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Spatial Distribution and Influencing Factors of Daylily Cultivation in the Farming–Pastoral Ecotone of Northern China

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  • Jingjing Peng

    (College of Resource and Environment, Shanxi Agricultural University, Jinzhong 030801, China)

  • Shuai Li

    (College of Resource and Environment, Shanxi Agricultural University, Jinzhong 030801, China)

  • Xingrong Ma

    (College of Resource and Environment, Shanxi Agricultural University, Jinzhong 030801, China)

  • Haoxi Ding

    (College of Resource and Environment, Shanxi Agricultural University, Jinzhong 030801, China)

  • Wenjing Fang

    (College of Resource and Environment, Shanxi Agricultural University, Jinzhong 030801, China)

  • Rutian Bi

    (College of Resource and Environment, Shanxi Agricultural University, Jinzhong 030801, China
    Datong Daylily Industrial Development Research Institute, Datong 037004, China)

Abstract

The farming–pastoral ecotone in northern China is an ecologically vulnerable area with low-quality arable land, and cash crops are an important economic source for local farmers. Although local governments have introduced supportive policies, there are still several factors that hinder the implementation of the policies: there is a lack of sufficient research on the distribution of specialty crops, and the driving factors for agricultural planting structure adjustment are not yet clear. In this study, the specialty cash crop of the daylily planting industry in Yunzhou District, in the Farming–Pastoral Ecotone in northern China, was selected as the research object. Field surveys were conducted to collect sample points and village-level survey data, which were further combined with Sentinel-1 and Sentinel-2 data, and vegetation indices. Support vector machine (SVM) and random forest (RF) classifiers were utilized to identify daylilies and compare the accuracy using different combinations of input data. Furthermore, the classification results were counted by village, and spatial autocorrelation was used to analyze the spatial distribution pattern of daylilies. Finally, in conjunction with the village-level survey data, Spearman correlation analysis, multiple regression trees (MRT), and random forests were employed to explore the driving factors of daylily cultivation. The results indicate that using an RF classification tree of 300 resulted in the optimal method, as it achieved the highest accuracy for crop classification. The overall accuracy and daylily classification accuracy were 94.6% and 94.75%, respectively. Daylily distributions were mainly concentrated near the Sanggan River, urban areas, and the tourism industry. The distribution area of daylilies in each village was concentrated in 13.4–38.8 hm 2 . Spatial clustering showed more aggregation of low–low and high–high types. Labor force and daylily yield were identified as the most significant influencing factors. Further analysis of the different regions revealed the importance of industry support policies and technical training. This study provides data to support the distribution of specialty crops in Yunzhou District and a technical basis for adjusting agricultural planting structures.

Suggested Citation

  • Jingjing Peng & Shuai Li & Xingrong Ma & Haoxi Ding & Wenjing Fang & Rutian Bi, 2024. "Spatial Distribution and Influencing Factors of Daylily Cultivation in the Farming–Pastoral Ecotone of Northern China," Land, MDPI, vol. 13(4), pages 1-22, March.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:4:p:439-:d:1367217
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    References listed on IDEAS

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    1. Marcel Fafchamps & Forhad Shilpi, 2003. "The spatial division of labour in Nepal," Journal of Development Studies, Taylor & Francis Journals, vol. 39(6), pages 23-66.
    2. Govereh, Jones & Jayne, T. S., 2003. "Cash cropping and food crop productivity: synergies or trade-offs?," Agricultural Economics, Blackwell, vol. 28(1), pages 39-50, January.
    3. Shiwei Liu & Pingyu Zhang & Ben Marley & Wenxin Liu, 2019. "The Factors Affecting Farmers’ Soybean Planting Behavior in Heilongjiang Province, China," Agriculture, MDPI, vol. 9(9), pages 1-13, September.
    4. Ge Song & Hongmei Zhang, 2021. "Cultivated Land Use Layout Adjustment Based on Crop Planting Suitability: A Case Study of Typical Counties in Northeast China," Land, MDPI, vol. 10(2), pages 1-19, January.
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