农作物长势遥感监测需求、系统框架及业务应用

Demands，system framework，and operational applicationof crop growth remote sensing monitoring

关键词:  农作物  长势  监测需求  系统设计  遥感应用

Key words:  crop  growth  monitoring needs  system design  remote sensing application

摘要:

【目的】农作物长势是农业生产管理的重要依据，也是农情遥感监测业务的重要组成 部分。【方法】在当前农作物长势遥感监测研究及业务状况扼要回顾基础上，文章从农作物 长势遥感监测需求、系统框架等方面进行了系统总结，并以全球冬小麦长势遥感监测应用 为例进行了说明。【结果】农作物长势遥感监测需求可以归纳为服务对象、作物类型、空间 范围、地面尺度、监测周期等5 个方面，系统框架至少包括数据层、方法层、结果层和服 务层4 个层次。【结论】针对农作物长势遥感监测技术研究及业务应用的现状，研究提出了 以下3 个观点，（1）农作物长势遥感监测业务方案是成熟的，但是关键技术研究有待加强； （2）农作物长势概念的深入解析，将有利提高长势遥感监测的业务化能力与精度；（3）针对 全球、国家、省级以及县级尺度农作物长势遥感监测，采用不同空间分辨率遥感数据开展监 测业务，是今后较长一个时期内农作物长势遥感监测的客观现状。上述研究结果给农作物长 势遥感监测业务的建设提供了依据，也明确地指明了系统地服务目标。

Abstract:

［Purpose］Crop growth is an important basis for agricultural production management，and is also an important component of agricultural monitoring using remote sensing operation.［Method］Based on the study of crop growth remote sensing monitoring and a brief review of its business operation，the paper conducted a systematic summary on the aspects of crop growth remote sensing monitoring demands，system framework，etc. Meanwhile，the paper also illustrated the demands and system framework by taking the application of global winter wheat growth remote sensing monitoring as an example.［Result］Crop growth remote sensing monitoring demands can be summarized into five aspects：service objects，crop types，spatial range，ground scale，monitoring period，and its system framework at least includes four layers： data layer，method layer，result layer，and service layer.［Conclusion］The paper made the following conclusions on the study of crop growth remote sensing monitoring technology and its business operation：firstly，operational solution of crop growth remote sensing monitoring is mature，but the study of key technologies needs to be further improved；secondly，deep analysis of crop growth concept will be conductive to improving the operation capacity of crop growth remote sensing monitoring and its accuracy；thirdly，in the different levels of global，national，provincial and county scales，the operations with different spatial resolutions will be implemented for crop growth remote sensing practices in the future for a long period of time. Above study results provided a basis for guiding operation of crop growth remote sensing monitoring and also clearly identified the service objects of the system.