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An Integrated Modeling Framework to Understand Agricultural Land-Use Changes at a Global-scale

机译:理解全球范围内农业土地利用变化的综合建模框架

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摘要

This paper presents an integrated agricultural land-use change model to simulate past and future dynamic changes in sown areas for four major crops at a global scale.This modeling approach,including four core models,was developed under the framework of Action-in-Context (AiC).The crop choice decision model,a Multinomial Logit model was used to model the crop choice decisions among a variety of available alternatives by using a crop utility function.A crop yield model,the GIS-based EPIC model was adopted to estimate the potential yields of different crop types under a given biophysical and agricultural management environment.A crop price model,the IFPSIM model was utilized to evaluate the price of the test crops in the international market.An urban expansion model was constructed to examine the characteristics of urban land expansion and the consequent cropland loss,and to dynamically update the total percentage of land available for agricultural land use.These models were seamlessly linked through data flow and exchange between them,and the dynamic feedback loop between agricultural land-use change and biophysical and socio-economic driving factors was studied.Empirical validation for the model conducted after model construction indicated the reliability of the model for addressing the complexity of current agricultural land-use change and its capacity for investigating long-term scenarios in the future.
机译:本文提出了一个综合的农业土地利用变化模型,以模拟全球范围内四种主要农作物的播种面积过去和将来的动态变化。这种建模方法是在情境行动框架下开发的,包括四个核心模型(AiC)。使用作物效用函数,使用多项式Lo​​git模型对多种可用替代方案中的作物选择决策进行建模。使用作物产量模型,基于GIS的EPIC模型进行估算在给定的生物物理和农业管理环境下,不同作物类型的潜在产量。使用作物价格模型,IFPSIM模型评估国际市场上试验作物的价格。构建城市扩张模型以检验作物的特征。这些模型是无缝的,可用于城市土地扩张和随之而来的耕地流失,并动态更新可用于农业用地的土地总百分比。通过数据流和数据交换之间的交换,研究了农业土地利用变化与生物物理和社会经济驱动因素之间的动态反馈环。模型构建后进行的模型验证表明,该模型解决复杂性的可靠性当前农业土地利用变化及其在未来长期情景调查中的能力。

著录项

  • 来源
  • 会议地点 Beijing(CN)
  • 作者单位

    Key Laboratory of Resources Remote Sensing Digital Agriculture,Ministry of Agriculture,Beijing 100081,China;

    Institute of Agricultural Resources and Regional Planning,Chinese Academy of Agricultural Sciences,Beijing 100081,China;

    Key Laboratory of Resources Remote Sensing Digital Agriculture,Ministry of Agriculture,Beijing 100081,China;

    Institute of Agricultural Resources and Regional Planning,Chinese Academy of Agricultural Sciences,Beijing 100081,China;

    Key Laboratory of Resources Remote Sensing Digital Agriculture,Ministry of Agriculture,Beijing 100081,China;

    Institute of Agricultural Resources and Regional Planning,Chinese Academy of Agricultural Sciences,Beijing 100081,China;

    Key Laboratory of Resources Remote Sensing Digital Agriculture,Ministry of Agriculture,Beijing 100081,China;

    Institute of Agricultural Resources and Regional Planning,Chinese Academy of Agricultural Sciences,Beijing 100081,China;

    Center for Spatial Information Science,University of Tokyo,Tokyo 153-8505,Japan;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 土壤学;
  • 关键词

    Sown area change; modeling; crop choice decision; yield; global scale;

    机译:播种面积变化;建模;作物​​选择决策;产量;全球规模;

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