and Cultural Towns,spatial position,town locations,scenic spots

Abstract:

Announced by the Ministry of Housing and Urban-Rural Development of P. R. China and the National Cultural Heritage Administration, seven batches of 312 historical and cultural towns in China were recorded from 2003 to 2019. These towns distributed in 31 provinces, autonomous regions and municipalities. The historical and cultural values of famous towns are mainly preserved in the scenic spots of towns. Referring to the maps and images of Baidu Map and Google Earth, the authors identified and located the locations of famous towns and their main scenic spots, and obtained the spatial dataset of 312 historical and cultural towns and scenic spots in China. The dataset was archived in .shp and .kmz data formats with data size of 1.48 MB in 16 data files (Compressed to 114 KB in three files).Browse

Foundation Item:

Data Citation:

YU Liang, QIU Yuchen, TANG Mingjie, HAN Sen, FU Meng, LIU Zhitao. Spatial Dataset of 312 Historical and Cultural Towns and Scenic Spots in China[J/DB/OL]. Digital Journal of Global Change Data Repository, 2022. https://doi.org/10.3974/geodb.2022.03.04.V1.

YU Liang, QIU Yuchen, TANG Mingjie, et al. The spatial distribution dataset of 312 renowned historical and cultural towns and scenic spots in China [J]. Journal of Global Change Data & Discovery, 2022, 6(3): 440-447.

References:

[1] Yu, L., Liu, J., Cao, Q. Y., et al. The spatial distribution dataset of 2555 Chinese traditional villages [J/DB/OL]. Digital Journal of Global Change Data Repository, 2018. https://doi.org/10.3974/geodb.2018.04.06.V1.
     [2] He, M. L., Ding, X. H., Yu, K. X. Spatial distribution characteristics of place-names in Zhuji from the perspective of geomorphology [J]. Science of Surveying and Mapping, 2020, 45(11): 147-153.
     [3] Chen, Z., Xu, Y., He, F., et al. Study on the Spatial Distribution of National Historic Villiage and Towns [J]. Architectural Journal, 2013(S1): 14-17.
     [4] Hu, H. S., Wang, L. Research on spatial configuration of historical and cultural towns (villages) in China [J]. Geography and Geo-Information Science, 2008(3): 109-112.
     [5] Zhao, Y., Zhang, J., Qin, Z. Progress in research on the historic cultural towns & villages in China [J]. Urban Planning Forum, 2005(2): 59-64.
     [6] Si, L. F., Wu, C. Map making with RS image: research and application [J]. Bulletin of Surveying and Mapping, 2009(3): 49-51, 58.
     [7] Zou, D., Sun, D. D. Application of remote sensing cartography in map making [J]. Technology Innovation and Application, 2020(3): 171-172.
     [8] Zhao, Y. Research on digital protection of ancient villages in Nanxi River Basin of Wenzhou based on HD image technology [J]. Social Sciences Review, 2013, 28(1): 240-241.
     [9] Bai, T. T. Research on geospatial data acquisition method based on Excel [J]. Journal of Green Science and Technology, 2018(18): 182-183.
     [10] GOOGLE EARTH. http://earth.google.com/ or www.google Earth.com.
     [11] BAIDU MAP. https://map.baidu.com/@13211798.77,2842902.63,12z.
     [12] Ministry of Housing and Urban-Rural Development of People’s Republic of China. https://www.mohurd.gov.cn/.
     [13] National Cultural Heritage Administration. http://www.ncha.gov.cn/col/col2266/index.html.
     [14] Ministry of Civil Affairs of the People's Republic of China. The Brochure of Administrative Divisions of Townships of the People's Republic of China 2018[M]. Beijing:China Society Press, 2018.
     [15] Jiangsu Government Affairs. http://kszzz.jszwfw.gov.cn/.
     [16] Lingshi People's Government. http://www.lingshi.gov.cn/.
     [17] Department of Housing and Urban-Rural Development of Ningxia Hui Autonomous Region. http://jst.nx.gov.cn/info/1077/30836.htm.
     [18] News Xinhua. http://www.xinhuanet.com/travel/2018-06/22/c_1123022492.htm.
     [19] HuaDu Net. https://www.lyhuadu.com/news/337.html.
     [20] Guying Town. http://newpaper.dahe.cn/hnrb/html/2016-11/21/content_95369.htm.
     [21] Wuzhen Travel Net. http://www.wuzhen.com.cn/web/origin?id=10.
     [22] Datong Travel Net. http://www.tlsdatong.com/.
     

Data Product:

ID Data Name Data Size Operation
0Datapaper_TownsScenicSpotsChina312.pdf717.00kbDownLoad
1 ScenicSpotsChina312.kmz 33.94KB
2 TownsChina312.kmz 34.03KB
3 TownsScenicSpotsChina312.rar 46.39KB
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