摘要
针对当前老龄化社会所带来的养老设施供给不足与供给不均衡问题,以滨城区为研究区,以精细化人口数据、养老设施数据为基础,分析格网单元的老龄化程度和养老服务压力,以POI数据与随机森林算法分别对主城区和乡镇区域构建选址模型,并进行空间选址预测;顾及老龄化程度和养老服务压力对选址结果进行等级划分。结果表明,主城区选址模型的正确率为89.83%,乡镇的选址模型正确率为90.72%;主导主城区和乡镇选址的指标不同,老年人口是影响主城区选址的主要因素,基础设施是影响乡镇选址的主要因素。在初步预测结果的基础上,将选址结果划分为一级需求适宜区、二级需求适宜区,为养老服务设施选址决策提供科学依据。
In view of the problem of insufficient supply and unbalanced supply of elderly care facilities brought about by the current aging society, this paper takes Bincheng District as the research area and analyses the degree of aging and elderly care facilities in grid cells, used refined population data and elderly care facility data. And then uses POI date and machine learning algorithms to build the location models for the main urban and township areas. After that, the site selection results are graded according to the aging degree and the pressure of elder care services. The results show that the correct rate of the main urban site selection model is 89.83%,and the correct rate of the township site selection model is 90.72%;the main urban and township site selection indicators are different.The elderly population is the main factor affecting the main urban site selection.Facilities are the main factor affecting the site selection of towns and villages.Based on the preliminary prediction results, the site selection results are divided into first-level demand suitable areas and second-level demand suitable areas to provide a scientific basis for decision-making on the location of elderly service facilities.
作者
刘新
王新建
吴政
戴昭鑫
孙哲
LIU Xin;WANG Xinjian;WU Zheng;DAI Zhaoxin;SUN Zhe(College of Geodesy and Geomatics,Shandong University of Science and Technology,Qingdao 266590,China;Key Laboratory of Geomatics and Digital Technology of Shandong Province,Shandong University of Science and Technology,Qingdao 266590,China;Chinese Academy of Surveying and Mapping,Beijing 100089,China)
出处
《测绘工程》
2023年第1期49-55,共7页
Engineering of Surveying and Mapping
基金
国家重点研发计划(2018YFB2100704)
国家自然科学基金资助项目(41871375
41907389)。
关键词
人口老龄化
选址
随机森林
适宜性
养老服务压力
population aging
site selection
random forest
suitability
pressure on elderly care services
