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利用高分影像和珞珈一号数据进行住房空置率高精度空间估算 被引量:3

High precision space estimation of housing vacancy rate using high resolution image and Luojia-1
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摘要 本文主要利用珞珈一号夜间灯光数据和高分遥感影像数据,提出了一种对研究区按建成区高层区、建成区低层区和非建成区住房进行空置率分区块估算的方法,采用夜晚实地记录的方法对估算结果进行精度检验,并通过LISA聚集图分析其空间聚集情况。表明结果:①研究区整体住房空置率为17.88%,均方根误差为0.14,其中非建成区的住房空置率整体上要高于建成区,而满置率却低于建成区;②研究区住房空置率呈高高集聚和低低集聚两种空间集聚特征,为进一步大范围了解农村地区住房情况及整体的空间分布规律提供了参考。 To estimate the house vacancy rate,this paper proposes a method that divides the study area into three parts: high-rise area in the built-up area,low-rise area in the built-up area and non-built-up area. In this method,the accuracy of the estimated results is tested by"night field record",and the local indicators of spatial association( LISA) is used to analyze its spatial aggregation.It can be found from the results that,① The overall house vacancy rates in the study area are 17.88%.The root-mean-square error is 0.14. The house vacancy rates in non-built-up areas are higher than that in built-up areas,while the full occupancy rates are lower than that in built-up areas.② The house vacancy rates in the study area present two spatial agglomeration characteristics: H-H agglomeration and L-L agglomeration. It provides a reference for further information about the vacancy rates of houses in rural areas and the spatial distribution regularity of house vacancy.
作者 张栋 李德平 周亮 黄金侠 高航 王嘉丞 马宇 ZHANG Dong;LI Deping;ZHOU Liang;HUANG Jinxia;GAO Hang;WANG Jiacheng;MA Yu(College of Resources and Environmental Science,Hunan Normal University,Changsha 410081,China;Key Laboratory of Geospatial Big Data Mining and Application,Changsha 410081,China)
出处 《测绘通报》 CSCD 北大核心 2021年第1期41-46,52,共7页 Bulletin of Surveying and Mapping
基金 湖南省教育厅科学研究重点项目(18A014)。
关键词 住房空置率 建成区和非建成区 珞珈一号夜间灯光数据 LISA自相关分析 house vacancy rate the built-up area and non-built-up area Luojia-1 night light date LISA
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