基于DMSP/OLS夜间灯光影像的省际经济发展水平评估模型研究

doi:10.3969/j.issn.0255-8297.2017.05.010

Abstract

Abstract:

This paper produces nighttime light intensity maps across 31 provinces and municipalities in mainland China using the DMSP/OLS nighttime lights data in 2001, 2004 and 2007. Brightness ratio and area ratio are introduced to construct a nighttime light index and a statistics index with ratio analysis and principal component analysis. The indices in 2001 and 2004 are used as training samples and the ones in 2007 as test data to establish a linear regression model at the provincial level. The coefcient of determination is 0.872. Spatio-temporal distribution of provincial socioeconomic development levels in China is analyzed based on the nighttime light index. The results indicate that, by introducing brightness and area ratios, using nighttime light indices to estimate regional socioeconomic development levels is feasible and effective.

Key words: DMSP/OLS, nighttime light index, principal component analysis, gross domestic product (GDP), regression analysis

CLC Number:

TP79

MA Dan, CHENG Hui, MAO Yan-ling, XING Shi-he. Estimation of Provincial Economic Development Levels Based on DMSP/OLS Nighttime Light Images[J]. Journal of Applied Sciences, 2017, 35(5): 647-657.

References

[1] 陈晋,卓莉,史培军,一之濑俊明. 基于DMSP/OLS数据的中国城市化过程研究-反映区域城市化水平的灯光指数的构建[J]. 遥感学报,2003, 7(3):168-176. Chen J, Zhuo L, Shi P J, Ichinose T. The study on urbanization process in China based on DMSP/OLS data:development of a light index for urbanization level estimation[J]. Journal of Remote Sensing, 2003, 7(3):168-176. (in Chinese)
[2] Yue W Z, Gao J B, Yang X C. Estimation of gross domestic product using multi-sensor remote sensing data:a case study in Zhejiang Province, East China[J]. Remote Sensing, 2014, 6(8):7260-7275.
[3] Elvidge C D, Cinzano P, Petiit D R, Arvesen J, Sutton P, Small C, Nemani R, Longcore T, Rich C, Safran J, Weeks J, Ebener S. The nights at mission concept[J]. International Journal of Remote Sensing, 2007, 28(12):2645-2670.
[4] 韩向娣,周艺,王世新,刘瑞,姚尧. 夜间灯光遥感数据的GDP空间化处理方法[J]. 地球信息科学学报,2012, 14(1):128-136. Han X D, Zhou Y, Wang S X, Liu R, Yao Y. GDP spatialization in China based on nighttime imagery[J]. Journal of Geo-information Science, 2012, 14(1):128-136. (in Chinese)
[5] Zhou Y K, Ma T, Zhou C H, Xu T. Nighttime light derived assessment of regional inequality of socioeconomic development in china[J]. Remote Sensing, 2015, 7(2):1242-1262.
[6] Elvidge C D, Baugh K E, Kihn E A, Kroehl H W, Davis E R, Davis C W. 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.
[7] Zhao N, Currit N, Samson E. Net primary production and gross domestic product in China derived from satellite imagery[J]. Ecological Economics, 2011, 70(5):921-928.
[8] Doll C N H, Muller J, Morley J G. Mapping regional economic activity from night-time light satellite imagery[J]. Ecological Economics, 2006, 57(1):75-92.
[9] 梁友嘉,徐中民. 基于夜间灯光辐射数据的张掖市甘州区GDP空间分布建模[J]. 冰川冻土, 2013(1):249-254. Liang Y J, Xu Z M. Modeling the spatial distribution of GDP based on night light radiation:a case study in Ganzhou District, Zhangye Municipality[J]. Journal of Glaciology and Geocryology, 2013(1):249-254. (in Chinese)
[10] 卓莉,史培军,陈晋,一之瀬俊明. 20世纪90年代中国城市时空变化特征-基于灯光指数CNLI方法的探讨[J]. 地理学报,2003, 58(6):893-902. Zhuo L, Shi P J, Chen J, Ichinose T. Application of compound night light index derived from DMSP/OLS data to urbanization analysis in China in the 1990s[J]. Acta Geographica Sinica, 2003, 58(6):893-902. (in Chinese)
[11] Li X, Ge L L, Chen X L. Detecting Zimbabwe's decadal economic decline using nighttime light imagery[J]. Remote Sensing, 2013, 5(9):4551-4570.
[12] 徐梦洁,陈黎,刘焕金,王慧. 基于DMSP/OLS夜间灯光数据的长江三角洲地区城市化格局与过程研究[J]. 国土资源遥感,2011(3):106-112. Xu M J, Chen L, Liu H J, Wang H. Pattern and process of urbanization in the Yangtze delta based on DMSP/OLS data[J]. Remote Sensing for Land & Resource, 2011(3):106-112. (in Chinese)
[13] 杨眉,王世新,周艺,王丽涛. 基于DMSP/OLS影像的城市化水平遥感估算方法[J]. 遥感信息,2011, 4:100-106. Yang M, Wang S X, Zhou Y, Wang L T. Review on applications of DMSP/OLS night-time emissions data[J]. Remote Sensing Information, 2011, 4:100-106. (in Chinese)
[14] Elvidge C D, Sutton P C, Ghosh T, Ghosh T, Tuttle B T, Baugh K E, Bhaduri B, Bright E. A global poverty map derived from satellite data[J]. Computers & Geosciences, 2009, 35:1652-1660.
[15] Ma T, Zhou C, Pei T, Haynie S, Fan J. Quantitative estimation of urbanization dynamics using time series of DMSP/OLS nighttime light data:a comparative case study from China's cities[J]. Remote Sensing of Environment, 2012, 124:99-107.
[16] Letu H, Hara M, Yagi H, Naoki K, Tana G, Nishio F, Shuhei O. 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.
[17] 苏泳娴. 基于DMSP/OLS夜间灯光数据的中国能源消费[D] 广州:中国科学院广州地球化学研究所,2015:1-18.
[18] Raupach M R, Rayner P J, Paget M. Regional variations in spatial structure of nightlights, population density and fossil-fuel CO₂ emissions[J]. Energy Policy, 2010, 38(9):4756-4764.
[19] Oda T, Maksyutov S. A very high-resolution global fossil fuel CO₂ emission inventory derived using a point source database and satellite-observed nighttime lights, 1980-2007[J]. Atmospheric Chemistry and Physics, 2011, 11(2):543-556.
[20] 贾俊平. 统计学[M]. 第6版. 北京:中国人民大学出版社,2015:120-378.

