IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v11y2022i6p873-d834495.html
   My bibliography  Save this article

A Survey Bias Index Based on Unmanned Aerial Vehicle Imagery to Review the Accuracy of Rural Surveys

Author

Listed:
  • Xueyan Zhang

    (Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Science and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

Abstract

Field surveys and questionnaires are a cornerstone of rural socioeconomic research, providing invaluable firsthand data regarding on-the-ground situations. However, cost-effective and efficient methods for validating the accuracy of self-reported data in such questionnaires are lacking. Biased data are likely to lead to incorrect conclusions. In this study, we propose a new index, the survey bias index (SBI), for evaluating the degree of survey bias in field surveys. This index was obtained by comparing the data recorded in questionnaires with those from portable unmanned aerial vehicles (UAVs). In a case study, we employed SBI to reveal the degree of survey bias of questionnaires in field surveys on rural homesteads. The SBI of self-reported areas of rural homesteads reached 0.439, implying that 43.9% of data were significantly different from those collected using UAVs. A greater SBI was obtained in the pre-urban zone (0.515) than in the pure rural zone (0.258). These results indicate that homestead areas in the pre-urban zone have more incentive to expand than those in the pure rural zone. UAV remote sensing can strongly support research in the field of social economy, which reveals key information hidden in field surveys and questionnaires.

