基于DMSP/OLS夜间灯光数据的新疆1992—2013年能源消费研究
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摘要
采用1992—2013年间DMSP/OLS夜间灯光数据与新疆统计年鉴数据相结合,并应用数学统计分析的方法,选取以灯光面积和总DN值为自变量模拟的算法,构建了新疆的能源消费空间模型。在考虑降尺度修改模型的基础上模拟了新疆地州市级的能源消费数据,并对年均模拟值数据空间分布差异进行分级,其中昌吉回族自治州、乌鲁木齐市、塔城地区和喀什地区的能源消费等级相对较高。本研究为新疆能源消费动态监测提供了新的方法支持。
All the energy problems in different countries or regions are facing great challenges.The timely and accurate grasp of the spatial dynamic change of energy consumption can make reasonable layout to occupy the initiative,make the optimal allocation of energy structure and put forward the feasible solution.In this paper,the authors put forward the combined DMSP/OLS night light data from 1992 to 2013 and Xinjiang statistical yearbook and the application of mathematical statistics and analysis method,selected the average light intensity,DN value and light area as independent variables by using multiple regression analysis.Considering the downscaling and modifying the model,the authors made the simulation of the Xinjiang state municipal energy consumption data,and made grading of the spatial distribution difference of annual simulation data.It is found that Changji,Urumqi,Tacheng and Kashihave relatively high energy consumption level.This paper puts forward a new method for the study of dynamic energy consumption in Xinjiang.
All the energy problems in different countries or regions are facing great challenges.The timely and accurate grasp of the spatial dynamic change of energy consumption can make reasonable layout to occupy the initiative,make the optimal allocation of energy structure and put forward the feasible solution.In this paper,the authors put forward the combined DMSP/OLS night light data from 1992 to 2013 and Xinjiang statistical yearbook and the application of mathematical statistics and analysis method,selected the average light intensity,DN value and light area as independent variables by using multiple regression analysis.Considering the downscaling and modifying the model,the authors made the simulation of the Xinjiang state municipal energy consumption data,and made grading of the spatial distribution difference of annual simulation data.It is found that Changji,Urumqi,Tacheng and Kashihave relatively high energy consumption level.This paper puts forward a new method for the study of dynamic energy consumption in Xinjiang.
引文
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[12]杨续超,康丽莉,张斌,等.基于多源遥感信息的电力消费量估算与影响因素分析---以浙江省为例[J].地理科学,2013,33(6):718-723.Yang X C,Kang L L,Zhang B,et al.Electricity consumption estimation using multi-sensor remote sensing data:A case study of Zhejiang Province[J].Scientia Geographica Sinica,2013,33(6):718-723.
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[16]吴健生,许娜,张曦文.中国低碳城市评价与空间格局分析[J].地理科学进展,2016,35(2):204-213.Wu J S,Xu N,Zhang X W.Evaluation of low-carbon city and spatial pattern analysis in China[J].Progress in Geography,2016,35(2):204-213.
[17]邹进贵,陈艳华,田径,等.基于Arc GIS的DMSP/OLS夜间灯光影像校正模型的构建[J].测绘地理信息,2014,39(4):33-37.Zou J G,Chen Y H,Tian J,et al.Construction of the calibration model for DMSP/OLS nighttime light images based on Arc GIS[J].Journal of Geomatics,2014,39(4):33-37.
[18]任宇飞,方创琳.京津冀城市群县域尺度生态效率评价及空间格局分析[J].地理科学进展,2017,36(1):87-98.Ren Y F,Fang C L.Spatial pattern and evaluation of eco-efficiency in counties of the Beijing-Tianjin-Hebei Urban Agglomeration[J].Progress in Geography,2017,36(1):87-98.
[19]孙伟,金晓斌,张志宏,等.中国主要城市群新增制造业用地特征及城镇体系耦合分析[J].地理科学进展,2016,35(12):1483-1493.Sun W,Jin X B,Zhang Z H,et al.Characteristics of new manufacturing land and coupling analysis with urban system in Chinese major urban agglomerations[J].Progress in Geography,2016,35(12):1483-1493.
[20]李双双,杨赛霓,刘宪锋.1960-2013年秦岭-淮河南北极端降水时空变化特征及其影响因素[J].地理科学进展,2015,34(3):354-363.Li S S,Yang S N,Liu X F.Spatiotemporal variability of extreme precipitation in north and south of the Qinling-Huaihe region and influencing factors during 1960-2013[J].Progress in Geography,2015,34(3):354-363.
