作物胁迫无人机遥感监测研究评述
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  • 英文篇名:The Use of UAV Remote Sensing Technology to Identify Crop Stress: A Review
  • 作者:黄耀欢 ; 李中华 ; 朱海涛
  • 英文作者:HUANG Yaohuan;LI Zhonghua;ZHU Haitao;State Key Lab of Resources and Environmental Information System,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences;University of Chinese Academy of Sciences;Satellite Environment Center,Ministry of Environmental Protection;
  • 关键词:无人机 ; 遥感监测 ; 作物胁迫 ; 光谱成像 ; 热红外传感器 ; 农业发展 ; 评述
  • 英文关键词:UAV;;remote sensing monitoring;;crop stress;;spectral imaging;;thermal infrared sensor;;agricultural development;;review
  • 中文刊名:DQXX
  • 英文刊名:Journal of Geo-Information Science
  • 机构:中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室;中国科学院大学;环境保护部卫星环境应用中心;
  • 出版日期:2019-04-24 14:53
  • 出版单位:地球信息科学学报
  • 年:2019
  • 期:v.21;No.140
  • 基金:国家重点研发计划项目(2016YFC0208202、2017YFB0503005)~~
  • 语种:中文;
  • 页:DQXX201904006
  • 页数:12
  • CN:04
  • ISSN:11-5809/P
  • 分类号:42-53
摘要
作物胁迫是全球农业发展的一个重要制约因素,实现快速、大范围、实时的作物胁迫监测对于农业生产具有重要意义。传统的作物胁迫监测方式,如田间调查、理化检测和卫星遥感监测总是受到各种田间条件或大气条件的制约。随着无人机和各种轻量化传感器的快速发展,其凭借高频、迅捷等优势为各种作物胁迫监测提供了一套全新的解决方案。本文在介绍了目前主流的多种无人机和传感器的基础上,首先对目前无人机遥感用于作物监测的主要胁迫类型进行了梳理,然后重点阐述了基于光谱成像和热红外传感器进行作物胁迫无人机遥感监测的应用和技术方法,最后提出了作物胁迫无人机遥感监测尚需解决的关键问题,并展望了未来无人机遥感用于作物胁迫监测的前景。
        Crop stress is an important factor restricting global agricultural development. Monitoring and understanding rapid, large-scale and real-time crop stress is of great significance for agricultural production. However,traditional methods of crop stress monitoring(such as fields surveys, physical and chemical detection, and satellite remote sensing), are strongly influenced by field and atmospheric conditions, temporal and spatial resolution,and labor costs. Rapid development of UAV platforms and various lightweight sensors, provide new solutions for various crop stress monitoring. These offer multiple advantages, primarily high frequency and speed. The introduction of various mainstream UAV platforms such as multi-rotor and fixed-wing, and sensors such as visible light digital camera, multispectral camera, hyperspectral camera, and thermal infrared camera has allowed for more efficient crop monitoring. This review explores the main biotic and abiotic stress types used by UAV remote sensing systems for crop monitoring. Biotic stressors mainly include miscellaneous grass stress, plant diseases, and insect pests stress. Abiotic stressors predominantly include water and nutrient stress. The application and technical methods of UAV remote sensing system monitoring of crop stress, based on spectral imaging and thermal infrared sensor technology are discussed. Sensitive bands and common vegetation indices used for crop stress monitoring are identified. Finally, key issues associated with UAV remote sensing and the future use of UAV remote sensing for crop stress monitoring are discussed. The advancement of UAV remote sensing technology, could contribute to improved identification and monitoring of crop stress in the near future.
引文
[1]杜广平.植物与植物生理[M].北京:北京大学出版社,2007.[Du G P.Plant and plant physiology[M].Beijing:Peking University press,2007.]
    [2]Martinelli F,Scalenghe R,Davino S,et al.Advanced methods of plant disease detection.A review[J].Agronomy for Sustainable Development,2015,35(1):1-25.
