基于NPP/VI RS夜间灯光和土地利用的大连市人口空间化研究
|
摘要
针对当前人口分布图绘制不够精确、分布状况偏离实际等问题,基于全国第二次土地利用调查数据和NPP/VIIRS夜间灯光数据,以大连市为例,结合该市128个典型采样点的实测人口数据,分别构建0. 5km×0. 5km栅格的人口空间化模型,以县(区)为验证单元,比较两种方法模拟人口分布的优缺点。结果显示,基于夜间灯光数据的人口分布在人口密集的城镇具有较高的显著性,结合土地利用数据模拟得到的乡村人口分布会更准确,两种数据与实际人口的相对误差分别为0. 14和0. 18,表明两种数据能较真实地预测出城市人口数量,为绘制高精度的人口空间化分布图提供了参考。
In view of the fact that the current population distribution map was not accurate enough and the distribution status deviated from reality,Dalian City was taken as an example to combine the measured population of 128 typical sampling points in Dalian,based on the second national land use survey data and NPP/VIIRS nighttime lighting data. Data,respectively,constructed a population spatialization model of 0. 5 km× 0. 5 km grid,and used the county( district) as a verification unit to compare the advantages and disadvantages of the two methods to simulate population distribution. The results showed that the population distribution was highly significant in densely populated towns,based on nighttime lighting data. The distribution of rural populations that were combined with land use data simulations was more accurate. The relative errors between the two data and the actual population were 0. 14 and 0. 18,indicating that the two data could predict the population of the city more realistically. This paper provided a reference for the development of high-precision population spatialization maps.
In view of the fact that the current population distribution map was not accurate enough and the distribution status deviated from reality,Dalian City was taken as an example to combine the measured population of 128 typical sampling points in Dalian,based on the second national land use survey data and NPP/VIIRS nighttime lighting data. Data,respectively,constructed a population spatialization model of 0. 5 km× 0. 5 km grid,and used the county( district) as a verification unit to compare the advantages and disadvantages of the two methods to simulate population distribution. The results showed that the population distribution was highly significant in densely populated towns,based on nighttime lighting data. The distribution of rural populations that were combined with land use data simulations was more accurate. The relative errors between the two data and the actual population were 0. 14 and 0. 18,indicating that the two data could predict the population of the city more realistically. This paper provided a reference for the development of high-precision population spatialization maps.
引文
[1]曹丽.中国人口分布及影响因素分析[D].吉林:东北亚研究院硕士学位论文,2012∶1-32.
[2]王雅雯,王利,郭峰.基于GIS的人口分布图的绘制研究——以辽阳市为例[J].测绘与空间地理信息,2008,31(2)∶97-101.
[3]陈楠.基于GIS的人口时空分布特征研究[D].青岛:山东科技大学硕士学位论文,2005∶1-146.
[4]王慧鹏.大连旅顺口区基准地形起伏度与人口分布的空间关联研究[D].大连:辽宁师范大学硕士学位论文,2014∶1-147.
[5]白平平.基于GIS的内蒙古人口分布特征和情景模拟[D].呼和浩特:内蒙古师范大学硕士学位论文,2012∶1-61.
[6]周自翔,李晶,任志远.基于GIS的关中—天水经济区地形起伏度与人口分布研究[J].地理科学,2012,32(8)∶951-957.
[7]杨眉,王世新,周艺,等. DMSP/OLS夜间灯光数据应用研究综述[J].遥感技术与应用,2011,26(1)∶45-51.
[8]曹丽琴,李平湘,张良培.基于DMSP/OLS夜间灯光数据的城市人口估算——以湖北省各县市为例[J].遥感信息,2009,(1)∶83-87.
[9]郑辉,曾燕,王勇,等.基于VIIRS夜间灯光数据的城市建筑密度估算——以南京主城区为例[J].科学技术与工程,2014,16(18)∶68-75.
[10]李峰,卫爱霞,米晓楠,等.基于NPP-VIIRS夜间灯光数据的河北省GDP空间化方法[J].信阳师范学院学报(自然科学版),2016,29(1)∶152-156.
[11]Shi K F,Huang C,Yu B L,et al. Evaluation of NPP-VIIRS Nighttime Light Composite Data for Extracting Built-up Urban Areas[J]. Remote Sensing Lettens,2014,5(4)∶358-366.
