Browse > Article
http://dx.doi.org/10.17820/eri.2020.7.3.171

Estimating the Method of the Number of Visitors of Water-friendly Park Using GPS Location Information  

Kim, Seong-Jun (R&D Division, Korea Institute of Hydrological Survey)
Kim, Tae-Jeong (R&D Division, Korea Institute of Hydrological Survey)
Kim, Chang-Sung (R&D Division, Korea Institute of Hydrological Survey)
Publication Information
Ecology and Resilient Infrastructure / v.7, no.3, 2020 , pp. 171-180 More about this Journal
Abstract
With the increase in industrialization and urbanization, scarcity of space for leisure life has become an important issue. Opportunities such as natural scenery and ecological experiences provided by waterfront spaces around streams are fundamental factors in the development of the community and creation of a hydrophilic park. In the past, on-site surveys have been conducted using human resources to quantify the number of river visitors, but the accuracy of the results was not sufficient owing to limitations in expenses, manpower, space, and time. In this study, to overcome this problem, we estimated the number of visitors using the location information related to hydrophilic parks. The study areas were Samrak Ecological Park and Daejeo Ecological Park located downstream of the Nakdong River. We compared and analyzed the pattern of the visitors by using the large communication data and the visiting pattern based on GPS location information. The GPS location information is based on Google Popular Times and Kakao visitor data. When the GPS location data were used, the pattern for weekday and weekend visitors was clearer than when the large communication data were used. Therefore, it is expected to be similar to the result of GPS location information if the number of visitors is extracted under the condition of precision of pCELL size and residence time of 30 minutes or more when using future communication big data. In addition, if revisions such as the Personal Information Protection Act are made to extract more accurate data, by estimating the number of visitors based on GPS data, more accurate indicators of the number of visitors can be derived.
Keywords
Google popular times; Location information; Mobile big data; Visitors; Water-friendly park;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
연도 인용수 순위
1 De Jonge, E., van Pelt, M., and Roos, M. 2012. Time patterns, geospatial clustering and mobility statistics based on mobile phone network data. In, Proceeding of the Federal Committee on Statistical Methodology Research Conference, January 10-12. Washington D.C.: Washington Convention Center.
2 Deville, P., Linard, C., Martin, S., Gilbert, M., Stevens, F.R., Gaughan, A.E., Blondela, V.D., and Tatem, A.J. 2014. Dynamic population mapping using mobile phone data. In, Proceeding of the National Academy of Sciences, 111. 45: 15888-15893.   DOI
3 Dixon, J., Elders, I., and Bell, K. 2018. Electric vehicle destination charging demand characterizations at popular amenities.
4 Douglass, R.W., Meyer, D.A., Ram, M., Rideout, D., and Song, D. 2015. High resolution population estimates from telecommunications data. EPJ Data Science, 4. 1: 1-13.   DOI
5 Kim, J.E., Park, C., Kim, A.Y., and Kim, H.G. 2019a. Analysis of behavioral characteristics by park types displayed in 3rd generation SNS. Journal of the Korean Institute of Landscape Architecture 47(2): 49-58. (in Korean)
6 Kim, J.H., Ko, Y.S., Kim, J.K., and Kim, D.H. 2014. The application of smart cell in space policy. Sejong: Korea Research Institute for Human Settlements. (in Korean)
7 Kim, S.J., Kim, C.S., and Kim, J.S. 2019b. Estimating visitors on water-friendly space in the river using mobile big data and UAV. Ecology and Resilient Infrastructure 6(4): 250-257. (in Korean)   DOI
8 Kim, T.J., Lee, D.R., Jang, S.M., and Kwon, H.H. 2017. Generation of radar rainfall data for hydrological and meteorological application (II) : radar rainfall ensemble. Journal of Korea Water Resources Association 50(1):17-28. (in Korean)   DOI
9 Lee, J.S. and Lee, S.E. 2019. A study on classification and characterization of water-friendly space for the smart river space management using the mobile big data. Korea Research Institute for Human Settlements 9: 69-82. (in Korean)
10 Lee, J.S., Lee, S.E., and Choi, J.Y. 2019. Using the mobile big data for the smart river space management: data validation and water-friendly space indicators. Korea Research Institute for Human Settlements 6: 3-18. (in Korean)
11 MOLIT. 2016. Study on river maintenance evaluation and improvement plan. Ministry of Land and Infrastructure and Transport, Sejong Korea.
12 MOLIT. 2017. A study on the utilization of the 4 rivers waterfront using mobile big data. Ministry of Land and Infrastructure and Transport, Sejong Korea.
13 KRIHS. 2018. using the mobile big data for the smart river space management. Korea Research Institute for Human Settlements, Sejong, Korea.
14 NARS. 2017. Management status and improvement tasks of waterfront park. NARS Field Survey Report No.55. National Assembly Research Service, Seoul, Korea.