    [3]廖小罕,周成虎,苏奋振,等.无人机遥感众创时代[J].地球信息科学学报,2016,18(11):1439-1447.[Liao X H,Zhou C H,Su F Z et al.The mass innovation era of UAV remote sensing[J].Journal of Geo-information Science,2016,18(11):1439-1447.]
    [4]杨海军,黄耀欢.化工污染气体无人机遥感监测[J].地球信息科学学报,2015,17(10):1269-1274.[Yang H J,Huang Y H.Evaluating atmospheric pollution of chemical plant based on unmanned aircraft vehicle(UAV)[J].Journal of Geo-information Science,2015,17(10):1269-1274.]
    [5]金伟,葛宏立,杜华强,等.无人机遥感发展与应用概况[J].遥感信息,2009(1):88-92.[Jin W,Ge H L,Du H Q,et al.A review on unmanned aerial vehicle remote sensing and its application[J].Remote Sensing Information,2009(1):88-92.]
    [6]孙中宇,陈燕乔,杨龙,等.轻小型无人机低空遥感及其在生态学中的应用进展[J].应用生态学报,2017,28(2):528-536.[Sun Z Y,Chen Y Q,Yang L,et al.Small unmanned aerial vehicles for low-altitude remote sensing and its application progress in ecolology[J].Chinese Journal of Applied Ecology,2017,28(2):528-536.]
    [7]宋晓阳,黄耀欢,董东林,等.融合数字表面模型的无人机遥感影像城市土地利用分类[J].地球信息科学学报,2018,20(5):703-711.[Song X Y,Huang Y H,Dong D L,et al.Urban land use classification from UAV remote sensing images based on digital surface model[J].Journal of Geo-information Science,2018,20(5):703-711.]
    [8]郭琪,童庆祥.无人机在气象监测中的应用[J].广东气象,2016,38(6):64-66.[Guo Q,Tong Q X.Application of uav in meteorological monitoring[J].Journal of Guangdong Meteorology,2016,38(6):64-66.]
    [9]Alheit K V,Busemeyer L,Liu W,et al.Multiple-line cross QTL mapping for biomass yield and plant height in triticale[J].Theoretical and Applied Genetics,2013,127(1):251-260.
    [10]Zhang C,Kovacs J M.The application of small unmanned aerial systems for precision agriculture:a review[J].Precision Agriculture,2012,13(6):693-712.
    [11]Cui J,Wang F,Dong X,et al.Landmark extraction and state estimation for UAV operation in forest[C]//Control conference.IEEE,2013:5210-5215.
    [12]López-Granados F,Torres-Sánchez J,Serrano-Pérez A,et al.Early season weed mapping in sunflower using UAV technology:variability of herbicide treatment maps against weed thresholds[J].Precision Agriculture,2016,17(2):183-199.
    [13]López-Granados F,Torres-Sánchez J,Castro A I D,et al.Object-based early monitoring of a grass weed in a grass crop using high resolution UAV imagery[J].Agronomy for Sustainable Development,2016,36(4):67.
    [14]Roope Nasi,Niko Viljanen,Jere Kaivosoja,et al.Estimating biomass and nitrogen amount of barley and grass using UAV and aircraft based spectral and photogrammetric3D features[J].Remote Aens,2018,10(7):1082.
    [15]李宗南,陈仲新,王利民,等.基于小型无人机遥感的玉米倒伏面积提取[J].农业工程学报,2014,30(19):207-213.[Li Z N,Chen Z X,Wang L M,et al.Area extraction of maize lodging based on remote sensing by small unmanned aerial vehicle[J].Transactions of the Chinese Society of Agricultural Engineering,2014,30(19):207-213.]
    [16]祝锦霞,陈祝炉,石媛媛,等.基于无人机和地面数字影像的水稻氮素营养诊断研究[J].浙江大学学报(农业与生命科学版),2010,36(1):78-83.[Zhu J X,Chen Z L,Shi Y Y,et al.Diagnoses of rice nitrogen status based on spectral characteristics of leaf and canopy[J].Journal of Zhejiang University(Agricultural and Life Sciences),2010,36(1):78-83.]
