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

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  • 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
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    References listed on IDEAS

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    1. Tur-Sinai, Aviad & Fleishman, Larisa & Romanov, Dmitri, 2020. "The accuracy of self-reported dwelling valuation," Journal of Housing Economics, Elsevier, vol. 48(C).
    2. 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.
    3. 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).
    4. 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.
    5. 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).
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