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Spatial Patterns and Driving Forces of Greenhouse Land Change in Shouguang City, China

Author

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  • Bohua Yu

    (Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Wei Song

    (Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Yanqing Lang

    (Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Architecture and Urban Planning, Chongqing Jiaotong University, Chongqing 400074, China)

Abstract

As an important facet of modern agricultural development, greenhouses satisfy ever-increasing demands for agricultural production and, therefore, constitute a growing proportion of global agriculture. However, just a handful of countries regularly collect statistics on the land cover of greenhouse infrastructure. Even when collected, these data cannot provide the detailed spatial information required for environmental risk assessment. It is, therefore, important to map spatial changes in greenhouse land cover using remote sensing (RS) approaches to determine the underlying factors driving these changes. In this paper, we apply a support vector machine (SVM) algorithm to identify greenhouse land cover in Shouguang City, China. Enhanced thematic mapper (ETM) images were selected as the data source for land use classification in this study as they can be freely acquired and offer the necessary spatial resolution. We then used a binary logistic regression model to quantitatively discern the mechanisms underlying changes in greenhouse land cover. The results of this study show that greenhouse land cover in Shouguang increased by 50.51% between 2000 and 2015, and that 90.39% of this expansion took place between 2010 and 2015. Elevation, slope, precipitation, and the distance to the nearest rural settlements and coastline are all significant factors driving expansion in greenhouse land cover, while distance to the nearest urban areas, rivers, roads, railways, and coastline have contributed to contractions in this land use type. Our research provided a practical approach to allow the detection of changes in greenhouse land cover in the countries with using free or low-cost satellite images.

Suggested Citation

  • Bohua Yu & Wei Song & Yanqing Lang, 2017. "Spatial Patterns and Driving Forces of Greenhouse Land Change in Shouguang City, China," Sustainability, MDPI, vol. 9(3), pages 1-15, March.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:3:p:359-:d:91862
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    References listed on IDEAS

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    1. Bo Wen & Yunhua Pan & Yanyuan Zhang & Jingjie Liu & Min Xia, 2018. "Does the Exhaustion of Resources Drive Land Use Changes? Evidence from the Influence of Coal Resources-Exhaustion on Coal Resources–Based Industry Land Use Changes," Sustainability, MDPI, vol. 10(8), pages 1-13, August.
    2. Artur Nemś & Magdalena Nemś & Klaudia Świder, 2018. "Analysis of the Possibilities of Using a Heat Pump for Greenhouse Heating in Polish Climatic Conditions—A Case Study," Sustainability, MDPI, vol. 10(10), pages 1-23, September.
    3. Minghui Ou & Yexi Zhong & Hongzhi Ma & Wenhui Wang & Manyu Bi, 2022. "Impacts of Policy-Driven Transformation in the Livelihoods of Fishermen on Agricultural Landscape Patterns: A Case Study of a Fishing Village, Island of Poyang Lake," Land, MDPI, vol. 11(8), pages 1-16, August.
    4. Ge, Dazhuan & Wang, Zhihua & Tu, Shuangshuang & Long, Hualou & Yan, Huili & Sun, Dongqi & Qiao, Weifeng, 2019. "Coupling analysis of greenhouse-led farmland transition and rural transformation development in China’s traditional farming area: A case of Qingzhou City," Land Use Policy, Elsevier, vol. 86(C), pages 113-125.

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