    [17]Castro A I D,Ehsani R,Ploetz R C,et al.Detection of laurel wilt disease in avocado using low altitude aerial imaging[J].Plos One,2015,10(4):e0124642.
    [18]李红军,李佳珍,雷玉平,等.无人机搭载数码相机航拍进行小麦、玉米氮素营养诊断研究[J].中国生态农业学报,2017(12):1832-1841.[Li H J,Li J Z,Lei Y P,et al.Diagnosis of nitrogen nutrition of winter wheat and summer corn using images from digital camera equipped on unmanned aerial vehicle[J].Chinese Journal of Eco-Agriculture,2017(12):1832-1841.]
    [19]Zamanallah M,Vergara O,Araus J L,et al.Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize.[J].Plant Methods,2015,11(1):35.
    [20]Severtson D,Callow N,Flower K,et al.Unmanned aerial vehicle canopy reflectance data detects potassium deficiency and green peach aphid susceptibility in canola[J].Precision Agriculture,2016,17(6):659-677.
    [21]Dash J P,Watt M S,Pearse G D,et al.Assessing very high resolution UAV imagery for monitoring forest health during a simulated disease outbreak[J].International Journal of Photogrammetry&Remote Sensing,2017,131:1-14.
    [22]Vanegas F,Bratanov D,Powell K,et al.A novel methodology for iimproving plant pest surveillance in vineyards and crops using UAV-based hyperspectral and spatial data.[J].Sensors,2018,18(1):260.
    [23]关丽,刘湘南,程承旗.土壤镉污染环境下水稻叶片叶绿素含量监测的高光谱遥感信息参数[J].光谱学与光谱分析,2009,29(10):2713-2716.[Guan L,Liu X N,Cheng CQ.Research on hyperspectral information parameters of chlorophyll content of rice leaf in cd-polluted soil environment[J].Spectroscopy and Spectral Analysis,2009,29(10):2713-2716.]
    [24]Wang H,Wang J,Wang Q,et al.Hyperspectral characteristics of winter wheat under freezing injury stress and LWC inversion model[C]//First International Conference on Agro-Geoinformatics.IEEE,2012:1-6.
    [25]秦占飞,常庆瑞,谢宝妮,等.基于无人机高光谱影像的引黄灌区水稻叶片全氮含量估测[J].农业工程学报,2016,32(23):77-85.[Qin Z F,Chang Q R,Xie B N,et al.Rice leaf nitrogen content estimation based on hyperspectral imagery of UAV in Yellow River diversion irrigation district[J].Transactions of the Chinese Society of Agricultural Engineering,2016,32(23):77-85.]
    [26]Calderón R,Navas-Cortés J A,Lucena C,et al.High-resolution airborne hyperspectral and thermal imagery for early detection of Verticillium,wilt of olive using fluorescence,temperature and narrow-band spectral indices[J].Remote Sensing of Environment,2013,139(139):231-245.
    [27]Bellvert J,Zarco-Tejada P J,Girona J,et al.Mapping crop water stress index in a'Pinot-noir'vineyard:comparing ground measurements with thermal remote sensing imagery from an unmanned aerial vehicle[J].Precision Agriculture,2014,15(4):361-376.
    [28]Matese A,Baraldi R,Berton A,et al.Estimation of water stress in grapevines using proximal and remote sensing methods[J].Remote Sensing,2018,10(1):114.
    [29]Bellvert J,Zarco-Tejada P J,Gonzalez-Dugo V,et al.Scheduling vineyard irrigation based on mapping leaf water potential from airborne thermal images[C]//European Conference in Precision Agriculture.2013:699-704.
    [30]Gonzalez-Dugo V,Zarco-Tejada P,Nicolás E,et al.Using high resolution UAV thermal imagery to assess the variability in the water status of five fruit tree species within a commercial orchard[J].Precision Agriculture,2013,14(6):660-678.
