农业遥感研究进展与展望
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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。
Agricultural remote sensing is an important branch of remote sensing science. This paper reviewsthe development course of agricultural remote sensing research and puts forward that both the applicationbreadth 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. intoacquiring more agricultural elements, and is expanding from traditional resources, environment fields to plantprotection and other agricultural directions. Agricultural remote sensing is gradually becoming the keytechnology of agricultural science. This paper summarizes some important achievements of agricultural remotesensing research in China in recent years in the fields of agricultural condition remote sensing, agriculturaldisaster remote sensing and agricultural resources and environment remote sensing etc. The author presentssome international frontier studies in agricultural remote sensing, including agricultural quantitative remotesensing, UAV remote sensing and crop phenotype remote sensing and so on. At last, the author forecasts somedevelopment prospects of domestic agricultural remote sensing technology, such as agricultural big dataacquisition using the integrated space-terrestrial information network, information intelligent extraction andmining using artificial intelligence and big data and so on in"13 th Five-Year Plan"and the next 10 yearsbased on the development of sensor, networking, internet +, big data, artificial intelligence and demand ofmodern agricultural development.
Agricultural remote sensing is an important branch of remote sensing science. This paper reviewsthe development course of agricultural remote sensing research and puts forward that both the applicationbreadth 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. intoacquiring more agricultural elements, and is expanding from traditional resources, environment fields to plantprotection and other agricultural directions. Agricultural remote sensing is gradually becoming the keytechnology of agricultural science. This paper summarizes some important achievements of agricultural remotesensing research in China in recent years in the fields of agricultural condition remote sensing, agriculturaldisaster remote sensing and agricultural resources and environment remote sensing etc. The author presentssome international frontier studies in agricultural remote sensing, including agricultural quantitative remotesensing, UAV remote sensing and crop phenotype remote sensing and so on. At last, the author forecasts somedevelopment prospects of domestic agricultural remote sensing technology, such as agricultural big dataacquisition using the integrated space-terrestrial information network, information intelligent extraction andmining using artificial intelligence and big data and so on in"13 th Five-Year Plan"and the next 10 yearsbased on the development of sensor, networking, internet +, big data, artificial intelligence and demand ofmodern agricultural development.
引文
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[13]史舟,梁宗正,杨媛媛,等.农业遥感研究现状与展望[J].农业机械学报,2015,45(2):247-260.
[14]蒙继华,吴炳方,李强子,等.农田农情参数遥感监测进展及应用展望[J].遥感信息,2010(3):122-127.
[15]刘纪远,匡文慧,张增祥,等.20世纪80年代末以来中国土地利用变化的基本特征与空间格局[J].地理学报,2014,69(1):3-13.
[16]唐华俊,周清波,刘佳,等.中国农作物空间分布遥感制图——小麦篇[M].北京:科学出版社,2015:10-50.
[17]刘婷,苏伟,王成,等.基于机载Li DAR数据的玉米叶面积指数反演[J].中国农业大学学报,2016,21:104-111.
[18]陈雪忠.渔业遥感应用理论与技术[M].北京:科学出版社,2015:10-27.
[19]杨鹏,吴文斌,周清波,等.基于作物模型与叶面积指数遥感同化的区域单产估测研究[J].农业工程学报,2007,23(9):130-136.
[20]Jiang Z,Chen Z,Chen J,et al.The Estimation of Regional Crop Yield Using Ensemble-Based Four-Dimensional Variational Data Assimilation[J].Remote Sensing,2014,6(4):2664-2681.
[21]Tang H,Li Z.Quantitative Remote Sensing in Thermal Infrared:Theory and Applications[J].Springer Berlin Heidelberg,2014.
[22]Deery D,Jimenez-Berni J,Jones H,et al.Proximal Remote Sensing Buggies and Potential Applications for Field-Based Phenotyping[J].Agronomy,2014,4(3):349-379.
