IDEAS home Printed from https://ideas.repec.org/a/spr/soinre/v179y2025i2d10.1007_s11205-025-03614-w.html
   My bibliography  Save this article

Integrating Multi-Source Satellite Imagery and Socio-Economic Household Data for Wealth-Based Poverty Assessment of India: A GIS and Machine Learning Based Approach

Author

Listed:
  • Prashant Kumar Arya

    (Institute for Human Development (IHD)
    Central University of Jharkhand)

  • Koyel Sur

    (Punjab Remote Sensing Centre (PRSC))

  • Siddharth Dhote

    (Institute for Human Development (IHD))

  • Harsh Siral

    (Mapmy India)

  • Tanushree Kundu

    (Central University of Jharkhand)

  • Balwant Singh Mehta

    (Institute for Human Development (IHD))

  • Ravi Srivastava

    (Institute for Human Development (IHD))

Abstract

Assessing poverty or disparity requires accurate data that is geographically pertinent, trackable (real-time evaluation), and less error-prone, which is important for achieving the Sustainable Development Goals (SDG) of the United Nations to remove poverty. Acquiring these datasets is tough, particularly in developing nations with fluctuating economic dynamics. Although poverty is a complicated phenomenon it cannot be conceptually or realistically quantified by a single data category, therefore an attempt has been made using multisource information to quantify poverty or disparity. The present study aims at the integration of conventional and non-conventional datasets by using Geographic Information Systems (GIS) analysis and a machine learning-based Random Forest Regression (RFR) model to predict inequality for the Grid scale (10 × 10 km) at a sub-national level. The significance of this research could substantially impact poverty alleviation efforts, which can provide valuable insight into wealth inequality that can guide evidence-based policy decisions, optimize resource allocation strategies, and achieve SDGs. The Demographic and Health Surveys (DHS), household wealth index (WI) factor score was considered to predict wealth inequality. To evaluate the model's efficacy in forecasting the WI factor score for India, the Random Forest Regression (RFR) model was supplied with both geospatial-based socio-economic datasets. The analysis revealed an R-square value of 0.86 between the observed and projected WI factor scores, demonstrating the model's high precision in predicting the WI. Besides, this study also discovered a negative association with a correlation (-0.6) between the district average WI and the Multidimensional Poverty Index (MPI) of India. Gini significance analysis determined crucial factors that are causing wealth disparity. Population count and POI density were shown to be the two most important variables, explaining 36.09% and 26.1% of the explanatory power, respectively. This suggests that places with a higher population density and POI density have more wealth disparity. Overall, the findings give essential insights into the factors that drive India's wealth inequality, which would help reform policies to eliminate this disparity.