    [31]杨凡.基于无人机激光雷达和高光谱的冬小麦生物量反演研究[D].西安:西安科技大学,2017.[Yang F.Estimation of winter wheat aboveground biomass with UAV LiDAR and hyperspectral data[D].Xi'an:Xi'an University of Science and Technology,2017]
    [32]杨浩,杨贵军,顾晓鹤,等.小麦倒伏的雷达极化特征及其遥感监测[J].农业工程学报,2014,30(7):1-8.[Yang H,Yang G J,Gu X H,et al.Radar polarimetric response features and remote sensing monitoring of wheat lodging[J].Transactions of the Chinese Society of Agricultural Engineering,2014,30(7):1-8.]
    [33]Pe?a J M,Torressánchez J,Serranopérez A,et al.Quantifying efficacy and limits of unmanned aerial vehicle(UAV)technology for weed seedling detection as affected by sensor resolution[J].Sensors,2015,15(3):5609-26.
    [34]Strange R N,Scott P R.Plant disease:A threat to global food security[J].Annual Review of Phytopathology,2005,43(1):83-116.
    [35]张竞成,袁琳,王纪华,等.作物病虫害遥感监测研究进展[J].农业工程学报,2012,28(20):1-11.[Zhang J C,Yuan L,Wang J H,et al.Research progress of crop diseases and pests monitoring based on remote sensing[J].Transactions of the Chinese Society of Agricultural Engineering,2012,28(20):1-11.]
    [36]乔红波,师越,司海平,等.基于无人机数字图像与高光谱数据融合的小麦全蚀病等级的快速分类技术[J].植物保护,2015,41(6):157-162.[Qiao H B,Shi Y,Si H P,et al.Fast multi-classification of wheat take-all levels based on the fusion of unmanned aerial vehicle digital images and spectral data[J].Plant Protection,2015,41(6):157-162.]
    [37]冷伟锋,王海光,胥岩,等.无人机遥感监测小麦条锈病初探[J].植物病理学报,2012,42(2):202-205.[Leng W F,Wang H G,Xu Y,et al.Preliminary study on monitoring wheat stripe rust with using UAV[J].Acta Phytopathologica Sinica,2012,42(2):202-205.]
    [38]Wang X,Zhao C,Guo N,et al.Determining the canopy water stress for spring wheat using canopy hyperspectral reflectance data in loess plateau semiarid regions[J].Spectroscopy Letters,2015,48(7):7.
    [39]Fuchs M,Tanner C B.Infrared thermometry of vegetation[J].Agronomy Journal,1962,58(6):597-601.
    [40]Idso S B,Jackson R D,Jr P J P,et al.Normalizing the stress-degree-day parameter for environmental variability[J].Agricultural Meteorology,1981,24(1):45-55.
    [41]Zhao T,Stark B,Chen Y Q,et al.Challenges in water stress quantification using small unmanned aerial system(sUAS):Lessons from a growing season of almond[C]//International Conference on Unmanned Aircraft Systems.IEEE,2016:1366-1370.
    [42]Chen S Y,,Zhang J S,Liu P,et al.Plant stress related protein GmSIK1 and encoding gene and use thereof:US,US20120266325 A1[P].2012.
    [43]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,2016,32(24):98-106.[Liu J G,Zhao C J,Yang G J,et al.Review of fieldbased phenotyping by unmanned aerial vehicle remote sensing platform[J].Transactions of the Chinese Society of Agricultural Engineering,2016,32(24):98-106.]
    [44]Genderen V J L.Advances in environmental remote sensing:Sensors,algorithms and applications[J].International Journal of Digital Earth,2011,4(5):446-447.
    [45]黄文江.作物病害遥感监测机理与应用[M].北京:中国农业科学技术出版社,2009.[Huang W J.Mechanism and application of remote sensing monitoring of crop diseases[M].Beijing:China Agricultural Science and Technology Press,2009.]
    [46]刘良云,黄木易,黄文江,等.利用多时相的高光谱航空图像监测冬小麦条锈病[J].遥感学报,2004,8(3):275-281.[Liu L Y,Huang M Y,Huang W J,et al.Monitoring stripe rust disease of winter wheat using multi-temporal hyperspectral airborne data[J].Journal of Remote Sensing,2004,8(3):275-281.]
