IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v8y2016i2p108-d62865.html
   My bibliography  Save this article

Coupling an Intercalibration of Radiance-Calibrated Nighttime Light Images and Land Use/Cover Data for Modeling and Analyzing the Distribution of GDP in Guangdong, China

Author

Listed:
  • Ziyang Cao

    (Key Laboratory of Marginal Sea Geology, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
    University of Chinese Academy of Sciences, Beijing 100089, China)

  • Zhifeng Wu

    (School of Geographical Sciences, Guangzhou University, Guangzhou 510006, China)

  • Yaoqiu Kuang

    (Key Laboratory of Marginal Sea Geology, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China)

  • Ningsheng Huang

    (Key Laboratory of Marginal Sea Geology, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China)

  • Meng Wang

    (Key Laboratory of Marginal Sea Geology, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
    University of Chinese Academy of Sciences, Beijing 100089, China)

Abstract

Spatialized GDP data is important for studying the relationships between human activities and environmental changes. Rapid and accurate acquisition of these datasets are therefore a significant area of study. Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) radiance-calibrated nighttime light (RC NTL) images exhibit the potential for providing superior estimates for GDP spatialization, as they are not restricted by the saturated pixels which exist in nighttime stable light (NSL) images. However, the drawback of light overflow is the limited accuracy of GDP estimation, and GDP data estimations based on RC NTL images cannot be directly used for temporal analysis due to a lack of on-board calibration. This study develops an intercalibration method to address the comparability problem. Additionally, NDVI images are used to reduce the light overflow effect. In this way, the secondary and tertiary industry outputs are estimated by using intercalibrated RC NTL images. Primary industry production is estimated by using land use/cover data. Ultimately, four 1 km gridded GDP maps of Guangdong for 2000, 2004, 2006 and 2010 are generated. The verification results of the proposed intercalibration method demonstrate that this method is reasonable and can be effectively implemented. These maps can be used to analyze the distribution and spatiotemporal changes of GDP density in Guangdong.