Suggested Citation

  • Prashant Kumar Arya & Koyel Sur & Siddharth Dhote & Harsh Siral & Tanushree Kundu & Balwant Singh Mehta & Ravi Srivastava, 2025. "Integrating Multi-Source Satellite Imagery and Socio-Economic Household Data for Wealth-Based Poverty Assessment of India: A GIS and Machine Learning Based Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 179(2), pages 653-676, September.
    • Handle: RePEc:spr:soinre:v:179:y:2025:i:2:d:10.1007_s11205-025-03614-w
    DOI: 10.1007/s11205-025-03614-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11205-025-03614-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11205-025-03614-w?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
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Walekhwa, Peter N. & Mugisha, Johnny & Drake, Lars, 2009. "Biogas energy from family-sized digesters in Uganda: Critical factors and policy implications," Energy Policy, Elsevier, vol. 37(7), pages 2754-2762, July.
    2. Heger, Martin Philipp & Zens, Gregor & Bangalore, Mook, 2020. "Land and poverty: the role of soil fertility and vegetation quality in poverty reduction," Environment and Development Economics, Cambridge University Press, vol. 25(4), pages 315-333, August.
    3. van der Weide, Roy & Blankespoor, Brian & Elbers, Chris & Lanjouw, Peter, 2024. "How accurate is a poverty map based on remote sensing data? An application to Malawi," Journal of Development Economics, Elsevier, vol. 171(C).
    4. Srijit Mishra, 2015. "Decomposing Poverty Change: Deciphering Change in Total Population and Beyond," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 61(4), pages 799-811, December.
    5. Njuguna, Christopher & McSharry, Patrick, 2017. "Constructing spatiotemporal poverty indices from big data," Journal of Business Research, Elsevier, vol. 70(C), pages 318-327.
    6. Alessandra Costagliola, 2021. "Labor Participation and Gender Inequalities in India: Traditional Gender Norms in India and the Decline in the Labor Force Participation Rate (LFPR)," The Indian Journal of Labour Economics, Springer;The Indian Society of Labour Economics (ISLE), vol. 64(3), pages 531-542, September.
    7. Justin Sandefur & Amanda Glassman, 2015. "The Political Economy of Bad Data: Evidence from African Survey and Administrative Statistics," Journal of Development Studies, Taylor & Francis Journals, vol. 51(2), pages 116-132, February.
    8. Thomas Lindner & Jonas Puck & Alain Verbeke, 2022. "Beyond addressing multicollinearity: Robust quantitative analysis and machine learning in international business research," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 53(7), pages 1307-1314, September.
    9. Connie Bayudan-Dacuycuy & Lora Kryz Baje, 2019. "When It Rains, It Pours? Analyzing the Rainfall Shocks-Poverty Nexus in the Philippines," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 145(1), pages 67-93, August.
    10. George Psacharopoulos & Harry Anthony Patrinos, 2018. "Returns to investment in education: a decennial review of the global literature," Education Economics, Taylor & Francis Journals, vol. 26(5), pages 445-458, September.
    11. Michel Opelele Omeno & Ying Yu & Wenyi Fan & Tolerant Lubalega & Chen Chen & Claude Kachaka Sudi Kaiko, 2021. "Analysis of the Impact of Land-Use/Land-Cover Change on Land-Surface Temperature in the Villages within the Luki Biosphere Reserve," Sustainability, MDPI, vol. 13(20), pages 1-23, October.
    12. Shantayanan Devarajan, 2013. "Africa's Statistical Tragedy," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 59, pages 9-15, October.
    13. Mengxue Liu & Hejie Wei & Xiaobin Dong & Xue-Chao Wang & Bingyu Zhao & Ying Zhang, 2022. "Integrating Land Use, Ecosystem Service, and Human Well-Being: A Systematic Review," Sustainability, MDPI, vol. 14(11), pages 1-31, June.
    14. Arouna Diallo & Richard Kouame Moussa, 2020. "Does access to electricity affect poverty? Evidence from Côte d'Ivoire," Economics Bulletin, AccessEcon, vol. 40(3), pages 2521-2537.
    15. Heger, Martin Philipp & Zens, Gregor & Bangalore, Mook, 2020. "Land and poverty: the role of soil fertility and vegetation quality in poverty reduction," LSE Research Online Documents on Economics 115658, London School of Economics and Political Science, LSE Library.
    16. Pieter Serneels & Stefan Dercon, 2021. "Aspirations, Poverty, and Education. Evidence from India," Journal of Development Studies, Taylor & Francis Journals, vol. 57(1), pages 163-183, January.
    17. Alelgn Ewunetu & Belay Simane & Ermias Teferi & Benjamin F. Zaitchik, 2021. "Land Cover Change in the Blue Nile River Headwaters: Farmers’ Perceptions, Pressures, and Satellite-Based Mapping," Land, MDPI, vol. 10(1), pages 1-25, January.
    18. Arouna Diallo & Richard Kouame Moussa, 2020. "Does access to electricity affect poverty? Evidence from Côte d'Ivoire," Post-Print hal-02956563, HAL.
    19. Tabish Nawab & Saqlain Raza & Malik Shahzad Shabbir & Ghulam Yahya Khan & Sana Bashir, 2023. "Multidimensional poverty index across districts in Punjab, Pakistan: estimation and rationale to consolidate with SDGs," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(2), pages 1301-1325, February.
    20. Yang Zhou & Chunyang Tong & Yongsheng Wang, 2022. "Road construction, economic growth, and poverty alleviation in China," Growth and Change, Wiley Blackwell, vol. 53(3), pages 1306-1332, September.
    21. Maggie G. Munthali & Nerhene Davis & Abiodun M. Adeola & Joel O. Botai & Jonathan M. Kamwi & Harold L. W. Chisale & Oluwagbenga O. I. Orimoogunje, 2019. "Local Perception of Drivers of Land-Use and Land-Cover Change Dynamics across Dedza District, Central Malawi Region," Sustainability, MDPI, vol. 11(3), pages 1-25, February.
