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Research on the Assessment Method of Sugarcane Cultivation Suitability in Guangxi Province, China, Based on Multi-Source Data

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  • Senzheng Chen

    (Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin 541004, China
    China-ASEAN Regional Innovation Center for Big Earth Data, Nanning 530022, China)

  • Huichun Ye

    (Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin 541004, China
    China-ASEAN Regional Innovation Center for Big Earth Data, Nanning 530022, China)

  • Chaojia Nie

    (Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China)

  • Hongye Wang

    (Cultivated Land Quality Monitoring and Protection Center, Ministry of Agriculture and Rural Affairs, Beijing 100125, China)

  • Jingjing Wang

    (School of Forestry, Hainan University, Haikou 570228, China)

Abstract

Conducting suitability assessment for sugarcane cultivation is of great significance for optimizing the sugarcane cultivation structure and industrial layout. In this paper, based on the requirements of sugarcane growth and development on climate, terrain, and other environmental conditions, as well as the influence of natural disasters, a total of 11 specific indicators in terms of climate factor, terrain factor, and disaster factor were selected to construct a sugarcane cultivation suitability assessment system based on the analytic hierarchy process (AHP). Then, using Guangxi Province, China, as an example, a suitability assessment for sugarcane cultivation was conducted using multi-source data on climate, terrain, and hazards over the past 30 years. The results showed that among 11 indicators, including annual average temperature, elevation had the largest contribution rate, followed by precipitation during the period of ≥20 °C, slope, and the autumn drought frequency. From the spatial distribution, 37% of the provincial regions were suitable for sugarcane cultivation, mainly distributed in Chongzuo City, Nanning City, Qinzhou City, and Beihai City. In total, 44% of the provincial regions were moderately suitable for sugarcane cultivation, mainly distributed in Hezhou City, Laibin City, and Liuzhou City. Additionally, only 19% of the provincial regions were unsuitable for sugarcane cultivation, mainly distributed in Baise City, Hechi City, and Guilin City, with the terrain factor being the main influencing factor of sugarcane suitability assessment. In order to make reasonable use of land resources and increase sugarcane yield, it is suggested that sugarcane cultivation areas should be adjusted to the central and southern regions such as Chongzuo City, Nanning City, Beihai City, and Qinzhou City, and other industries should be developed in the northern regions which are not suitable for sugarcane cultivation.

Suggested Citation

  • Senzheng Chen & Huichun Ye & Chaojia Nie & Hongye Wang & Jingjing Wang, 2023. "Research on the Assessment Method of Sugarcane Cultivation Suitability in Guangxi Province, China, Based on Multi-Source Data," Agriculture, MDPI, vol. 13(5), pages 1-17, April.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:5:p:988-:d:1136800
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    References listed on IDEAS

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    1. Wang, Sheng & Lian, Jinjiao & Peng, Yuzhong & Hu, Baoqing & Chen, Hongsong, 2019. "Generalized reference evapotranspiration models with limited climatic data based on random forest and gene expression programming in Guangxi, China," Agricultural Water Management, Elsevier, vol. 221(C), pages 220-230.
    2. Daniel Nohrstedt & Maurizio Mazzoleni & Charles F. Parker & Giuliano Baldassarre, 2021. "Exposure to natural hazard events unassociated with policy change for improved disaster risk reduction," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    3. R. Duncan McIntosh & Austin Becker, 2020. "Applying MCDA to weight indicators of seaport vulnerability to climate and extreme weather impacts for U.S. North Atlantic ports," Environment Systems and Decisions, Springer, vol. 40(3), pages 356-370, September.
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    Cited by:

    1. Yifang Zhou & Mingzhang Pan & Wei Guan & Changcheng Fu & Tiecheng Su, 2023. "Predicting Sugarcane Yield via the Use of an Improved Least Squares Support Vector Machine and Water Cycle Optimization Model," Agriculture, MDPI, vol. 13(11), pages 1-23, November.

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