Estimation of Provincial Economic Development Levels Based on DMSP/OLS Nighttime Light Images

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	WANG Juquan, WANG Wei, MA Huimin, YANG Bo, DU Wen. Urban Passenger Flow Aggregation Risk Forecasting Based on Principal Component Regression Algorithm [J]. Journal of Applied Sciences, 2019, 37(4): 529-540.
[2]	WANG Jin-wei, XU Chun-hui. Copy-Move Forgery Detection for Color Images Based on QPCA [J]. Journal of Applied Sciences, 2019, 37(2): 291-300.
[3]	AZIGULI Heni, GAO Qian, ALIMUJIANG Kasimu. On Spatial Simulation of Secondary and Tertiary Industrial GDP in Northern Slope Tianshan Mountains Urban Agglomeration Based on Night Light Data [J]. Journal of Applied Sciences, 2019, 37(1): 87-98.
[4]	WANG Xiang-yang1,2, WAN Wang-gen1,2. Motion Segmentation via Multi-task Robust Principal Component Analysis [J]. Journal of Applied Sciences, 2014, 32(5): 473-480.
[5]	MENG Yi-fei1, YUAN Xue1, WEI Xue-ye1, QIN Fei-zhou2, QIN Qing-nu1. Single Sample Face Recognition with Virtual Samples and Linear Subspace Feature Extraction [J]. Journal of Applied Sciences, 2013, 31(5): 488-494.
[6]	CHEN Bo, CAI Jin-lin, CHEN Wen-sheng, LIU Zhen-he, LI Yan. Shape Prior Extraction Based on 2DPCA Training [J]. Journal of Applied Sciences, 2013, 31(1): 84-90.
[7]	YAN Xiao-zhen, XIE Hong, WANG Tong. Uncertain Sensor Data Prediction for Wireless Sensor Networks [J]. Journal of Applied Sciences, 2012, 30(6): 566-572.
[8]	. Seabed Classification Based on Principal Component Analysis of Multiple Features Combined with Sonar Image [J]. Journal of Applied Sciences, 2010, 28(4): 374-380.
[9]	HU Xiao, YU Wang-xin, YAO Jing. Face Recognition Using Binary Structure-Based Feature Selection [J]. Journal of Applied Sciences, 2010, 28(3): 271-276.
[10]	. Detection and Compensation of Shadows in High Resolution Remote Sensing Images Using PCA [J]. Journal of Applied Sciences, 2010, 28(2): 136-141.
[11]	DING Meng1, CAO Yun-feng1;2, WU Qing-xian1. Crater Detection from Gray Image of the Moon Surface [J]. Journal of Applied Sciences, 2009, 27(2): 156-160.
[12]	HE Liang-hua, ZOU Cai-rong, ZHAO Li. A Method Using Skin-Color and Template Gradients for Face Detection [J]. Journal of Applied Sciences, 2004, 22(4): 487-492.
[13]	SONG Ai-bo, ZHUANG Xiao-qing, HE Jie-yue, YE Ning, DONG Yi-sheng. Quick Clustering of Large Log Data in Library [J]. Journal of Applied Sciences, 2003, 21(3): 284-288.
[14]	HE ZHENYA, GU MINGLIANG, WANG TAIJUN, SHI XIAOXING. Principal Component Feature for Speech Recognition [J]. Journal of Applied Sciences, 1999, 17(4): 427-432.
[15]	GE MIAO. Relationship between Reference Value of Chinese Healthy Adult and Young People's Whole Blood Contrast Viscosity and Geographical Factors [J]. Journal of Applied Sciences, 1998, 16(4): 495-498.