IDEAS home Printed from https://ideas.repec.org/a/eee/ecolec/v70y2011i5p921-928.html
   My bibliography  Save this article

Net primary production and gross domestic product in China derived from satellite imagery

Author

Listed:
  • Zhao, Naizhuo
  • Currit, Nate
  • Samson, Eric

Abstract

Since the 1980s Chinese economic reform has greatly accelerated its economic growth while in contrast China's environment is increasingly degraded. The Chinese government has recognized that environmental protection and sustainable economic development can promote mutual and sustainable co-development of the economy and the environment as a basic national principle. This paper examines the interactions between economic development and environmental change in China that were compared and analyzed for the years 1996 and 2000. Net primary production (NPP) was selected as a proxy evaluator of ecosystems and gross domestic product (GDP) was chosen as a proxy evaluator of economic development. An NPP change map was produced with Advanced Very High Resolution Radiometer (AVHRR) summed annual NPP imagery products. The Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) nighttime imagery was used to produce a Chinese GDP change map. An integrated map was produced to exhibit the combined changes of NPP and GDP. This map showed that in the regions with increased GDP, NPP decreased but the regions with no GDP change were smaller in area for NPP increase while larger in area for NPP decrease. The changing pattern of NPP varied with the developing level of GDP at province level. A province's development of GDP is controlled by its accessibility to natural resources. Interactions between NPP and GDP are greatly affected by factors of spatial location aside from human factors and natural systems' characteristics.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:ecolec:v:70:y:2011:i:5:p:921-928
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0921-8009(11)00009-7
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jikun Huang & Scott Rozelle, 1995. "Environmental Stress and Grain Yields in China," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(4), pages 853-864.
    2. 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.
    3. Shafik, Nemat, 1994. "Economic Development and Environmental Quality: An Econometric Analysis," Oxford Economic Papers, Oxford University Press, vol. 46(0), pages 757-773, Supplemen.
    4. 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.
    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. 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. Natalya Rybnikova & Boris Portnov, 2015. "Using light-at-night (LAN) satellite data for identifying clusters of economic activities in Europe," Letters in Spatial and Resource Sciences, Springer, vol. 8(3), pages 307-334, November.
    3. Xiang Ji & Jiasen Sun & Qunwei Wang & Qianqian Yuan, 2019. "Revealing Energy Over-Consumption and Pollutant Over-Emission Behind GDP: A New Multi-criteria Sustainable Measure," Computational Economics, Springer;Society for Computational Economics, vol. 54(4), pages 1391-1421, December.
    4. Nicolene Hamman & Andrew Phiri, 2022. "Using Nighttime Luminosity as a Proxy for Economic Growth in Africa: Is It a Bright Idea?," Managing Global Transitions, University of Primorska, Faculty of Management Koper, vol. 20(2 (Summer), pages 139-165.
    5. Kim, Kyoochul, 2022. "The North Korean economy seen by satellite: Estimates of national performance, regional gaps based on nighttime light," Journal of Asian Economics, Elsevier, vol. 78(C).
    6. Nicola Pestalozzi & Peter Cauwels & Didier Sornette, 2013. "Dynamics and Spatial Distribution of Global Nighttime Lights," Papers 1303.2901, arXiv.org.
    7. 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.
    8. E. Ustaoglu & R. Bovkır & A. C. Aydınoglu, 2021. "Spatial distribution of GDP based on integrated NPS-VIIRS nighttime light and MODIS EVI data: a case study of Turkey," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(7), pages 10309-10343, July.
    9. Jingjing Liu & Jing Wang & Tianlin Zhai & Zehui Li, 2022. "The Response of Ecologically Functional Land to Changes in Urban Economic Growth and Transportation Construction in China," IJERPH, MDPI, vol. 19(21), pages 1-17, November.

    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. Boslett, Andrew & Hill, Elaine & Ma, Lala & Zhang, Lujia, 2021. "Rural light pollution from shale gas development and associated sleep and subjective well-being," Resource and Energy Economics, Elsevier, vol. 64(C).
    2. 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.
    3. Zhaoxin Dai & Yunfeng Hu & Guanhua Zhao, 2017. "The Suitability of Different Nighttime Light Data for GDP Estimation at Different Spatial Scales and Regional Levels," Sustainability, MDPI, vol. 9(2), pages 1-15, February.
    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. 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.
    6. 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.
    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. Xiang Ji & Jiasen Sun & Qunwei Wang & Qianqian Yuan, 2019. "Revealing Energy Over-Consumption and Pollutant Over-Emission Behind GDP: A New Multi-criteria Sustainable Measure," Computational Economics, Springer;Society for Computational Economics, vol. 54(4), pages 1391-1421, December.
    9. 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.
    10. 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.
    11. Huixia Zhao & Emi Uchida & Xiangzheng Deng & Scott Rozelle, 2011. "Do Trees Grow with the Economy? A Spatial Analysis of the Determinants of Forest Cover Change in Sichuan, China," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 50(1), pages 61-82, September.
    12. 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.
    13. Felbermayr, Gabriel & Gröschl, Jasmin & Sanders, Mark & Schippers, Vincent & Steinwachs, Thomas, 2022. "The economic impact of weather anomalies," World Development, Elsevier, vol. 151(C).
    14. 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.
    15. 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.
    16. Thomas Steinwachs, 2019. "Geography Matters: Spatial Dimensions of Trade, Migration and Growth," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 81.
    17. Meng, Lina & Graus, Wina & Worrell, Ernst & Huang, Bo, 2014. "Estimating CO2 (carbon dioxide) emissions at urban scales by DMSP/OLS (Defense Meteorological Satellite Program's Operational Linescan System) nighttime light imagery: Methodological challenges and a ," Energy, Elsevier, vol. 71(C), pages 468-478.
    18. 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.
    19. 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.
    20. World Bank, 2015. "Socioeconomic Impact of Mining on Local Communities in Africa," World Bank Publications - Reports 22489, The World Bank Group.

    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:eee:ecolec:v:70:y:2011:i:5:p:921-928. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolecon .

    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.