Analyzing trend in artificial light pollution pattern in India using NTL sensor's data

被引:18
|
作者
Kumar, Pavan [1 ]
Rehman, Sufia [1 ]
Sajjad, Haroon [1 ]
Tripathy, Bismay Ranjan [2 ]
Rani, Meenu [3 ]
Singh, Sourabh [3 ]
机构
[1] Jamia Millia Islamia, Fac Nat Sci, New Delhi, India
[2] Natl Ctr Earth Sci Studies, Thiruvananthapuram, Kerala, India
[3] GB Pant Natl Inst Himalayan Environm & Sustainabl, Ctr Land & Water Resource Management, Koshi, Uttarakhand, India
关键词
Night time satellite data; DMSP-OLS; Inter-; calibration; Light pollution; Regression; URBANIZATION DYNAMICS; TIME-SERIES; NIGHT; CHINA; IMAGERY; INTERCALIBRATION; IMPACT;
D O I
10.1016/j.uclim.2018.12.005
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Exponential growth of population and the resultant rapid rate of urbanization and industrialization in India have significantly transformed its nighttime light environment. The study makes an attempt to analyze the spatio-temporal pattern of light pollution and its causative actors in a fast-developing economy. We utilized nighttime light data from 1993 to 2013 and calibrated through linear regression. Ten patches of major changes from the whole study area were selected to assess the intensity of light pollution at regional scale. Spatial analysis of light pollution in selected patches revealed that New Delhi, Telangana, Maharashtra, Karnataka and Uttar Pradesh experienced increase in very high light pollution intensity. West Bengal, Gujarat and Tamil Nadu witnessed a remarkable change from low to high light pollution. Urban expansion, industrial development and air pollution are main drivers for increasing light pollution. Strong correlation was found between light pollution and digital numbers (DN) values at regional scale. The maps generated through Defense Meteorological Satellite Program Operational Line Scanner Night Time Light data not only helped in assessing the intensity of light pollution but also identified its causative actors. The results of study can effectively be utilized for setting priorities of environmental protection in different geographical regions at various scales.
引用
收藏
页码:272 / 283
页数:12
相关论文
共 50 条
  • [41] Categorical Data Analysis and Pattern Mining of Top Colleges in India by Using Twitter Data
    Mamgain, Nehal
    Pant, Bhaskar
    Mittal, Ankush
    2016 8TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMMUNICATION NETWORKS (CICN), 2016, : 341 - 345
  • [42] Algebraic optimization of data delivery pattern's in mobile sensor networks
    Zadorozhny, V
    Chrysanthis, PK
    Labrinidis, A
    15TH INTERNATIONAL WORKSHOP ON DATABASE AND EXPERT SYSTEMS APPLICATIONS, PROCEEDINGS, 2004, : 668 - 672
  • [43] Spatial-temporal expansion and determinants of light pollution in India?s riparian habitats
    Khanduri, Megha
    Sah, Ruchika
    Ramachandran, Aishwarya
    Hussain, Syed Ainul
    Badola, Ruchi
    Candolin, Ulrika
    Hoelker, Franz
    ENVIRONMENTAL IMPACT ASSESSMENT REVIEW, 2023, 98
  • [44] Industrial Monitoring Using Image Processing, IoT and Analyzing the Sensor Values Using Big Data
    Rukmani, P.
    Teja, Gunda Krishna
    Vinay, M. Sai
    Reddy, Bhanu Prakash K.
    INTERNATIONAL CONFERENCE ON ROBOTICS AND SMART MANUFACTURING (ROSMA2018), 2018, 133 : 991 - 997
  • [45] Interpreting complex data from a three-sensor multipoint optical fibre ethanol concentration sensor system using artificial neural network pattern recognition
    King, D
    Lyons, WB
    Flanagan, C
    Lewis, E
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2004, 15 (08) : 1560 - 1567
  • [46] Improved Vehicle Steering Pattern Recognition by Using Selected Sensor Data
    Ouyang, Zhenchao
    Niu, Jianwei
    Guizani, Mohsen
    IEEE TRANSACTIONS ON MOBILE COMPUTING, 2018, 17 (06) : 1383 - 1396
  • [47] Multiscale Trend Analysis for Pampa Grasslands Using Ground Data and Vegetation Sensor Imagery
    Scotta, Fernando C.
    da Fonseca, Eliana L.
    SENSORS, 2015, 15 (07) : 17666 - 17692
  • [48] Analyzing the User's Sentiments of ChatGPT Using Twitter Data
    Korkmaz A.
    Aktürk C.
    Talan T.
    Iraqi Journal for Computer Science and Mathematics, 2023, 4 (02): : 202 - 214
  • [49] How important is the statistical approach for analyzing categorical data? A critique using artificial nests
    Lewis, KP
    OIKOS, 2004, 104 (02) : 305 - 315
  • [50] Integration of Image Pattern Recognition and Photon Sensor for Analyzing Cytokine Gene Expression Using πCode MicroDisc
    Juntit, On-anong
    Sornsuwan, Kanokporn
    Yasamut, Umpa
    Tayapiwatana, Chatchai
    BIOSENSORS-BASEL, 2024, 14 (06):