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Assessment of Potential Land Suitability for Tea ( Camellia sinensis (L.) O. Kuntze) in Sri Lanka Using a GIS-Based Multi-Criteria Approach

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  • Sadeeka Layomi Jayasinghe

    (School of Environmental and Rural Science, University of New England, Armidale, NSW 2351, Australia
    Department of Export Agriculture, Faculty of Animal Science and Export Agriculture, Uva Wellassa University, Passara Road, Badulla 90000, Sri Lanka)

  • Lalit Kumar

    (School of Environmental and Rural Science, University of New England, Armidale, NSW 2351, Australia)

  • Janaki Sandamali

    (Department of oceanography and marine geology, Faculty of Fisheries and Marine Sciences & Technology, University of Ruhuna, Matara 81000, Sri Lanka)

Abstract

The potential land suitability assessment for tea is a crucial step in determining the environmental limits of sustainable tea production. The aim of this study was to assess land suitability to determine suitable agricultural land for tea crops in Sri Lanka. Climatic, topographical and soil factors assumed to influence land use were assembled and the weights of their respective contributions to land suitability for tea were assessed using the Analytical Hierarchical Process (AHP) and the Decision-Making Trail and Evaluation Laboratory (DEMATEL) model. Subsequently, all the factors were integrated to generate the potential land suitability map. The results showed that the largest part of the land in Sri Lanka was occupied by low suitability class (42.1%) and 28.5% registered an unsuitable land cover. Furthermore, 12.4% was moderately suitable, 13.9% was highly suitable and 2.5% was very highly suitable for tea cultivation. The highest proportion of “very highly suitable” areas were recorded in the Nuwara Eliya District, which accounted for 29.50% of the highest category. The model validation results showed that 92.46% of the combined “highly suitable” and “very highly suitable” modelled classes are actual current tea-growing areas, showing the overall robustness of this model and the weightings applied. This result is significant in that it provides effective approaches to enhance land-use efficiency and better management of tea production.

Suggested Citation

  • Sadeeka Layomi Jayasinghe & Lalit Kumar & Janaki Sandamali, 2019. "Assessment of Potential Land Suitability for Tea ( Camellia sinensis (L.) O. Kuntze) in Sri Lanka Using a GIS-Based Multi-Criteria Approach," Agriculture, MDPI, vol. 9(7), pages 1-25, July.
    • Handle: RePEc:gam:jagris:v:9:y:2019:i:7:p:148-:d:246630
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    References listed on IDEAS

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    1. Seo, Sung-No Niggol & Mendelsohn, Robert & Munasinghe, Mohan, 2005. "Climate change and agriculture in Sri Lanka: a Ricardian valuation," Environment and Development Economics, Cambridge University Press, vol. 10(5), pages 581-596, October.
    2. Xinyi Zhou & Yong Hu & Yong Deng & Felix T. S. Chan & Alessio Ishizaka, 2018. "A DEMATEL-based completion method for incomplete pairwise comparison matrix in AHP," Annals of Operations Research, Springer, vol. 271(2), pages 1045-1066, December.
    3. Herath, Deepananda & Weersink, Alfons, 2009. "From Plantations to Smallholder Production: The Role of Policy in the Reorganization of the Sri Lankan Tea Sector," World Development, Elsevier, vol. 37(11), pages 1759-1772, November.
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    Cited by:

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    6. S. Abdul Rahaman & S. Aruchamy, 2022. "Land Suitability Evaluation of Tea ( Camellia sinensis L.) Plantation in Kallar Watershed of Nilgiri Bioreserve, India," Geographies, MDPI, vol. 2(4), pages 1-23, November.
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    8. Mateusz Ciski & Krzysztof Rząsa & Marek Ogryzek, 2019. "Use of GIS Tools in Sustainable Heritage Management—The Importance of Data Generalization in Spatial Modeling," Sustainability, MDPI, vol. 11(20), pages 1-21, October.
    9. Ying Han & Yongjian He & Zhuoran Liang & Guoping Shi & Xiaochen Zhu & Xinfa Qiu, 2023. "Risk Assessment and Application of Tea Frost Hazard in Hangzhou City Based on the Random Forest Algorithm," Agriculture, MDPI, vol. 13(2), pages 1-14, January.
    10. Shouqiang Yin & Jing Li & Jiaxin Liang & Kejing Jia & Zhen Yang & Yuan Wang, 2020. "Optimization of the Weighted Linear Combination Method for Agricultural Land Suitability Evaluation Considering Current Land Use and Regional Differences," Sustainability, MDPI, vol. 12(23), pages 1-25, December.

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