Suggested Citation

  • Xueyan Zhang, 2022. "A Survey Bias Index Based on Unmanned Aerial Vehicle Imagery to Review the Accuracy of Rural Surveys," Land, MDPI, vol. 11(6), pages 1-11, June.
  • Handle: RePEc:gam:jlands:v:11:y:2022:i:6:p:873-:d:834495
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/11/6/873/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/11/6/873/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cao, Qian & Sarker, Md Nazirul Islam & Sun, Jiangyan, 2019. "Model of the influencing factors of the withdrawal from rural homesteads in China: Application of grounded theory method," Land Use Policy, Elsevier, vol. 85(C), pages 285-289.
    2. Kar, Abhishek & Brauer, Michael & Bailis, Rob & Zerriffi, Hisham, 2020. "The risk of survey bias in self-reports vs. actual consumption of clean cooking fuels," World Development Perspectives, Elsevier, vol. 18(C).
    3. Li, Xuesong & Li, Hao & Wang, Xingwu, 2013. "Farmers' willingness to convert traditional houses to solar houses in rural areas: A survey of 465 households in Chongqing, China," Energy Policy, Elsevier, vol. 63(C), pages 882-886.
    4. Tur-Sinai, Aviad & Fleishman, Larisa & Romanov, Dmitri, 2020. "The accuracy of self-reported dwelling valuation," Journal of Housing Economics, Elsevier, vol. 48(C).
    5. Su, Kangchuan & Hu, Baoqing & Shi, Kaifang & Zhang, Zhongxun & Yang, Qingyuan, 2019. "The structural and functional evolution of rural homesteads in mountainous areas: A case study of Sujiaying village in Yunnan province, China," Land Use Policy, Elsevier, vol. 88(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. Yao Qian & Qingyuan Yang & Haozhe Zhang & Kangchuan Su & Huiming Zhang & Xiaochi Qu, 2022. "The Impact of Farming Households’ Livelihood Vulnerability on the Intention of Homestead Agglomeration: The Case of Zhongyi Township, China," Land, MDPI, vol. 11(8), pages 1-20, August.
    2. Xianjun Wang & Junfang Kang, 2023. "Decision Making and Influencing Factors in Withdrawal of Rural Residential Land-Use Rights in Suzhou, Anhui Province, China," Land, MDPI, vol. 12(2), pages 1-20, February.
    3. Cao, Qian & Sarker, Md Nazirul Islam & Sun, Jiangyan, 2019. "Model of the influencing factors of the withdrawal from rural homesteads in China: Application of grounded theory method," Land Use Policy, Elsevier, vol. 85(C), pages 285-289.
    4. Xiuling Ding & Qian Lu & Lipeng Li & Apurbo Sarkar & Hua Li, 2023. "Does Labor Transfer Improve Farmers’ Willingness to Withdraw from Farming?—A Bivariate Probit Modeling Approach," Land, MDPI, vol. 12(8), pages 1-27, August.
    5. Alam, Majbaul & Bhattacharyya, Subhes, 2017. "Are the off-grid customers ready to pay for electricity from the decentralized renewable hybrid mini-grids? A study of willingness to pay in rural Bangladesh," Energy, Elsevier, vol. 139(C), pages 433-446.
    6. Jia Gao & Ge Song & Shuhan Liu, 2022. "Factors influencing farmers’ willingness and behavior choices to withdraw from rural homesteads in China," Growth and Change, Wiley Blackwell, vol. 53(1), pages 112-131, March.
    7. Alla Koblyakova & Larisa Fleishman & Orly Furman, 2022. "Accuracy of Households’ Dwelling Valuations, Housing Demand and Mortgage Decisions: Israeli Case," The Journal of Real Estate Finance and Economics, Springer, vol. 65(1), pages 48-74, July.
    8. Yaoyang Zhao & Scott Cloutier & Hongqing Li, 2020. "Farmers’ Economic Status and Satisfaction with Homestead Withdrawal Policy: Expectation and Perceived Value," IJERPH, MDPI, vol. 17(19), pages 1-16, September.
    9. Mesbahuddin Ahmed & Anu Muhammad Anisur Rahman & Most Nilufa Khatun, 2020. "Empowerment of the Extreme Poor Women through Microfinance: Evidence from Northern Part of Bangladesh," Journal of Contemporary Research in Social Sciences, Michael Laurence, vol. 2(4), pages 68-80.
    10. Zhang, Yongchao & Torre, André & Ehrlich, Marianne, 2023. "The impact of Chinese government promoted homestead transfer on labor migration and household's well-being: A study in three rural areas," Journal of Asian Economics, Elsevier, vol. 86(C).
    11. Jiafang Jin & Xinyi Li & Guoxiu Liu & Xiaowen Dai & Ruiping Ran, 2024. "Analysis of Influencing Factors on Farmers’ Willingness to Pay for the Use of Residential Land Based on Supervised Machine Learning Algorithms," Land, MDPI, vol. 13(3), pages 1-20, March.
    12. Vinci, Sabato & Bartolacci, Francesca & Salvia, Rosanna & Salvati, Luca, 2022. "Housing markets, the great crisis, and metropolitan gradients: Insights from Greece, 2000–2014," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    13. Lei Zhu & Chenyujing Yang & Yuanyuan Zhang & Yongji Xue, 2022. "Using Marginal Land Resources to Solve the Shortage of Rural Entrepreneurial Land in China," Land, MDPI, vol. 11(7), pages 1-20, July.
    14. Yuan Yi & Kaifeng Duan & Fang He & Yuxuan Si, 2024. "The Effects and Mechanisms of the Rural Homestead System on the Imbalance of Rural Human–Land Relationships: Evidence from the Yangtze River Delta Urban Agglomeration in China," Land, MDPI, vol. 13(2), pages 1-19, January.
    15. Emily Schulte & Fabian Scheller & Daniel Sloot & Thomas Bruckner, 2021. "A meta-analysis of residential PV adoption: the important role of perceived benefits, intentions and antecedents in solar energy acceptance," Papers 2112.12464, arXiv.org.
    16. Wenxin Zhao & Yangbing Li & Qingrong Wang & Jing’an Shao, 2024. "Coupling Coordination Relationship and Spatiotemporal Heterogeneity between Functional Diversification and Settlement Evolution in Traditional Mountain Areas (2000–2020): A Case Study of Fengjie Count," Land, MDPI, vol. 13(7), pages 1-21, July.
    17. Li, Jing & Lo, Kevin & Zhang, Pingyu & Guo, Meng, 2021. "Reclaiming small to fill large: A novel approach to rural residential land consolidation in China," Land Use Policy, Elsevier, vol. 109(C).
    18. Ashwini K. Aggarwal & Asif Ali Syed & Sandeep Garg, 2021. "Diffusion of RT Solar PV in Suburbs of Delhi/NCR, India: Triggers of Architect Recommendation Intent," Vision, , vol. 25(3), pages 285-299, September.
    19. Su, Kangchuan & Hu, Baoqing & Shi, Kaifang & Zhang, Zhongxun & Yang, Qingyuan, 2019. "The structural and functional evolution of rural homesteads in mountainous areas: A case study of Sujiaying village in Yunnan province, China," Land Use Policy, Elsevier, vol. 88(C).
    20. Alipour, Mohammad & Taghikhah, Firouzeh & Irannezhad, Elnaz & Stewart, Rodney A. & Sahin, Oz, 2022. "How the decision to accept or reject PV affects the behaviour of residential battery system adopters," Applied Energy, Elsevier, vol. 318(C).

    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:jlands:v:11:y:2022:i:6:p:873-:d:834495. 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.