IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i10p3676-d175579.html
   My bibliography  Save this article

Spatial Pattern of Farmland Abandonment in Japan: Identification and Determinants

Author

Listed:
  • Guandong Su

    (Department of Geography, Division of Humanities, Graduate School of Letters, Hiroshima University, Hiroshima 739-8522, Japan)

  • Hidenori Okahashi

    (Department of Geography, Faculty of Letters, Nara University, Nara 631-8502, Japan)

  • Lin Chen

    (Department of Geography, Division of Humanities, Graduate School of Letters, Hiroshima University, Hiroshima 739-8522, Japan
    National Institutes for the Humanities, Tokyo 105-0001, Japan)

Abstract

In recent years, Japan has undergone an unprecedented increase in farmland abandonment, which not only causes serious environmental problems and rural landscape loss, but also has a significant impact on socio-economic conditions and the livelihood of Japanese farmers. Many studies have analyzed farmland abandonment and its processes and drivers at multiple scales; however, few have focused on East Asia, especially Japan, which is a heavily depopulated country in rural areas suffering from serious abandonment. Therefore, this study attempts to shed light on the spatial patterns and determinants of farmland abandonment in Japan. For this analysis, we used the former municipalities defined in 1950 at a national scale as unit samples. Consequently, the spatial patterns, characteristics and variations of farmland abandonment in Japan are displayed. As for the drivers or determinants, we adopted ordinary least squares (OLS) and geographically weighted regression (GWR) by categorizing the determinants into geographical and socio-economic aspects. We have found that, firstly, farmland abandonment in Japan exhibits a significantly uneven pattern. While taking the farmland abandonment rate as a measurement, the results demonstrate that most abandoned farmland is positively correlated with slope and is highly clustered in the Kanto, Chubu and Chugoku Shikoku regions, compared to other regions that are suitable for agricultural production, such as the Hokkaido and Tohoku regions. Secondly, the arable land ratio of self-sufficient farm households, the ratio of non-successor farm households and the number of laborers per farm household positively affect abandonment. In contrast, arable land area per farm household and paddy field density have a negative impact on abandonment. Thirdly, the determinants are spatially varied among study regions. Farmland abandonment is driven by interactions of multiple determinants and depends on specific local circumstances. Such results can contribute to the understanding of farmland abandonment in Japan, promoting the maintenance of farmland and sustainable agriculture.