Suggested Citation

  • Ziyang Cao & Zhifeng Wu & Yaoqiu Kuang & Ningsheng Huang & Meng Wang, 2016. "Coupling an Intercalibration of Radiance-Calibrated Nighttime Light Images and Land Use/Cover Data for Modeling and Analyzing the Distribution of GDP in Guangdong, China," Sustainability, MDPI, vol. 8(2), pages 1-18, January.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:2:p:108-:d:62865
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/8/2/108/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/8/2/108/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Christopher D. Elvidge & Daniel Ziskin & Kimberly E. Baugh & Benjamin T. Tuttle & Tilottama Ghosh & Dee W. Pack & Edward H. Erwin & Mikhail Zhizhin, 2009. "A Fifteen Year Record of Global Natural Gas Flaring Derived from Satellite Data," Energies, MDPI, vol. 2(3), pages 1-28, August.
    2. Zhao, Naizhuo & Currit, Nate & Samson, Eric, 2011. "Net primary production and gross domestic product in China derived from satellite imagery," Ecological Economics, Elsevier, vol. 70(5), pages 921-928, March.
    3. Sutton, Paul C. & Costanza, Robert, 2002. "Global estimates of market and non-market values derived from nighttime satellite imagery, land cover, and ecosystem service valuation," Ecological Economics, Elsevier, vol. 41(3), pages 509-527, June.
    4. Doll, Christopher N.H. & Muller, Jan-Peter & Morley, Jeremy G., 2006. "Mapping regional economic activity from night-time light satellite imagery," Ecological Economics, Elsevier, vol. 57(1), pages 75-92, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hu, Ting & Huang, Xin, 2019. "A novel locally adaptive method for modeling the spatiotemporal dynamics of global electric power consumption based on DMSP-OLS nighttime stable light data," Applied Energy, Elsevier, vol. 240(C), pages 778-792.
    2. Shengnan Jiang & Guoen Wei & Zhenke Zhang & Yue Wang & Minghui Xu & Qing Wang & Priyanko Das & Binglin Liu, 2020. "Detecting the Dynamics of Urban Growth in Africa Using DMSP/OLS Nighttime Light Data," Land, MDPI, vol. 10(1), pages 1-19, December.
    3. Qian Chen & Tingting Ye & Naizhuo Zhao & Mingjun Ding & Zutao Ouyang & Peng Jia & Wenze Yue & Xuchao Yang, 2021. "Mapping China’s regional economic activity by integrating points-of-interest and remote sensing data with random forest," Environment and Planning B, , vol. 48(7), pages 1876-1894, September.
    4. Senkai Xie & Wenjia Zhang & Yi Zhao & De Tong, 2022. "Extracting Land Use Change Patterns of Rural Town Settlements with Sequence Alignment Method," Land, MDPI, vol. 11(2), pages 1-17, February.
    5. Juan C Duque & Nancy Lozano-Gracia & Jorge E Patino & Paula Restrepo, 2022. "Urban form and productivity: What shapes are Latin-American cities?," Environment and Planning B, , vol. 49(1), pages 131-150, January.
    6. Hu, Ting & Wang, Ting & Yan, Qingyun & Chen, Tiexi & Jin, Shuanggen & Hu, Jun, 2022. "Modeling the spatiotemporal dynamics of global electric power consumption (1992–2019) by utilizing consistent nighttime light data from DMSP-OLS and NPP-VIIRS," Applied Energy, Elsevier, vol. 322(C).
    7. Juan C. Duque & Nancy Lozano‐Gracia & Jorge E. Patino & Paula Restrepo Cadavid, 2021. "Institutional fragmentation and metropolitan coordination in Latin American cities: Are there links with city productivity?," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(4), pages 1096-1128, August.
    8. Shi, Kaifang & Chen, Yun & Yu, Bailang & Xu, Tingbao & Yang, Chengshu & Li, Linyi & Huang, Chang & Chen, Zuoqi & Liu, Rui & Wu, Jianping, 2016. "Detecting spatiotemporal dynamics of global electric power consumption using DMSP-OLS nighttime stable light data," Applied Energy, Elsevier, vol. 184(C), pages 450-463.
    9. Thomas Ferreira, 2018. "Using satellite data to track socio-economic outcomes: a case study of Namibia," Working Papers 12/2018, Stellenbosch University, Department of Economics.
    10. Bin Guo & Wencai Zhang & Lin Pei & Xiaowei Zhu & Pingping Luo & Weili Duan, 2022. "Remote Sensing Evidence for Significant Variations in the Global Gross Domestic Product during the COVID-19 Epidemic," Sustainability, MDPI, vol. 14(22), pages 1-21, November.
    11. Juan Jose Miranda & Oscar A. Ishizawa & Hongrui Zhang, 2020. "Understanding the Impact Dynamics of Windstorms on Short-Term Economic Activity from Night Lights in Central America," Economics of Disasters and Climate Change, Springer, vol. 4(3), pages 657-698, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Qian Chen & Tingting Ye & Naizhuo Zhao & Mingjun Ding & Zutao Ouyang & Peng Jia & Wenze Yue & Xuchao Yang, 2021. "Mapping China’s regional economic activity by integrating points-of-interest and remote sensing data with random forest," Environment and Planning B, , vol. 48(7), pages 1876-1894, September.
    2. Addison,Douglas M. & Stewart,Benjamin P., 2015. "Nighttime lights revisited : the use of nighttime lights data as a proxy for economic variables," Policy Research Working Paper Series 7496, The World Bank.
    3. Lionel Roger, 2018. "Blinded by the light? Heterogeneity in the luminosity-growth nexus and the African growth miracle," Discussion Papers 2018-04, University of Nottingham, CREDIT.
    4. Jaqueson K. Galimberti, 2020. "Forecasting GDP Growth from Outer Space," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(4), pages 697-722, August.
    5. Jeremy Proville & Daniel Zavala-Araiza & Gernot Wagner, 2017. "Night-time lights: A global, long term look at links to socio-economic trends," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-12, March.
    6. Cuong Nguyen & Ilan Noy, 2018. "Measuring the Impact of Insurance on Urban Recovery with Light: The 2010-2011 New Zealand Earthquakes," CESifo Working Paper Series 7031, CESifo.
    7. Nguyen, Cuong & Noy, Ilan, 2018. "Measuring the impact of insurance on urban recovery with light: The 2011 New Zealand earthquake," Working Paper Series 6955, Victoria University of Wellington, School of Economics and Finance.
    8. Ilari Määttä & Thomas Ferreira & Christian Leßmann, 2022. "Nighttime lights and wealth in very small areas: [Nachtlichter und Wohlstand in Kleinräumigen Daten:]," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 42(2), pages 161-190, August.
    9. Tilottama Ghosh & Sharolyn J. Anderson & Christopher D. Elvidge & Paul C. Sutton, 2013. "Using Nighttime Satellite Imagery as a Proxy Measure of Human Well-Being," Sustainability, MDPI, vol. 5(12), pages 1-32, November.
    10. Nguyen, Cuong & Noy, Ilan, 2018. "Measuring the impact of insurance on urban recovery with light: The 2011 New Zealand earthquake," Working Paper Series 20316, Victoria University of Wellington, School of Economics and Finance.
    11. Yunfeng Hu & Yunzhi Zhang, 2020. "Global Nighttime Light Change from 1992 to 2017: Brighter and More Uniform," Sustainability, MDPI, vol. 12(12), pages 1-17, June.
    12. World Bank, 2015. "Socioeconomic Impact of Mining on Local Communities in Africa," World Bank Publications - Reports 22489, The World Bank Group.
    13. Hoang Ha Nguyen Thi & Alfons Weichenrieder, 2023. "Tax Haven Welfare and the Crackdown on Secrecy: Evidence from Night Light Emissions," CESifo Working Paper Series 10721, CESifo.
    14. Juergen Bitzer & Erkan Goeren, 2018. "Foreign Aid and Subnational Development: A Grid Cell Analysis," Working Papers V-407-18, University of Oldenburg, Department of Economics, revised Mar 2018.
    15. Felbermayr, Gabriel & Gröschl, Jasmin & Sanders, Mark & Schippers, Vincent & Steinwachs, Thomas, 2018. "Shedding Light on the Spatial Diffusion of Disasters," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181556, Verein für Socialpolitik / German Economic Association.
    16. J. Vernon Henderson & Adam Storeygard & David N. Weil, 2012. "Measuring Economic Growth from Outer Space," American Economic Review, American Economic Association, vol. 102(2), pages 994-1028, April.
    17. Anna Bruederle & Roland Hodler, 2018. "Nighttime lights as a proxy for human development at the local level," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-22, September.
    18. Konno, Akio & Kato, Hironori & Takeuchi, Wataru & Kiguchi, Riku, 2021. "Global evidence on productivity effects of road infrastructure incorporating spatial spillover effects," Transport Policy, Elsevier, vol. 103(C), pages 167-182.
    19. Qi Zhang & James Cust, 2016. "Nighttime Lights and Power Infrastructure Investment: Evidence from Angola," OxCarre Working Papers 185, Oxford Centre for the Analysis of Resource Rich Economies, University of Oxford.
    20. John Gibson & Susan Olivia & Geua Boe‐Gibson, 2020. "Night Lights In Economics: Sources And Uses," Journal of Economic Surveys, Wiley Blackwell, vol. 34(5), pages 955-980, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:8:y:2016:i:2:p:108-:d:62865. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.