[21]刘璐.基于夜间灯光数据的城市群蔓延指标[J].国土资源遥感,2018,30(2):208-213.doi:10.6046/gtzyyg.2018.02.28.Liu L.Urban sprawl metrics based on night-time light data for metropolitan areas[J].Remote Sensing for Land and Resources,2018,30(2):208-213.doi:10.6046/gtzyyg.2018.02.28.
[22]刘佳,辛鑫,刘斌,等.基于DMSP/OLS夜间灯光影像的2000-2013年鄂尔多斯市城市扩张遥感制图与驱动因子分析[J].国土资源遥感,2018,30(1):166-172.doi:10.6046/gtzyyg.2018.01.23.Liu J,Xin X,Liu B,et al.Urban expansion mapping and driving factor analysis of Ordos City during the period of 2000-2013based on DMSP/OLS nighttime light data[J].Remote Sensing for Land and Resources,2018,30(1):166-172.doi:10.6046/gtzyyg.2018.01.23.
[23]李宗光,胡德勇,李吉贺,等.基于夜间灯光数据的连片特困区GDP估算及其空间化[J].国土资源遥感,2016,28(2):168-174.doi:10.6046/gtzyyg.2016.02.26.Li Z G,Hu D Y,Li J H,et al.Simulation and spatialization of GDPin poverty areas based on night light imagery[J].Remote Sensing for Land and Resources,2016,28(2):168-174.doi:10.6046/gtzyyg.2016.02.26.
[2]Welch R.Monitoring urban population and energy utilization patterns from satellite data[J].Remote sensing of Environment,1980,9(1):1-9.
[3]Elvidge C D,Baugh K E,Kihn E A,et al.Relation between satellite observed visible-near infrared emissions,population,economic activity and electric power consumption[J].International Journal of Remote Sensing,1997,18(6):1373-1379.
[4]Chand T R K,Badarinath K V S,Elvidge C D,et al.Spatial characterization of electrical power consumption patterns over India using temporal DMSP-OLS night-time satellite data[J].International Journal of Remote Sensing,2009,30(3):647-661.
[5]Amaral S,Cmara G,Monteiro A M V,et al.Estimating population and energy consumption in Brazilian Amazonia using DMSP nighttime satellite data[J].Computers,Environment and Urban Systems,2005,29(2):179-195.
[6]Doll C N H.CIESIN Thematic Guide to Night-time Light Remote Sensing and Its Applications[R].Palisades,NY:Center for International Earth Science Information Network of Columbia University,2008.
[7]Letu H,Hara M,Yagi H,et al.Estimating energy consumption from night-time DMPS/OLS imagery after correcting for saturation effects[J].International Journal of Remote Sensing,2010,31(16):4443-4458.
[8]Takashima M,Hayashi H,Kimura H,et al.Earthquake damaged area estimation using DMSP/OLS night-time imagery-application for Hanshin-Awaji Earthquake[C]//IEEE International Geoscience and Remote Sensing Symposium.Honolulu:IEEE,2000,1:336-338.
[9]吴健生,牛妍,彭建,等.基于DMSP/OLS夜间灯光数据的1995-2009年中国地级市能源消费动态[J].地理研究,2014,33(4):625-634.Wu J S,Niu Y,Peng J,et al.Research on energy consumption dynamic among prefecture-level cities in China based on DMSP/OLSnighttime light[J].Geographical Research,2014,33(4):625-634.
[10]李通,何春阳,杨洋,等.1995-2008年中国大陆电力消费量时空动态[J].地理学报,2011,66(10):1403-1412.Li T,He C Y,Yang Y,et al.Understanding electricity consumption changes in Chinese mainland from 1995 to 2008 by using DMSP/OLS stable nighttime light time series data[J].Acta Geographica Sinica,2011,66(10):1403-1412.
[11]吴耀文,丁浩东,李宛婕,等.基于DMSP/OLS的湖北能源需求预测[J].科技视界,2013(11):152,180.Wu Y W,Ding H D,Li W J,et al.Based on DMSP/OLS energy demand forecasting of Hubei[J].Science and Technology Vision,2013(11):152,180.
[12]杨续超,康丽莉,张斌,等.基于多源遥感信息的电力消费量估算与影响因素分析---以浙江省为例[J].地理科学,2013,33(6):718-723.Yang X C,Kang L L,Zhang B,et al.Electricity consumption estimation using multi-sensor remote sensing data:A case study of Zhejiang Province[J].Scientia Geographica Sinica,2013,33(6):718-723.
