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农学学报 ›› 2018, Vol. 8 ›› Issue (1): 175-179.doi: 10.11923/j.issn.2095-4050.cjas2018-1-175

所属专题: 农业学科与产业发展 现代农业发展与乡村振兴

• 新兴及交叉学科发展篇 • 上一篇    下一篇

农业遥感研究进展与展望

唐华俊   

  1. 中国农业科学院,北京 100081
  • 收稿日期:2017-11-04 修回日期:2017-11-27 出版日期:2018-01-20 发布日期:2020-04-22
  • 作者简介:唐华俊,男,1960年出生,四川阆中人,研究员,博士,主要从事基于遥感技术的农业土地资源合理利用、农作物种植面积空间分布和结构变化规律研究。先后任国家973项目首席科学家,国家自然科学基金重大项目课题和重点基金等项目主持人;获国家科技进步二等奖2项、北京市科技进步一等奖1项和二等奖3项;发表学术论文220篇;出版学术著作10部(含英文2部)。培养博士22人、硕士8人,指导博士后18人。通信地址:100081 北京市海淀区中关村南大街12号 中国农业科学院农业资源与农业区划研究所,Tel:010-82109398,E-mail:tanghuajun@caas.cn。

Progress and Prospect of Agricultural Remote Sensing Research

Tang Huajun   

  1. Chinese Academy of Agricultural Sciences, Beijing 100081, China
  • Received:2017-11-04 Revised:2017-11-27 Online:2018-01-20 Published:2020-04-22

摘要:

农业遥感是遥感科学的重要分支。文章回顾了农业遥感研究的百年发展历程,认为目前遥感在农业领域的应用广度和深度都在不断扩展,农业遥感从获取传统的总产、面积、单产等要素向更多监测要素不断深入,从传统的资源、环境向植保、农学等方向不断扩展,农业遥感正逐步成为农业科学的基础关键技术。论文从农情遥感、农业灾害遥感、农业资源环境遥感等领域全面总结了近年来中国农业遥感研究取得的成就及重要成果。从农业定量遥感、无人机遥感、作物表型遥感等方面指出了农业遥感研究发展的国际前沿,分析认为,随着传感器、物联网、互联网+、大数据、人工智能等技术的发展及现代农业发展的需求,“十三五”及未来10年,国内农业遥感技术在天空地一体化的农业遥感大数据获取、人工智能与大数据等的信息智能提取和挖掘等方面发展前景巨大。

关键词: 农情遥感, 农业灾害遥感, 农业资源遥感, 无人机遥感, 作物表型遥感, 展望

Abstract:

Agricultural remote sensing is an important branch of remote sensing science. This paper reviews the development course of agricultural remote sensing research and puts forward that both the application breadth and depth of remote sensing technique in the field of agriculture are continuously expanding. Agricultural remote sensing is going deep from monitoring single factor of production, area and yield etc. into acquiring more agricultural elements, and is expanding from traditional resources, environment fields to plant protection and other agricultural directions. Agricultural remote sensing is gradually becoming the key technology of agricultural science. This paper summarizes some important achievements of agricultural remote sensing research in China in recent years in the fields of agricultural condition remote sensing, agricultural disaster remote sensing and agricultural resources and environment remote sensing etc. The author presents some international frontier studies in agricultural remote sensing, including agricultural quantitative remote sensing, UAV remote sensing and crop phenotype remote sensing and so on. At last, the author forecasts some development prospects of domestic agricultural remote sensing technology, such as agricultural big data acquisition using the integrated space-terrestrial information network, information intelligent extraction and mining using artificial intelligence and big data and so on in “13th Five-Year Plan” and the next 10 years based on the development of sensor, networking, internet+, big data, artificial intelligence and demand of modern agricultural development.

Key words: Agricultural Condition Remote Sensing, Agricultural Disaster Remote Sensing, Agricultural Resources Remote Sensing, UAV Remote Sensing, Crop Phenotype Remote Sensing, Prospects

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