    22. Meng Le Zhang & Gwilym Pryce, 2020. "The dynamics of poverty, employment and access to amenities in polycentric cities: Measuring the decentralisation of poverty and its impacts in England and Wales," Urban Studies, Urban Studies Journal Limited, vol. 57(10), pages 2015-2030, August.
    23. Paul, Pintu, 2019. "Effects of education and poverty on the prevalence of girl child marriage in India: A district–level analysis," Children and Youth Services Review, Elsevier, vol. 100(C), pages 16-21.
    24. Li, Yurui & Li, Yi & Karácsonyi, Dávid & Liu, Zhengjia & Wang, Yongsheng & Wang, Jieyong, 2020. "Spatio-temporal pattern and driving forces of construction land change in a poverty-stricken county of China and implications for poverty-alleviation-oriented land use policies," Land Use Policy, Elsevier, vol. 91(C).
    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. Yen H. T. Nguyen & Tuyen Q. Tran & Dung T. Hoang & Thu M. T. Tran & Trung T. Nguyen, 2023. "Land quality, income, and poverty among rural households in the North Central Region, Vietnam," Poverty & Public Policy, John Wiley & Sons, vol. 15(2), pages 150-172, June.
    2. Annisaa Rizky Dwi Brintanti & Iqram Ramadhan Jamil & Usman Alhassan & Brama Yudha Kusmara & Yessi Rahmawati, 2025. "Inverted N-shape relationships: revisiting the dynamic effect of natural resources on poverty in Indonesia," Asia-Pacific Journal of Regional Science, Springer, vol. 9(1), pages 83-105, March.
    3. Dang, Hai-Anh H & Carletto, Calogero, 2022. "Recall Bias Revisited: Measure Farm Labor Using Mixed-Mode Surveys and Multiple Imputation," IZA Discussion Papers 14997, Institute of Labor Economics (IZA).
    4. Shanping Wang & Peng Cao & Xiao Ouyang, 2024. "Nonlinear influence of construction land on poverty reduction efficiency in Chinese poor counties: new evidence using a panel threshold model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(2), pages 3557-3587, February.
    5. Sam Desiere & Lotte Staelens & Marijke D’Haese, 2016. "When the Data Source Writes the Conclusion: Evaluating Agricultural Policies," Journal of Development Studies, Taylor & Francis Journals, vol. 52(9), pages 1372-1387, September.
    6. Thierry Mamadou Asngar, 2022. "Does financial development improve access to electricity in sub-Saharan Africa?," SN Business & Economics, Springer, vol. 2(9), pages 1-18, September.
    7. Mensah, Emmanuel Buadi & Szirmai, Adam, 2018. "Africa Sector Database (ASD): Expansion and update," MERIT Working Papers 2018-020, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    8. Chroufa, Mohamed Ali & Chtourou, Nouri, 2024. "The impact of income inequality on economic growth in MENA region: The role of energy poverty threshold effect," Energy, Elsevier, vol. 313(C).
    9. Manhisse, Nelson & Ogawa, Keiichi, 2024. "Smallholder households and children’s schooling in primary education in Mozambique," International Journal of Educational Development, Elsevier, vol. 105(C).
    10. Gashaye, Amare Terefe & Liu, Hongxun & Li, Jianglong, 2025. "The effect of access to electricity on rural households of underdeveloped countries: Evidence from Ethiopia," Energy Policy, Elsevier, vol. 199(C).
    11. Qian Xiong & Wenxin Shen & Chunna Liu & Xuteng Zhang & Wenzhe Tang & Colin F. Duffield & Felix Kin Peng Hui & Lihai Zhang, 2024. "Impact of Access to Electricity and Socio-Economic Environment on Poverty Reduction: An Empirical Study on Myanmar," Energies, MDPI, vol. 17(21), pages 1-20, October.
    12. Jane Onuabuchi Munonye & Robert Ugochukwu Onyeneke & Daniel Adu Ankrah & Fred Fosu Agyarko & Chinenye Judith Onyeneke & Jalil Ghassemi Nejad & Comfort Chikezie, 2025. "Do climate change, access to electricity and renewable energy consumption matter in aquaculture production in Africa?," Natural Resources Forum, Blackwell Publishing, vol. 49(2), pages 986-1009, May.
    13. Mirzabaev, Alisher & Strokov, Anton & Krasilnikov, Pavel, 2023. "The impact of land degradation on agricultural profits and implications for poverty reduction in Central Asia," Land Use Policy, Elsevier, vol. 126(C).
    14. Shuang Xu & Kai Chen & Jiang Li, 2025. "Decomposing Poverty Change: A New Four-Dimensional Decomposition Method," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 178(1), pages 137-162, May.
    15. Bruno Emmanuel Ongo Nkoa & Honoré Tekam Oumbé & Georges Ngnouwal Eloundou & Thierry Asngar Mamadou, 2022. "Impact of access to electricity on internal conflicts in Africa: Does income inequality matter?," African Development Review, African Development Bank, vol. 34(3), pages 395-409, September.
    16. Gwilym Owen & Yu Chen & Timothy Birabi & Gwilym Pryce & Hui Song & Bifeng Wang, 2023. "Residential segregation of migrants: Disentangling the intersectional and multiscale segregation of migrants in Shijiazhuang, China," Urban Studies, Urban Studies Journal Limited, vol. 60(1), pages 166-182, January.
    17. Ji Liu, 2024. "Education legislations that equalize: a study of compulsory schooling law reforms in post-WWII United States," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
    18. Uwe Sunde & Thomas Dohmen & Benjamin Enke & Armin Falkbriq & David Huffman & Gerrit Meyerheim, 2022. "Patience and Comparative Development," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(5), pages 2806-2840.
    19. Hongbin Li & Huan Wang & Claire Cousineau & Matthew Boswell, 2023. "What Can Students Gain from China's Higher Education?," Asian Economic Policy Review, Japan Center for Economic Research, vol. 18(2), pages 287-304, July.
    20. Aguirre Unceta, Rafael, 2021. "The economic and social impact of mining-resources exploitation in Zambia," Resources Policy, Elsevier, vol. 74(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:spr:soinre:v:179:y:2025:i:2:d:10.1007_s11205-025-03614-w. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.