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基于GIS的复种指数潜力研究

A Study on Cropping Index Potential Based on GIS

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【作者】 范锦龙吴炳方

【Author】 FAN Jin-long,WU Bing-fang (Institute of Remote Sensing Applications,CAS,Beijing 100101,China)

【机构】 中国科学院遥感应用研究所中国科学院遥感应用研究所 北京100101北京100101

【摘要】 复种指数对农业生产具有重要意义 ,通过计算复种指数潜力可以对未来粮食生产潜力进行预测。本文提出基于GIS技术的复种指数潜力计算方法。在GIS软件的支持下 ,分析全国农业统计数据 ,使用遥感数据修正全国县级耕地面积统计数据 ,进而计算各县最大复种指数 ,同时收集并处理气象数据。通过分析最大复种指数与积温、降水和日照时数的关系 ,提出以外包络法构建复种指数潜力模型。利用建立的复种指数潜力模型计算全国 1km尺度的复种指数潜力 ,并使用空间统计方法得到全国及分省的复种指数潜力。全国复种指数潜力为 198 5 %。

【Abstract】 Cropping index is a very important indicator. Food production potential in the future can be forecasted by the cropping index potential. However,there were little studies on the cropping index potential. Several references estimated the cropping index potential over China by the very simple means or with the provincial statistical data. The results were different. This paper put forward the methods of calculating cropping index potential based on GIS technology. The agricultural statistical data were processed. The statistical data of the area of arable land of each county were replaced by the data of the area of arable land extracted from remotely sensed data due to the quality of the statistical data. The maximum of cropping index of each county then was calculated further. The climatic data were collected and processed, too. After analyzing the relationship between the maximum of cropping index and the accumulated temperature, precipitation and sun hour data, this paper put forward the model of cropping index potential by the means of the outside envelope. Then this paper calculated the cropping index potential over China with 1 km resolution based on the model the paper proposed. The cropping index potential of the whole China and each province were obtained by using the spatial statistical methods. According to the results, the cropping index potential of the whole China is 198.5%.

【关键词】 复种指数潜力GIS积温降水
【Key words】 cropping index potentialGISaccumulated temperatureprecipitation
【基金】 科技部国家十五科技攻关课题“农业信息资源开发与共享技术研究”(2001BA513B02);中国科学院知识创新工程重要方向项目:全球农作物遥感估产研究(KZCX2313)
  • 【文献出处】 遥感学报 ,Journal of Remote Sensing , 编辑部邮箱 ,2004年06期
  • 【分类号】S12
  • 【被引频次】91
  • 【下载频次】728
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