Journal of Geo-information Science >
Analysis of Spatiotemporal Characteristics and Spatial Patterns of Residents' Medical Treatment based on Algorithm of Trajectory Drift
Received date: 2020-09-03
Request revised date: 2020-12-24
Online published: 2021-08-25
Supported by
National Natural Science Foundation of China(41471333)
The Central Guided Local Development of Science and Technology Project(2017L3012)
Copyright
The spatial and temporal characteristics of residents' medical treatment reflect the service capacity and layout rationality of medical facilities. This study investigated the features and patterns of medical treatment using taxi trajectory data in Xiamen. We divided Xiamen Island into different research units based upon the central lines of roads. We presented a trajectory drift algorithm to extract the medical treatment OD data for tertiary hospitals. This algorithm deals with the positional error associated with trajectory data and can improve the extraction accuracy. Hospitalizing behavior was analyzed from the perspective of space and time. Finally, based on the residents' preference for hospitals, we discussed the spatial patterns of residents' medical treatment by K-means algorithm. The results show that: (1) Compared with traditional buffer analysis, the trajectory drift algorithm didn't require high positioning accuracy when extracting OD data for hospitals. OD data can be extracted more reasonably and completely only by shifting OD point's coordinates, with an accuracy increased by more than 30%. It was also applicable to all floating vehicle trajectory data; (2) The peak time of medical treatment occurred at 7 am and 2 pm, respectively. The number of medical visits was twice on weekends (including holidays) than working days. When the travel distance was greater than 1 km, the number of medical visits decreased with the increase of travel distance, following a Weibull function distribution; (3) Residents regarded the Zhongshan, the First Affiliated, and the Chinese Medicine Hospital as their first choice for medical treatment. There was a significant regional difference in choices of medical treatment, that is residents preferred nearby hospitals. The southwest of Xiamen Island had sufficient medical resources, and residents' average medical travel distance was less than 4 km. However, residents in northwest and southeast of Xiamen Island mostly had to travel about 10 km for medical treatment. The medical resources in these regions were relatively scarce and needed to be strengthened eagerly; (4) The service capacity of the nine tertiary hospitals in Xiamen Island was obviously different. The residents had a strong preference for the Zhongshan, the First Affiliated, and the Chinese Medicine hospitals, with evaluated preference values greater than 33%. The service scopes of these three hospitals basically covered the whole Xiamen Island, which indicated strong attraction and service capacity for the residents. The values of residents' preference for the other six hospitals ranged from 0 to 33%. These six hospitals mainly treated nearby residents, leading to weak attraction and service capacity. This study provides alternative methods to extract the spatiotemporal features of residents' medical treatment and supports the decision-making of optimizing the spatial configuration of medical facilities.
DING Wei , WU Qunyong . Analysis of Spatiotemporal Characteristics and Spatial Patterns of Residents' Medical Treatment based on Algorithm of Trajectory Drift[J]. Journal of Geo-information Science, 2021 , 23(6) : 979 -991 . DOI: 10.12082/dqxxkx.2021.200506
表1 轨迹数据样例 (2015年6月13日)Tab. 1 Sample of trajectory data (13 June 2015) |
车辆ID | 日期时间 | 经度/°E | 纬度/°N | 车速/(km/h) | 空重车状态 |
---|---|---|---|---|---|
1000 | 00:00:55 | 118.120 | 24.515 | 14.8 | 空 |
1000 | 00:01:55 | 118.119 | 24.512 | 38.9 | 重 |
1000 | 00:02:55 | 118.115 | 24.513 | 44.4 | 重 |
1000 | 00:03:55 | 118.115 | 24.511 | 38.9 | 重 |
1000 | 00:04:55 | 118.110 | 24.510 | 25.9 | 重 |
1000 | 00:05:55 | 118.104 | 24.508 | 50.2 | 重 |
1000 | 00:06:55 | 118.101 | 24.503 | 48.2 | 重 |
1000 | 00:07:55 | 118.101 | 24.503 | 48.2 | 重 |
1000 | 00:08:55 | 118.095 | 24.493 | 1.9 | 空 |
1000 | 00:09:55 | 118.090 | 24.492 | 51.9 | 空 |
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