Modeling the luminous intensity of Beijing, China using DMSP-OLS night-time lights series data for estimating population density

被引:36
|
作者
Kumar, Pavan [1 ]
Sajjad, Haroon [1 ]
Joshi, P. K. [2 ]
Elvidge, Christopher D. [3 ]
Rehman, Sufia [1 ]
Chaudhary, B. S. [4 ]
Tripathy, Bismay Ranjan [5 ]
Singh, Jyoti [6 ]
Pipal, Gajendra [7 ]
机构
[1] Jamia Millia Islamia, Dept Geog, Fac Nat Sci, New Delhi, India
[2] Jawaharlal Nehru Univ, Sch Environm Sci, New Delhi, India
[3] Stanford Univ, Appl Earth Sci, NOAA, Boulder, CO 80305 USA
[4] Kurukshetra Univ, Dept Geophys, Kurukshetra, Haryana, India
[5] Natl Ctr Earth Sci Studies Earth Syst Sci Org, Thiruvananthapuram, Kerala, India
[6] Natl Remote Sensing Ctr, Forest & Ecol Grp, Hyderabad, Telangana, India
[7] Punjab Remote Sensing Ctr, Ludhiana, Punjab, India
关键词
Correlation analysis; Light intensity; Population dynamics; DMSP-OLS sensor; URBANIZATION DYNAMICS; SPATIOTEMPORAL DYNAMICS; SATELLITE IMAGERY; HUMAN-SETTLEMENTS; TIME-SERIES; INTERCALIBRATION; ECONOMY; SURFACE; IMPACT; REGION;
D O I
10.1016/j.pce.2018.06.002
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Various scientific researches were conducted to monitor human activities and natural phenomena with the availability of various night time satellite data such as Defense Meteorological Satellite Program (DMPS). Population growth especially in a faster growing economy like China is an important indicator for assessing socio-economic development, urban planning and environmental management. Thus, spatial distribution of population is instrumental in assessing growth and developmental activities in Beijing city of China. The satellite observation data derived from Defense Meteorological Satellite Program (DMSP) was utilized to estimate population density through the measurement of light flux with radiometric recording. The data was calibrated using C-0, C-1, C-2 parameters before processing. Population density of Beijing city was estimated using light volume of this calibrated data. Regression analysis between urban population and light volume revealed high correlation (r(2) = 0.89). Thus, population density can effectively be estimated using light intensity. The model used for estimating urban population density can effectively be utilized for other major cities of the world.
引用
收藏
页码:26 / 34
页数:9
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