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中国农学通报 ›› 2010, Vol. 26 ›› Issue (14): 364-364.

所属专题: 现代农业发展与乡村振兴 农业气象

• 工程 机械 水利 装备 • 上一篇    下一篇

GIS技术在中国农业气候区划中的应用进展

王连喜 李欣   

  • 收稿日期:2010-03-03 修回日期:2010-03-30 出版日期:2010-07-20 发布日期:2010-07-20
  • 基金资助:
    中国气象局公益性行业(气象)科研专项

Application progress of GIS for Agro-climatic division in China

  • Received:2010-03-03 Revised:2010-03-30 Online:2010-07-20 Published:2010-07-20

摘要: 地理信息系统(GIS)的空间分析功能与传统区划方法的结合,可以得到更加精细的农业气候区划结果,其作为一种技术手段已经广泛应用于农业气候区划,为当地农业生产决策提供可靠的依据。笔者着重从气候要素细网格化、区划成果数字化、信息服务、“3S”技术相结合等四个方面,总结GIS技术在中国农业气候区划中的应用进展,对应用中所存在的问题进行分析讨论,提出将来可能的研究方向,以期对该领域的研究提供参考。几点建议如下:(1)进行农业气候区划时应综合考虑多种自然环境因素和社会因子;(2)运用GIS技术进行“自下而上”的区域合并过程中,需要更好地结合自动合并与人工合并;(3)区划指标应考虑运用逻辑交集运算;(4)建立基于Web技术的开放式共享GIS农业气候区划平台;(5)GIS结合GPS、卫星遥感数据可以从宏观的角度全面监测农作物的整个生长发育过程,对指导农业生产具有重要的应用价值。

关键词: 大豆, 大豆, 栽培模式, 关键技术

Abstract: The spatial analysis functions of Geographic Information System (GIS) combined with the traditional zoning methods could get more precise results of agro-climatic division. GIS as a kind of technological means has been widely used in agro-climatic division, which provide a reliable basis for making a decision of agricultural production. Summing up the application progress on agro-climatic division based on GIS in China is discovered from four points such as climate factors fine-gridding, map digitizing, information services and “3S” technologies combination. Furthermore, some problems in the application are discussed and potential research directions are pointed out in order to provide some reference for researchers in the field. Some suggestions are as follows: (1) Many kinds of natural factors and social factors should be taken into account compositely when doing agro-climatic division; (2) The “bottom-up” of the region merging process by GIS needs to combine with the auto-merge and manual-merge more better; (3) Zoning indexes should be considered using the logical intersection operation; (4) Setting up the Web-based open platform for sharing the agro-climatic division of GIS; (5) GIS combine with GPS, satellite remote sensing data could comprehensive monitor the whole process of crop growth from a macro point of view, and have an important application value for directing agricultural production.