农业遥感研究现状与展望

遥感技术具有覆盖面积大、重访周期短、获取成本相对低等优势,对大面积露天农业生产的调查、评价、监测和管理具有独特的作用。从20世纪70年代出现民用资源卫星后,农业成为遥感技术最先投入应用和收益显著的领域。特别是随着高空间、高光谱和高时间分辨率遥感数据的出现,农业遥感技术在长时间序列作物长势动态监测、农作物种类细分、田间精细农业信息获取等关键技术方面得到了突破。但是农业生产的分散性、时空变异性等特点,对当前农业遥感技术的应用还存在诸多挑战。本文简要回顾了农业遥感发展历程以及其应用的理论基础;再从农作物估产、农业资源调查、农业灾害监测和精准农业管理4个领域阐述了国内外相关研究和应用情况。最后提出农业遥感应加强与地面农业观测网技术的结合,推动新一代低空无人机遥感平台的发展,强化多源传感器融合以及农业过程模型与遥感数据同化的研究。

Status and Prospect of Agricultural Remote Sensing

Remote sensing technology can cost-effectively access a wide range of real-time land surface spatial information, and provides an effective way for resource surveys, environmental monitoring and disaster prediction. With the help of remote sensing technology, geo-information can be acquired quickly, accurately, efficiently and comprehensively. Undoubtedly, remote sensing will play an increasingly important role in the fields of geosciences, agricultural sciences, and so on. In particular civil resources satellite was launched in the 1970s, which was applied in agriculture and benefited first. Moreover, significant developments were registered in some key fields along with the advancement of high resolution remote sensing. The combination of their high temporal frequency with extended geographical coverage makes them particularly useful for time series crop growth monitoring, crop types subdivision, and acquisition of field precision agriculture. The fact is of note that the new challenges followed as a result of the dispersion and spatial-temporal variability in agricultural production. An overview of the history and theoretical background of agricultural remote sensing technology was introduced. And then four aspects of yield estimation, agricultural resources survey, agricultural disaster monitoring and precision agriculture management were presented. Remotely sensed data from existing platforms and the ground observation network technology which can provide an important data source for supporting agriculture were expected. On the other hand, new generation remote sensing platform of low altitude unmanned aerial vehicle (UAV) should be promoted. Although progress has been made, current methods and techniques still bear potential to further explore multi-sensors, spectral data, surface characteristic parameters and existing crop model. The combination of multi-sensor data and assimilation will enhance the perspectives of using remotely sensed data for agriculture.