IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i1p419-d1312443.html
   My bibliography  Save this article

Improvement of the Methodology for the Assessment of the Agro-Resource Potential of Agricultural Landscapes

Author

Listed:
  • Zhumakhan Mustafayev

    (Department of Landscape Study and Problems of Nature Management, Institute of Geography and Water Security Science Committee, Almaty 050000, Kazakhstan)

  • Akhmetkal Medeu

    (Department of Landscape Study and Problems of Nature Management, Institute of Geography and Water Security Science Committee, Almaty 050000, Kazakhstan)

  • Irina Skorintseva

    (Department of Landscape Study and Problems of Nature Management, Institute of Geography and Water Security Science Committee, Almaty 050000, Kazakhstan)

  • Tatiana Bassova

    (Department of Landscape Study and Problems of Nature Management, Institute of Geography and Water Security Science Committee, Almaty 050000, Kazakhstan)

  • Gulnar Aldazhanova

    (Department of Landscape Study and Problems of Nature Management, Institute of Geography and Water Security Science Committee, Almaty 050000, Kazakhstan)

Abstract

The purpose of this study was the scientific justification of the concept of assessment of the agro-resource potential of agricultural landscapes and the improvement of the methodology for such assessment, on the basis of knowledge integration principles that allow for the combining of various fields of science in order to create an integrated methodological approach to addressing scientific and practical problems of environmental management. Based on the analysis of modern worldviews and natural scientific ideas on the mechanisms of biomass production in natural systems, we propose a methodology for the assessment of the agro-resource potential of agricultural landscapes that is an integral function of four key components (groups of factors)—agroclimatic resources (ACR), soil–land resources (SLR), agrobiological resources (ABR) and water resources (WR)—and that is based on the laws of nature and the principles of agricultural nature management. The proposed algorithm for predicting the natural state of agricultural landscapes based on agroclimatic, agrochemical and agrobiological integrated indexes allowed us to develop a unified integrated approach to the methodology for the assessment of the agro-resource potential of agricultural landscapes that makes it possible to determine the logical sequence of the trend of changes in the natural process, fully characterizing its state in the space–time scale.