    [47]Geipel J,Link J,Wirwahn J,et al.A programmable aerial multispectral camera system for in-season crop biomass and nitrogen content estimation[J].Agriculture,2016,6(1):4.
    [48]Liu Y,Cheng T,Zhu Y,et al.Comparative analysis of vegetation indices,non-parametric and physical retrieval methods for monitoring nitrogen in wheat using UAV-based multispectral imagery[C]//Geoscience and Remote Sensing Symposium.IEEE,2016:7362-7365.
    [49]Castro A I D,Jurado-Expósito M,Pe?a-Barragán J M,et al.Airborne multi-spectral imagery for mapping cruciferous weeds in cereal and legume crops[J].Precision Agriculture,2012,13(3):302-321.
    [50]Jorge T S,Francisca L G,Isabel D C A,et al.Configuration and specifications of an unmanned aerial vehicle(UAV)for early site specific weed management[J].Plos One,2013,8(3):e58210.
    [51]Zarco-Tejada P J,González-Dugo V,Williams L E,et al.A PRI-based water stress index combining structural and chlorophyll effects:Assessment using diurnal narrowband airborne imagery and the CWSI thermal index[J].Remote Sensing of Environment,2013,138(138):38-50.
    [52]Nebiker S,Lack N,Ab?cherli M,et al.Light-weight multispectral UAV sensors and their capabilities for predicting grain yield and detecting plant diseases[J].ISPRS-International Archives of the Photogrammetry,Remote Sensing and Spatial Information Sciences,2016,XLI-B1:963-970.
    [53]Zhao C,Huang M,Huang W,et al.Analysis of winter wheat stripe rust characteristic spectrum and establishing of inversion models[C]//IEEE International Geoscience&Remote Sensing Symposium.IEEE,2004.
    [54]Baluja J,Diago M P,Balda P,et al.Assessment of vineyard water status variability by thermal and multispectral imagery using an unmanned aerial vehicle(UAV)[J].Irrigation Science,2012,30(6):511-522.
    [55]Lisa C,Matteo C,Monica G,et al.Unmanned aerial vehicle to estimate nitrogen status of turfgrasses[J].Plos One,2016,11(6):e0158268.
    [56]Lee W S,Alchanatis V,Yang C,et al.Review:Sensing technologies for precision specialty crop production[J].Computers&Electronics in Agriculture,2010,74(1):2-33.
    [57]Schmitz A,Kiewnick S,Schlang J,et al.Use of high resolution digital thermography to detect Heterodera schachtii infestation in sugar beets[J].Commun Agric Appl Biol Sci,2004,69(3):359-363.
    [58]Lili Z,Duchesne J,Nicolas H,et al.Détection infrarouge thermique des maladies du bléd'hiver[J].Eppo Bulletin,1991,21(3):659-672.
    [59]Nicolas H,Stafford J V.Use of remote sensing within the optical and thermal spectral ranges in order to detect Septoria tritici on winter wheat[C]//Precision agriculture'05.Papers presented at the 5thEuropean Conference on Precision Agriculture,Uppsala,Sweden,2005:81-89.
    [60]Leinonen I,Jones H G.Combining thermal and visible imagery for estimating canopy temperature and identifying plant stress[J].Journal of Experimental Botany,2004,55(401):1423-1431.
    [61]Dejonge K C,Taghvaeian S,Trout T J,et al.Comparison of canopy temperature-based water stress indices for maize[J].Agricultural Water Management,2015,156:51-62.
    [62]Hardin P,Jensen R.Small-scale unmanned aerial vehicles in environmental remote sensing:Challenges and opportunities[J].Mapping Sciences&Remote Sensing,2011,48(1):99-111.
    [63]Shi Y,Ji S P,Shao X W,et al.Framework of SAGI agriculture remote Sensing and its perspectives in supporting national food security[J].Journal of Integrative Agriculture,2014,13(7):1443-1450.

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