[12]Elvidge C D,Baugh K E,Zhizhi M,et al. Why VIIRS Data are Superior to DMSP for Mapping Night-time Lights[J]. Proceedings of the Asia-Pacific Advanced Network,2013,35(6)∶2-19.
[13]黄益修.基于夜间灯光遥感影像和社会感知数据的人口空间化研究[D].上海:华东师范大学硕士学位论文,2016∶1-56.
[14]高义,王辉,王培涛,等.基于人口普查与多源夜间灯光数据的海岸带人口空间化分析[J].资源科学,2013,35(12)∶2517-2523.
[15]陈晴,侯西勇,吴莉.基于土地利用数据和夜间灯光数据的人口空间化模型对比分析——以黄河三角洲高效生态经济区为例[J].人文地理,2014,29(5)∶94-100.
[16]Zeng C,Zhou Y,Wang S,et al. Population Spatialization in China Based on Night-time Imagery and Land use Data[J]. International Journal of Remote Sensing,2011,32(24)∶9599-9620.
[17]Sutton P. Modeling Population Density with Night-time Satellite Imagery and GIS[J]. Computers Environment and Urban Systems,1997,21(3-4)∶227-244.
[2]王雅雯,王利,郭峰.基于GIS的人口分布图的绘制研究——以辽阳市为例[J].测绘与空间地理信息,2008,31(2)∶97-101.
[3]陈楠.基于GIS的人口时空分布特征研究[D].青岛:山东科技大学硕士学位论文,2005∶1-146.
[4]王慧鹏.大连旅顺口区基准地形起伏度与人口分布的空间关联研究[D].大连:辽宁师范大学硕士学位论文,2014∶1-147.
[5]白平平.基于GIS的内蒙古人口分布特征和情景模拟[D].呼和浩特:内蒙古师范大学硕士学位论文,2012∶1-61.
[6]周自翔,李晶,任志远.基于GIS的关中—天水经济区地形起伏度与人口分布研究[J].地理科学,2012,32(8)∶951-957.
[7]杨眉,王世新,周艺,等. DMSP/OLS夜间灯光数据应用研究综述[J].遥感技术与应用,2011,26(1)∶45-51.
[8]曹丽琴,李平湘,张良培.基于DMSP/OLS夜间灯光数据的城市人口估算——以湖北省各县市为例[J].遥感信息,2009,(1)∶83-87.
[9]郑辉,曾燕,王勇,等.基于VIIRS夜间灯光数据的城市建筑密度估算——以南京主城区为例[J].科学技术与工程,2014,16(18)∶68-75.
[10]李峰,卫爱霞,米晓楠,等.基于NPP-VIIRS夜间灯光数据的河北省GDP空间化方法[J].信阳师范学院学报(自然科学版),2016,29(1)∶152-156.
[11]Shi K F,Huang C,Yu B L,et al. Evaluation of NPP-VIIRS Nighttime Light Composite Data for Extracting Built-up Urban Areas[J]. Remote Sensing Lettens,2014,5(4)∶358-366.
[12]Elvidge C D,Baugh K E,Zhizhi M,et al. Why VIIRS Data are Superior to DMSP for Mapping Night-time Lights[J]. Proceedings of the Asia-Pacific Advanced Network,2013,35(6)∶2-19.
[13]黄益修.基于夜间灯光遥感影像和社会感知数据的人口空间化研究[D].上海:华东师范大学硕士学位论文,2016∶1-56.
[14]高义,王辉,王培涛,等.基于人口普查与多源夜间灯光数据的海岸带人口空间化分析[J].资源科学,2013,35(12)∶2517-2523.
[15]陈晴,侯西勇,吴莉.基于土地利用数据和夜间灯光数据的人口空间化模型对比分析——以黄河三角洲高效生态经济区为例[J].人文地理,2014,29(5)∶94-100.
[16]Zeng C,Zhou Y,Wang S,et al. Population Spatialization in China Based on Night-time Imagery and Land use Data[J]. International Journal of Remote Sensing,2011,32(24)∶9599-9620.
[17]Sutton P. Modeling Population Density with Night-time Satellite Imagery and GIS[J]. Computers Environment and Urban Systems,1997,21(3-4)∶227-244.