Suggested Citation

  • Zhumakhan Mustafayev & Akhmetkal Medeu & Irina Skorintseva & Tatiana Bassova & Gulnar Aldazhanova, 2024. "Improvement of the Methodology for the Assessment of the Agro-Resource Potential of Agricultural Landscapes," Sustainability, MDPI, vol. 16(1), pages 1-16, January.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:1:p:419-:d:1312443
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/1/419/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/1/419/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hajkowicz, Stefan, 2006. "Multi-attributed environmental index construction," Ecological Economics, Elsevier, vol. 57(1), pages 122-139, April.
    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. Cook, David & Proctor, Wendy, 2007. "Assessing the threat of exotic plant pests," Ecological Economics, Elsevier, vol. 63(2-3), pages 594-604, August.
    2. H. K. Millington & J. E. Lovell & C. A. K. Lovell, 2013. "Using Fieldwork, GIS and DEA to Guide Management of Urban Stream Health," CEPA Working Papers Series WP072013, School of Economics, University of Queensland, Australia.
    3. Franciely Velozo Aragão & Daiane Maria de Genaro Chiroli & Fernanda Cavicchioli Zola & Emanuely Velozo Aragão & Luis Henrique Nogueira Marinho & Ana Lidia Cascales Correa & João Carlos Colmenero, 2023. "Smart Cities Maturity Model—A Multicriteria Approach," Sustainability, MDPI, vol. 15(8), pages 1-20, April.
    4. Loureiro, Maria L. & Dominguez Arcos, Fernando, 2012. "Applying Best–Worst Scaling in a stated preference analysis of forest management programs," Journal of Forest Economics, Elsevier, vol. 18(4), pages 381-394.
    5. Agustí Pérez-Foguet & Ricard Giné Garriga, 2011. "Analyzing Water Poverty in Basins," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(14), pages 3595-3612, November.
    6. Sydorovych, Olha & Wossink, Ada, 2008. "An Application of Conjoint Analysis in Agricultural Sustainability Assessment," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44464, European Association of Agricultural Economists.
    7. O. Flores Baquero & J. Gallego-Ayala & R. Giné-Garriga & A. Jiménez-Fernández. Palencia & A. Pérez-Foguet, 2017. "The Influence of the Human Rights to Water and Sanitation Normative Content in Measuring the Level of Service," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 133(2), pages 763-786, September.
    8. Galdeano-Gómez, E. & Aznar-Sánchez, J.A. & Pérez-Mesa, J.C. & Piedra-Muñoz, L., 2017. "Exploring Synergies Among Agricultural Sustainability Dimensions: An Empirical Study on Farming System in Almería (Southeast Spain)," Ecological Economics, Elsevier, vol. 140(C), pages 99-109.
    9. Ju, Keyi & Su, Bin & Zhou, Dequn & Zhou, P. & Zhang, Yuqiang, 2015. "Oil price crisis response: Capability assessment and key indicator identification," Energy, Elsevier, vol. 93(P2), pages 1353-1360.
    10. Forio, Marie Anne Eurie & Landuyt, Dries & Bennetsen, Elina & Lock, Koen & Nguyen, Thi Hanh Tien & Ambarita, Minar Naomi Damanik & Musonge, Peace Liz Sasha & Boets, Pieter & Everaert, Gert & Dominguez, 2015. "Bayesian belief network models to analyse and predict ecological water quality in rivers," Ecological Modelling, Elsevier, vol. 312(C), pages 222-238.
    11. Marko Kallio & Joseph H. A. Guillaume & Matti Kummu & Kirsi Virrantaus, 2018. "Spatial Variation in Seasonal Water Poverty Index for Laos: An Application of Geographically Weighted Principal Component Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 140(3), pages 1131-1157, December.
    12. Prabal Barua & Syed Hafizur Rahman & Suman Barua & Ismail M.M. Rahman, 2020. "Climate Change Vulnerability And Responses Of Fisherfolk Communities In The South-Eastern Coast Of Bangladesh," Water Conservation & Management (WCM), Zibeline International Publishing, vol. 4(1), pages 20-31, March.
    13. Salvatore Ammirato & Gerarda Fattoruso & Antonio Violi, 2022. "Parsimonious AHP-DEA Integrated Approach for Efficiency Evaluation of Production Processes," JRFM, MDPI, vol. 15(7), pages 1-15, June.
    14. Gómez-Limón, José A. & Sanchez-Fernandez, Gabriela, 2010. "Empirical evaluation of agricultural sustainability using composite indicators," Ecological Economics, Elsevier, vol. 69(5), pages 1062-1075, March.
    15. Hatefi, S.M. & Torabi, S.A., 2010. "A common weight MCDA-DEA approach to construct composite indicators," Ecological Economics, Elsevier, vol. 70(1), pages 114-120, November.
    16. Caroline A Sullivan & Hatem Jemmali, 2014. "Toward Understanding Water Conflicts in MENA Region: A Comparative Analysis Using Water Poverty Index," Working Papers 859, Economic Research Forum, revised Nov 2014.
    17. Hatem Jemmali & Caroline Sullivan, 2014. "Multidimensional Analysis of Water Poverty in MENA Region: An Empirical Comparison with Physical Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 115(1), pages 253-277, January.
    18. Zhou, P. & Ang, B.W. & Poh, K.L., 2007. "A mathematical programming approach to constructing composite indicators," Ecological Economics, Elsevier, vol. 62(2), pages 291-297, April.
    19. Hatem Jemmali, 2018. "Water Poverty in Africa: A Review and Synthesis of Issues, Potentials, and Policy Implications," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(1), pages 335-358, February.
    20. Blancas, Francisco J. & Caballero, Rafael & González, Mercedes & Lozano-Oyola, Macarena & Pérez, Fátima, 2010. "Goal programming synthetic indicators: An application for sustainable tourism in Andalusian coastal counties," Ecological Economics, Elsevier, vol. 69(11), pages 2158-2172, September.

    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:16:y:2024:i:1:p:419-:d:1312443. 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.