Suggested Citation

  • Guandong Su & Hidenori Okahashi & Lin Chen, 2018. "Spatial Pattern of Farmland Abandonment in Japan: Identification and Determinants," Sustainability, MDPI, vol. 10(10), pages 1-22, October.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:10:p:3676-:d:175579
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/10/3676/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/10/10/3676/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Löw, Fabian & Prishchepov, Alexander V. & Waldner, François & Dubovyk, Olena & Akramkhanov, Akmal & Biradar, Chandrashekhar & Lamers, John P., 2018. "Mapping cropland abandonment in the Aral Sea Basin with MODIS time series," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 10(2), pages 1-24.
    2. Deininger, Klaus & Savastano, Sara & Carletto, Calogero, 2012. "Land Fragmentation, Cropland Abandonment, and Land Market Operation in Albania," World Development, Elsevier, vol. 40(10), pages 2108-2122.
    3. Müller, Daniel & Leitão, Pedro J. & Sikor, Thomas, 2013. "Comparing the determinants of cropland abandonment in Albania and Romania using boosted regression trees," Agricultural Systems, Elsevier, vol. 117(C), pages 66-77.
    4. Hualin Xie & Peng Wang & Guanrong Yao, 2014. "Exploring the Dynamic Mechanisms of Farmland Abandonment Based on a Spatially Explicit Economic Model for Environmental Sustainability: A Case Study in Jiangxi Province, China," Sustainability, MDPI, vol. 6(3), pages 1-23, March.
    5. Chiou, Yu-Chiun & Jou, Rong-Chang & Yang, Cheng-Han, 2015. "Factors affecting public transportation usage rate: Geographically weighted regression," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 161-177.
    6. Renwick, Alan W. & Jansson, Torbjorn & Verburg, Peter H. & Revoredo-Giha, Cesar & Britz, Wolfgang & Gocht, Alexander & McCracken, Davy, 2011. "Policy Reform and Agricultural Land Abandonment," 85th Annual Conference, April 18-20, 2011, Warwick University, Coventry, UK 108772, Agricultural Economics Society.
    7. Prishchepov, Alexander V. & Radeloff, Volker C. & Müller, Daniel & Dubinin, Maxim & Baumann, Matthias, 2011. "Determinants of agricultural land abandonment in post-soviet European Russia," IAMO Forum 2011: Will the "BRICs Decade" Continue? – Prospects for Trade and Growth 1, Leibniz Institute of Agricultural Development in Central and Eastern Europe (IAMO).
    8. Pirdavani, Ali & Bellemans, Tom & Brijs, Tom & Kochan, Bruno & Wets, Geert, 2014. "Assessing the road safety impacts of a teleworking policy by means of geographically weighted regression method," Journal of Transport Geography, Elsevier, vol. 39(C), pages 96-110.
    9. Heller, Peter S., 2016. "The challenge of an aged and shrinking population: Lessons to be drawn from Japan’s experience," The Journal of the Economics of Ageing, Elsevier, vol. 8(C), pages 85-93.
    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. Xin Deng & Dingde Xu & Miao Zeng & Yanbin Qi, 2018. "Landslides and Cropland Abandonment in China’s Mountainous Areas: Spatial Distribution, Empirical Analysis and Policy Implications," Sustainability, MDPI, vol. 10(11), pages 1-14, October.
    2. Carolina Perpiña Castillo & Eloína Coll Aliaga & Carlo Lavalle & José Carlos Martínez Llario, 2020. "An Assessment and Spatial Modelling of Agricultural Land Abandonment in Spain (2015–2030)," Sustainability, MDPI, vol. 12(2), pages 1-23, January.
    3. Alexander V. Prishchepov & Florian Schierhorn & Fabian Löw, 2021. "Unraveling the Diversity of Trajectories and Drivers of Global Agricultural Land Abandonment," Land, MDPI, vol. 10(2), pages 1-8, January.
    4. Wojciech Sroka & Bernd Pölling & Tomasz Wojewodzic & Miroslaw Strus & Paulina Stolarczyk & Olga Podlinska, 2019. "Determinants of Farmland Abandonment in Selected Metropolitan Areas of Poland: A Spatial Analysis on the Basis of Regression Trees and Interviews with Experts," Sustainability, MDPI, vol. 11(11), pages 1-23, May.
    5. Castro, P. & Pedroso, R. & Lautenbach, S. & Vicens, R., 2020. "Farmland abandonment in Rio de Janeiro: Underlying and contributory causes of an announced development," Land Use Policy, Elsevier, vol. 95(C).
    6. Han Li & Wei Song, 2021. "Cropland Abandonment and Influencing Factors in Chongqing, China," Land, MDPI, vol. 10(11), pages 1-21, November.
    7. Zheng, Linyi, 2024. "Big hands holding small hands: The role of new agricultural operating entities in farmland abandonment," Food Policy, Elsevier, vol. 123(C).
    8. Subedi, Yuba Raj & Kristiansen, Paul & Cacho, Oscar, 2022. "Reutilising abandoned cropland in the Hill agroecological region of Nepal: Options and farmers’ preferences," Land Use Policy, Elsevier, vol. 117(C).
    9. Thiagu Ranganathan & Ghanshyam Pandey, 2018. "Who Leaves Farmland Fallow and Why? An Empirical Investigation Using Nationally Representative Survey Data from India," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 30(5), pages 914-933, December.
    10. Robert Pazúr & Juraj Lieskovský & Matthias Bürgi & Daniel Müller & Tibor Lieskovský & Zhen Zhang & Alexander V. Prishchepov, 2020. "Abandonment and Recultivation of Agricultural Lands in Slovakia—Patterns and Determinants from the Past to the Future," Land, MDPI, vol. 9(9), pages 1-22, September.
    11. Suresh Chaudhary & Yukuan Wang & Amod Mani Dixit & Narendra Raj Khanal & Pei Xu & Bin Fu & Kun Yan & Qin Liu & Yafeng Lu & Ming Li, 2020. "A Synopsis of Farmland Abandonment and Its Driving Factors in Nepal," Land, MDPI, vol. 9(3), pages 1-22, March.
    12. Ionuț Săvulescu & Bogdan-Andrei Mihai & Marina Vîrghileanu & Constantin Nistor & Bogdan Olariu, 2019. "Mountain Arable Land Abandonment (1968–2018) in the Romanian Carpathians: Environmental Conflicts and Sustainability Issues," Sustainability, MDPI, vol. 11(23), pages 1-11, November.
    13. Buting Hong & Jicheng Wang & Jiangtao Xiao & Quanzhi Yuan & Ping Ren, 2025. "Spatiotemporal Patterns and Determinants of Cropland Abandonment in Mountainous Regions of China: A Case Study of Sichuan Province," Land, MDPI, vol. 14(3), pages 1-25, March.
    14. Jiang Du & Miao Zeng & Zhengjuan Xie & Shikun Wang, 2019. "Power of Agricultural Credit in Farmland Abandonment: Evidence from Rural China," Land, MDPI, vol. 8(12), pages 1-14, December.
    15. David Fernández-Nogueira & Eduardo Corbelle-Rico, 2019. "Determinants of Land Use/Cover Change in the Iberian Peninsula (1990–2012) at Municipal Level," Land, MDPI, vol. 9(1), pages 1-12, December.
    16. Wei Song, 2019. "Mapping Cropland Abandonment in Mountainous Areas Using an Annual Land-Use Trajectory Approach," Sustainability, MDPI, vol. 11(21), pages 1-24, October.
    17. Daquan Huang & Haoran Jin & Xingshuo Zhao & Shenghe Liu, 2014. "Factors Influencing the Conversion of Arable Land to Urban Use and Policy Implications in Beijing, China," Sustainability, MDPI, vol. 7(1), pages 1-15, December.
    18. Guo Chen & Amy K Glasmeier & Min Zhang & Yang Shao, 2016. "Urbanization and Income Inequality in Post-Reform China: A Causal Analysis Based on Time Series Data," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-16, July.
    19. Wojciech Sroka & Jaroslaw Mikolajczyk & Tomasz Wojewodzic & Boguslawa Kwoczynska, 2018. "Agricultural Land vs. Urbanisation in Chosen Polish Metropolitan Areas: A Spatial Analysis Based on Regression Trees," Sustainability, MDPI, vol. 10(3), pages 1-22, March.
    20. Akash Malhotra, 2018. "A hybrid econometric-machine learning approach for relative importance analysis: Prioritizing food policy," Papers 1806.04517, arXiv.org, revised Aug 2020.

    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:jsusta:v:10:y:2018:i:10:p:3676-:d:175579. 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.