[13]Zhao N,Ghosh T,Samson E L.Mapping spatio-temporal changes of Chinese electric power consumption using night-time imagery[J].International Journal of Remote Sensing,2012,33(20):6304-6320.
[14]苏泳娴,陈修治,叶玉瑶,等.基于夜间灯光数据的中国能源消费碳排放特征及机理[J].地理学报,2013,68(11):1513-1526.Su Y X,Chen X Z,Ye Y Y,et al.The characteristics and mechanisms of carbon emissions from energy consumption in China using DMSP/OLS night light imageries[J].Acta Geographica Sinica,2013,68(11):1513-1526.
[15]王琪,袁涛,郑新奇.基于夜间灯光数据的中国省域GDP总量分析[J].城市发展研究,2013,20(7):44-48.Wang Q,Yuan T,Zheng X Q.GDP gross analysis at province-level in China based on night-time light satellite imagery[J].Urban Development Studies,2013,20(7):44-48.
[16]吴健生,许娜,张曦文.中国低碳城市评价与空间格局分析[J].地理科学进展,2016,35(2):204-213.Wu J S,Xu N,Zhang X W.Evaluation of low-carbon city and spatial pattern analysis in China[J].Progress in Geography,2016,35(2):204-213.
[17]邹进贵,陈艳华,田径,等.基于Arc GIS的DMSP/OLS夜间灯光影像校正模型的构建[J].测绘地理信息,2014,39(4):33-37.Zou J G,Chen Y H,Tian J,et al.Construction of the calibration model for DMSP/OLS nighttime light images based on Arc GIS[J].Journal of Geomatics,2014,39(4):33-37.
[18]任宇飞,方创琳.京津冀城市群县域尺度生态效率评价及空间格局分析[J].地理科学进展,2017,36(1):87-98.Ren Y F,Fang C L.Spatial pattern and evaluation of eco-efficiency in counties of the Beijing-Tianjin-Hebei Urban Agglomeration[J].Progress in Geography,2017,36(1):87-98.
[19]孙伟,金晓斌,张志宏,等.中国主要城市群新增制造业用地特征及城镇体系耦合分析[J].地理科学进展,2016,35(12):1483-1493.Sun W,Jin X B,Zhang Z H,et al.Characteristics of new manufacturing land and coupling analysis with urban system in Chinese major urban agglomerations[J].Progress in Geography,2016,35(12):1483-1493.
[20]李双双,杨赛霓,刘宪锋.1960-2013年秦岭-淮河南北极端降水时空变化特征及其影响因素[J].地理科学进展,2015,34(3):354-363.Li S S,Yang S N,Liu X F.Spatiotemporal variability of extreme precipitation in north and south of the Qinling-Huaihe region and influencing factors during 1960-2013[J].Progress in Geography,2015,34(3):354-363.
[21]刘璐.基于夜间灯光数据的城市群蔓延指标[J].国土资源遥感,2018,30(2):208-213.doi:10.6046/gtzyyg.2018.02.28.Liu L.Urban sprawl metrics based on night-time light data for metropolitan areas[J].Remote Sensing for Land and Resources,2018,30(2):208-213.doi:10.6046/gtzyyg.2018.02.28.
[22]刘佳,辛鑫,刘斌,等.基于DMSP/OLS夜间灯光影像的2000-2013年鄂尔多斯市城市扩张遥感制图与驱动因子分析[J].国土资源遥感,2018,30(1):166-172.doi:10.6046/gtzyyg.2018.01.23.Liu J,Xin X,Liu B,et al.Urban expansion mapping and driving factor analysis of Ordos City during the period of 2000-2013based on DMSP/OLS nighttime light data[J].Remote Sensing for Land and Resources,2018,30(1):166-172.doi:10.6046/gtzyyg.2018.01.23.
[23]李宗光,胡德勇,李吉贺,等.基于夜间灯光数据的连片特困区GDP估算及其空间化[J].国土资源遥感,2016,28(2):168-174.doi:10.6046/gtzyyg.2016.02.26.Li Z G,Hu D Y,Li J H,et al.Simulation and spatialization of GDPin poverty areas based on night light imagery[J].Remote Sensing for Land and Resources,2016,28(2):168-174.doi:10.6046/gtzyyg.2016.02.26.