引用本文:王一鹤,杨 飞,王卷乐,刘丽峰※,马 娅.农业大数据研究与应用进展[J].中国农业信息,2018,30(4):48-57
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农业大数据研究与应用进展
王一鹤1, 杨 飞2, 王卷乐2, 刘丽峰※1, 马 娅3
1.山东理工大学,淄博255049;2.中国科学院地理科学与资源研究所,资源与环境信息系统国家重点实验室,北京100101;3.环境保护部环境规划院,北京100012
摘要:
【目的】在全球快速发展和数据信息量迅猛增长背景下,大数据技术也成为各行业应 对海量数据的重要助力。国内对于农业大数据的研究起步较晚,缺乏对相关研究的归纳总 结。文章通过对目前农业大数据应用、技术等研究进行论述,对未来农业大数据的发展方向 进行展望。【方法】文章采用文献综述法,概述了国内外农业大数据的研究进展,分析了农 业大数据的应用方向与关键技术,简要介绍了部分农业大数据平台,指出了目前发展存在的 问题并提出未来发展方向。【结果】我国农业大数据发展十分迅速,目前已应用在了农业育 种、生产与养殖、农业气象预测、市场管理与农产品追溯等领域,相关的农业大数据平台也 已投入使用,但目前仍存在数据缺乏统一标准、共享水平低、缺乏大数据人才、缺乏自主核 心技术、已有大数据平台缺乏实用性、数据保护体系不完善等问题。【结论】未来要进一步 完善农业大数据采集体系,提高数据共享水平,增强大数据尤其是农业大数据的人才培养力 度,优化大数据分析技术,让数据挖掘变得更加高效,自主研发大数据处理框架减少对国外 技术的依赖,此外要对原有的大数据平台进行升级,建设出包含农业旅游、文化等丰富的、 能够为基层群众提供更加实用性服务的农业大数据平台以及针对大数据资源特点,完善大数 据的安全保障工作。
关键词:  农业;大数据;关键技术;发展方向
DOI:10.12105/j.issn.1672-0423.20180404
分类号:
基金项目:中国工程科技知识中心防灾减灾知识服务系统建设项目(CKCEST-2017-3-1),国家重点研发计划项目(2017YFA0604804);中国科学院前沿科学重点研究项目(QYZDY-SSW-DQC007)
Overview of the progress in researches and applications ofagriculture big data
Wang Yihe1, Yang Fei2, Wang Juanle2, Liu Lifeng※1, Ma Ya3
1.Shandong University of Technology,Zibo 255049,China;2.Institute of Geographic Sciences and Natural Resources Research,State Key laboratory of Resources and Environmental Information System, Chinese Academy of Sciences,Beijing 100101,China;3.Environmental Economic Institute, Chinese Academy for Environmental Planning,Beijing100012,China
Abstract:
[Purpose]With the rapid development of the world and the rapid growth of data information,big data technology has become an important boost for various industries to cope with massive data.Agriculture data is characterized by wide coverage and uneven distribution, and traditional data processing methods are difficult to meet the task of processing large amounts of agriculture data.The development of big data provides a good tool for solving such problems. However,domestic researches on agriculture big data has fell behind and the number of related research is limited.The article discusses the current development of agriculture big data applications and technologies,and looks forward to the future development in agriculture big data processing.[Method]The article reviewed literature and summarized the research progress of agriculture big data in China and abroad.It further analyzed the application direction and key technologies of agriculture big data,and introduced some agriculture big data platforms briefly. Finally,it pointed out the current development problems and proposed future development directions.[Result]China’s agriculture big data has developed quickly,and it has been applied in the fields of crop breeding,animal breeding,agriculture meteorological forecasting, market management and agricultural products traceability,and the relevant agriculture big data platform has also been under operation.However,there are still some problems at present. First,the uniform data standards is lacking and the data sharing is limited.Second,the talents associated with big data are also lacking that it is difficult to carry out relevent works.Third,the mainstream big data processing technology is developed by foreign countries,and the domestic independent technology is rare.Fourth,at present,many agriculture big data platforms have only limited practicality.Fifth,the data protection system is weak.[Conclusion]There are some important works to do in the future.First of all,the collection system of agriculture big data needs to be further improved and the level of data sharing should be improved,besides,the work of educating big data talents is urgently required.Secondly,big data analytics technology should be improved to finish the work of data mining.At the same time,more efficiently and more selfowned core technology should be invented.Last but not the least,the existing agriculture big data platforms should be upgraded and more rich content should be added to the platform such as tourism and culture so that it can provide more practical functions,besides,a more sophisticated big data protection system should be established according to the characteristics of data resources.
Key words:  agriculture;big data;key technology;direction of development