结合多源数据的第二产业时空变化发展研究  

Research on the temporal change and development of the secondary industrybased on multi-source data

作　　者：袁德宝[1] 吴雨阳 郭伟 潘星 YUAN Debao;WU Yuyang;GUO Wei;PAN Xing(School of Earth Science and Surveying Engineering,China University of Mining and Technology(Beijing),Haidian District,Beijing 100083,China;Surveying and Mapping Technology Service Center of Sichuan Bureau of Surveying and Mapping and Geographic Information,Chengdu 610093,China)

机构地区：[1]中国矿业大学(北京)地球科学与测绘工程学院,北京100083 [2]四川测绘地理信息局测绘技术服务中心,四川成都610093

出　　处：《测绘通报》2024年第9期112-116,共5页Bulletin of Surveying and Mapping

基　　金：国家自然科学基金(52174160)。

摘　　要：针对夜间灯光数据不能较好地解释第二产业空间布局的问题,本文提出了一种适合第二产业增加值空间化的新方法。该方法将筛选的POI数据与地表温度数据相结合,构建第二产业地表温度POI指数(STPI指数),并与农村居民点的夜间灯光数据耦合建模,以淮海经济区核心城市群为研究区开展研究。结果表明,相比于耦合土地利用数据与夜间灯光遥感数据方法,本文提出的第二产业空间化模型在2014、2016、2018、2020年各个年份的拟合优度(R 2分别为0.926、0.882、0.907、0.896)均优于前者(R 2分别为0.859、0.805、0.880、0.849),每年的平均相对误差均低于前者,平均值维持在10%左右。并以徐州市辖区为例,局部对比两种方法的第二产业空间化结果,本文方法可以显著提高第二产业增加值建模精度与空间化效果,其空间分布与实际更为吻合.本文结果可为有关部门制订区域经济发展规划提供一定的参考。In response to the challenge of inadequately explaining the spatial layout of the secondary industry using nighttime light data,this paper proposes a novel method suitable for spatializing the added value of the secondary industry.The approach involves combining selected points of interest(POI)data with land surface temperature data to construct the secondary industry surface temperature-POI index(STPI Index).This index is then coupled with nighttime light data from rural residential areas,and the study is conducted in the core urban cluster of the Huaihai economic zone.Results show that,compared to methods coupling land use data with nighttime light remote sensing data,the proposed spatialization model for the secondary industry consistently demonstrates superior goodness of fit in the years 2014,2016,2018,and 2020(0.926,0.882,0.907,0.896,respectively)compared to the former(0.859,0.805,0.880,0.849,respectively).The average relative error each year is lower than the former,maintaining around 10%.Using Xuzhou city as an example,a local comparison of the spatialized results for the added value of the secondary industry reveals that the proposed method significantly enhances modeling accuracy and spatialization effectiveness.The spatial distribution pattern is more aligned with reality.The results of this study can provide valuable references for relevant departments in formulating regional economic development plans.

关 键 词：第二产业空间化 夜间灯光遥感 POI数据 地表温度数据 STPI指数 

分 类 号：P208[天文地球—地图制图学与地理信息工程]