IDEAS home Printed from https://ideas.repec.org/p/osf/socarx/vf28g.html
   My bibliography  Save this paper

Using satellites and artificial intelligence to measure health and material-living standards in India

Author

Listed:
  • Daoud, Adel
  • Jordan, Felipe
  • Sharma, Makkunda
  • Johansson, Fredrik
  • Dubhashi, Devdatt
  • Paul, Sourabh
  • Banerjee, Subhashis

Abstract

The application of deep learning methods to survey human development in remote areas with satellite imagery at high temporal frequency can significantly enhance our understanding of spatial and temporal patterns in human development. Current applications have focused their efforts in predicting a narrow set of asset-based measurements of human well-being within a limited group of African countries. Here, we leverage georeferenced village-level census data from across 30 percent of the landmass of India to train a deep-neural network that predicts 16 variables representing material conditions from annual composites of Landsat 7 imagery. The census-based model is used as a feature extractor to train another network that predicts an even larger set of developmental variables (over 90 variables) included in two rounds of the National Family Health Survey (NFHS) survey. The census-based model outperforms the current standard in the literature, night-time-luminosity-based models, as a feature extractor for several of these large set of variables. To extend the temporal scope of the models, we suggest a distribution-transformation procedure to estimate outcomes over time and space in India. Our procedure achieves levels of accuracy in the R-square of 0.92 to 0.60 for 21 development outcomes, 0.59 to 0.30 for 25 outcomes, and 0.29 to 0.00 for 28 outcomes, and 19 outcomes had negative R-square. Overall, the results show that combining satellite data with Indian Census data unlocks rich information for training deep learning models that track human development at an unprecedented geographical and temporal definition.

Suggested Citation

  • Daoud, Adel & Jordan, Felipe & Sharma, Makkunda & Johansson, Fredrik & Dubhashi, Devdatt & Paul, Sourabh & Banerjee, Subhashis, 2021. "Using satellites and artificial intelligence to measure health and material-living standards in India," SocArXiv vf28g, Center for Open Science.
    • Handle: RePEc:osf:socarx:vf28g
    DOI: 10.31219/osf.io/vf28g
    as

    Download full text from publisher

    File URL: https://osf.io/download/61cf37cbb0ea7109d6b2a841/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/vf28g?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Sara Randall & Ernestina Coast, 2015. "Poverty in African Households: the Limits of Survey and Census Representations," Journal of Development Studies, Taylor & Francis Journals, vol. 51(2), pages 162-177, February.
    2. 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.
    3. Halleröd, Björn & Rothstein, Bo & Daoud, Adel & Nandy, Shailen, 2013. "Bad Governance and Poor Children: A Comparative Analysis of Government Efficiency and Severe Child Deprivation in 68 Low- and Middle-income Countries," World Development, Elsevier, vol. 48(C), pages 19-31.
    4. Daoud, Adel & Kim, Rockli & Subramanian, S.V., 2019. "Predicting women's height from their socioeconomic status: A machine learning approach," Social Science & Medicine, Elsevier, vol. 238(C), pages 1-1.
    Full references (including those not matched with items on IDEAS)

    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. Adel Daoud & Felipe Jordan & Makkunda Sharma & Fredrik Johansson & Devdatt Dubhashi & Sourabh Paul & Subhashis Banerjee, 2021. "Measuring poverty in India with machine learning and remote sensing," Papers 2202.00109, arXiv.org, revised Oct 2022.
    2. Adel Daoud & Felipe Jordán & Makkunda Sharma & Fredrik Johansson & Devdatt Dubhashi & Sourabh Paul & Subhashis Banerjee, 2023. "Using Satellite Images and Deep Learning to Measure Health and Living Standards in India," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 167(1), pages 475-505, June.
    3. Adel Daoud, 2021. "The International Monetary Funds intervention in education systems and its impact on childrens chances of completing school," Papers 2201.00013, arXiv.org.
    4. Adel Daoud, 2020. "The wealth of nations and the health of populations: A quasi-experimental design of the impact of sovereign debt crises on child mortality," Papers 2012.14941, arXiv.org.
    5. Daoud, Adel, 2021. "The International Monetary Fund’s intervention in education systems and its impact on children’s chances of completing school," SocArXiv kbc34, Center for Open Science.
    6. Adel Daoud & Anders Herlitz & SV Subramanian, 2020. "Combining distributive ethics and causal Inference to make trade-offs between austerity and population health," Papers 2007.15550, arXiv.org, revised Aug 2020.
    7. Seiffert, Sebastian, 2015. "The Role of Economic Geography in Subnational African Development," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113186, Verein für Socialpolitik / German Economic Association.
    8. Corral, Leonardo R. & Schling, Maja, 2017. "The impact of shoreline stabilization on economic growth in small island developing states," Journal of Environmental Economics and Management, Elsevier, vol. 86(C), pages 210-228.
    9. Hayakawa, Kazunobu & Keola, Souknilanh & Silaphet, Korrakoun & Yamanouchi, Kenta, 2022. "Estimating the impacts of international bridges on foreign firm locations: a machine learning approach," IDE Discussion Papers 847, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    10. Zhonghua Cheng & Xiaowen Hu, 2023. "The effects of urbanization and urban sprawl on CO2 emissions in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(2), pages 1792-1808, February.
    11. Beyer, Robert C.M. & Franco-Bedoya, Sebastian & Galdo, Virgilio, 2021. "Examining the economic impact of COVID-19 in India through daily electricity consumption and nighttime light intensity," World Development, Elsevier, vol. 140(C).
    12. 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).
    13. Merima Ali & Odd-Helge Fjeldstad & Boqian Jiang & Abdulaziz B Shifa, 2019. "Colonial Legacy, State-building and the Salience of Ethnicity in Sub-Saharan Africa," The Economic Journal, Royal Economic Society, vol. 129(619), pages 1048-1081.
    14. Yu Kun Wang & Li Zhang, 2022. "Tax Revenue, Night Lights and Underground Economy: Evidence from China," Journal of Tax Reform, Graduate School of Economics and Management, Ural Federal University, vol. 8(2), pages 186-198.
    15. Sumit Agarwal & Thomas Kigabo & Ms. Camelia Minoiu & Mr. Andrea F Presbitero & Andre Silva, 2018. "Financial Access Under the Microscope," IMF Working Papers 2018/208, International Monetary Fund.
    16. Julian Donaubauer & Peter Kannen & Frauke Steglich, 2022. "Foreign Direct Investment & Petty Corruption in Sub-Saharan Africa: An Empirical Analysis at the Local Level," Journal of Development Studies, Taylor & Francis Journals, vol. 58(1), pages 76-95, January.
    17. Huang, Siyu & Shi, Yi & Chen, Qinghua & Li, Xiaomeng, 2022. "The growth path of high-tech industries: Statistical laws and evolution demands," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    18. Flückiger, Matthias & Ludwig, Markus, 2015. "Economic shocks in the fisheries sector and maritime piracy," Journal of Development Economics, Elsevier, vol. 114(C), pages 107-125.
    19. Andaleeb Rahman & Sumit Mishra, 2020. "Does Non-farm Income Affect Food Security? Evidence from India," Journal of Development Studies, Taylor & Francis Journals, vol. 56(6), pages 1190-1209, June.
    20. Menezes, Flavio & Figer, Vivian & Jardim, Fernanda & Medeiros, Pedro, 2022. "A near real-time economic activity tracker for the Brazilian economy during the COVID-19 pandemic," Economic Modelling, Elsevier, vol. 112(C).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:osf:socarx:vf28g. 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: OSF (email available below). General contact details of provider: https://arabixiv.org .

    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.