无人机遥感技术在精量灌溉中应用的研究进展  

Review on UAV Remote Sensing Application in Precision Irrigation

作　　者：韩文霆[1] 张立元[2] 牛亚晓 史翔 HAN Wenting;ZHANG Liyuan;NIU Yaxiao;SHI Xiang(Institute of Soil and Water Conservation,Northwest A&F University,Yangling,Shaanxi 712100,China;College of Mechanical and Electronic Engineering,Northwest A&F University,Yangling,Shaanxi 712100,China)

机构地区：[1]西北农林科技大学水土保持研究所,陕西杨凌712100 [2]西北农林科技大学机械与电子工程学院,陕西杨凌712100

出　　处：《农业机械学报》2020年第2期1-14,共14页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家自然科学基金项目(51979233);国家重点研发计划项目(2017YFC0403203);杨凌示范区产学研用协同创新重大项目(2018CXY-23);高等学校学科创新引智计划项目(B12007)

摘　　要：以提高农业用水效率为目标的精量灌溉是未来农业灌溉的主要模式,精量灌溉的前提条件是对作物缺水的精准诊断和科学的灌溉决策。用于作物缺水诊断和灌溉决策定量指标的信息获取技术主要基于田间定点监测、地面车载移动监测及卫星遥感。无人机从根本上解决了卫星遥感由于时空分辨率低而导致的瞬时拓延、空间尺度转换、遥感参数与模型参数定量对应等技术难题,也克服了地面监测效率低、成本高、影响田间作业等问题。近几年的研究结果表明,无人机遥感系统可以高通量地获取多个地块的高时空分辨率图像,使精准分析农业气象条件、土壤条件、作物表型等参数的空间变异性及其相互关系成为可能,为大面积农田范围内快速感知作物缺水空间变异性提供了新手段,在精量灌溉技术应用中具有明显的优势和广阔的前景。无人机遥感系统已经应用在作物覆盖度、株高、倒伏面积、生物量、叶面积指数、冠层温度等农情信息的监测方面,但在作物缺水诊断和灌溉决策定量指标监测方面的研究才刚刚起步,目前主要集中在作物水分胁迫指数(CWSI)、作物系数、冠层结构相关指数、土壤含水率、叶黄素相关指数(PRI)等参数估算的研究,有些指标已经成功应用于监测多种作物的水分胁迫状况,但对于大多数作物和指标,模型的普适性还有待进一步研究。给出了无人机遥感在精准灌溉技术中应用的技术体系,并指出,为满足不同尺度的高效率监测和实现农业用水精准动态管理的需求,今后无人机遥感需要结合卫星遥感和地面监测系统,其中天空地一体化农业水信息监测网络优化布局方法与智能组网技术、多源信息时空融合与同化技术、作物缺水多指标综合诊断模型、农业灌溉大数据等将是未来重点研究内容。Precision irrigation aiming at improving the agricultural water use efficiency is the main mode of future agricultural irrigation,with the accurate detection of crop water stress and the scientific irrigation decision being its prerequisite.For decades,field-based fixed-point monitoring,on-board vehicle movement monitoring and satellite remote sensing were the information acquisition techniques for the quantitative detection of crop water stress and irrigation decision-making.The emergence of unmanned aerial vehicle(UAV)fundamentally solved the technical problems of satellite remote sensing caused by its low temporal-spatial resolution,including instantaneous extension,spatial scale conversion,quantitative correspondence between remote sensing parameters and model parameters.At the same time,UAV remote sensing technology also solved the problems of ground monitoring methods,such as low efficiency and high cost.Research results in recent years showed that the UAV remote sensing system could obtain high-temporal resolution images of multiple plots with high throughput,making it possible to analyze the spatial variability of agro-meteorological conditions,soil conditions,crop phenotypes and their mutual relationships accurately.It provided a new method for quickly sensing the spatial variability of crop water stress within a large area of farmland,which had obvious advantages and broad prospects in the application of precision irrigation.UAV remote sensing technology was successfully applied to obtain agricultural information,including fractional vegetation cover,plant height,lodging area,biomass,leaf area index and canopy temperature.However,study on quantitative indicator monitoring for crop water stress detection and irrigation decision-making has just started.At present,it mainly focuses on crop water stress index(CWSI),crop coefficient,canopy structural index,soil water content,PRI etc.Some of the above indicators were successfully applied to monitor the water stress status of various crops,but for most crops a

关 键 词：无人机遥感 精量灌溉 变量灌溉 作物需水量 作物水分胁迫 

分 类 号：S127[农业科学—农业基础科学] S274