[23]刘建刚,赵春江,杨贵军,等.无人机遥感解析田间作物表型信息研究进展[J].农业工程学报,2016,43(24):98-106.
[24]朱建章,石强,陈凤娥,等.遥感大数据研究现状与发展趋势[J].中国图像图形学报,2016,21(11):1425-1439.
[2]郭德友,吕耀昌,彭德福,等.农业遥感:农作物估产的理论与方法[M].北京:科学出版社,1986:100-200.
[3]陈仲新,任建强,唐华俊,等.中国农业遥感研究应用进展与展望[J].遥感学报,2016,20(5):748-765.
[4]彭望琭,白振平,刘湘南,等.遥感概论[M].北京:高等教育出版社,2002:9-15.
[5]孙家抦.遥感原理与应用[M].武汉:武汉大学出版社,2013:24-52.
[6]王纪华,赵春江,黄文江,等.农业定量遥感基础与应用[M].北京:科学出版社,2008:259-276.
[7]Boryan C,Yang Z,Di L,et al.A new automatic stratification method for U.S.agricultural area sampling frame construction based on the cropland data layer[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2014,7(11):4317-4327.
[8]周清波.国内外农情遥感现状与发展趋势[J].中国农业资源与区划,2004,25(5):9-14
[9]林文鹏,王长耀.大尺度作物遥感监测方法与应用[M].北京:科学出版社,2010:7-19.
[10]Atzberger C.Advances in remote sensing of agriculture:context description,existing operational monitoring systems and major information needs[J].Remote Sensing,2013,5:949-981.
[11]Thenkabail Prasad S.Global Croplands and their Importance for Water and Food Security in the Twenty-first Century:Towards an Ever Green Revolution that Combines a Second Green Revolution with a Blue Revolution[J].Remote Sensing,2010,2(9):2305-2312.
[12]唐华俊,吴文斌,杨鹏,等.农作物空间格局遥感监测研究进展[J].中国农业科学,2010,43(14):2879-2888.
[13]史舟,梁宗正,杨媛媛,等.农业遥感研究现状与展望[J].农业机械学报,2015,45(2):247-260.
[14]蒙继华,吴炳方,李强子,等.农田农情参数遥感监测进展及应用展望[J].遥感信息,2010(3):122-127.
[15]刘纪远,匡文慧,张增祥,等.20世纪80年代末以来中国土地利用变化的基本特征与空间格局[J].地理学报,2014,69(1):3-13.
[16]唐华俊,周清波,刘佳,等.中国农作物空间分布遥感制图——小麦篇[M].北京:科学出版社,2015:10-50.
[17]刘婷,苏伟,王成,等.基于机载Li DAR数据的玉米叶面积指数反演[J].中国农业大学学报,2016,21:104-111.
[18]陈雪忠.渔业遥感应用理论与技术[M].北京:科学出版社,2015:10-27.
[19]杨鹏,吴文斌,周清波,等.基于作物模型与叶面积指数遥感同化的区域单产估测研究[J].农业工程学报,2007,23(9):130-136.
[20]Jiang Z,Chen Z,Chen J,et al.The Estimation of Regional Crop Yield Using Ensemble-Based Four-Dimensional Variational Data Assimilation[J].Remote Sensing,2014,6(4):2664-2681.
[21]Tang H,Li Z.Quantitative Remote Sensing in Thermal Infrared:Theory and Applications[J].Springer Berlin Heidelberg,2014.
[22]Deery D,Jimenez-Berni J,Jones H,et al.Proximal Remote Sensing Buggies and Potential Applications for Field-Based Phenotyping[J].Agronomy,2014,4(3):349-379.
[23]刘建刚,赵春江,杨贵军,等.无人机遥感解析田间作物表型信息研究进展[J].农业工程学报,2016,43(24):98-106.
[24]朱建章,石强,陈凤娥,等.遥感大数据研究现状与发展趋势[J].中国图像图形学报,2016,21(11):1425-1439.