遥感技术与应用 2019, Vol. 34 Issue (1): 21-32 DOI: 10.11873/j.issn.1004-0323.2019.1.0021 |
综述 |
|
|
|
|
作物病虫害遥感监测和预测预警研究进展 |
鲁军景1,2,孙雷刚1,2,黄文江3 |
(1.河北省科学院地理科学研究所,河北 石家庄050021;
2.河北省地理信息开发应用工程技术研究中心,河北 石家庄050021;
3.中国科学院遥感与数字地球研究所 数字地球重点实验室,北京100094) |
|
Research Progress in Monitoring and Forecasting of Crop Diseases and Pests by Remote Sensing |
Lu Junjing1,2,Sun Leigang1,2,Huang Wenjiang3 |
(1.Institute of Geographical Sciences,Hebei Academy of Sciences,Shijiazhuang 050021,China;
2.Hebei Engineering Research Center for Geographic Information Application,
Shijiazhuang 050021,China;3.Key Laboratory of Digital Earth Science,Institute of Remote
Sensing and Digital Earth,Chinese Academy of Sciences,Beijing 100094,China) |
[1]Huo Zhiguo,Liu Wancai,Shao Zhenrun,et al.On Developing Long Term Meteorological Prediction Research of Crop Pests and Diseases Prevailing in China[J].Journal of Natural Disasters,2000,9(1):117-121.[霍治国,刘万才,邵振润,等.试论开展中国农作物病虫害危害流行的长期气象预测研究[J].自然灾害学报,2000,9(1):117-121.]
[2]Huang Wenjiang,Zhang Jincheng,Luo Juhua,et al.Remote Sensing Monitoring and Forecasting of Crop Pests and Diseases[M].Beijing:Science Press,2015.[黄文江,张竞成,罗菊花,等.作物病虫遥感监测与预测[M].北京:科学出版社,2015.]
[3]Lu Junjing,Huang Wenjiang,Zhang Jingcheng,et al.Quantitative Identification of Yellow Rust and Powdery Mildew in Winter Wheat based on Wavelet Feature[J].Spectroscopy and Spectral Analysis,2016,36(6):1854-1858.[鲁军景,黄文江,张竞成,等.基于小波特征的小麦白粉病与条锈病的定量识别研究[J].光谱学与光谱分析,2016,36(6):1854-1858.]
[4]Sankaran S,Mishra A,Ehsani R,et al.A Review of Advanced Techniques for Detecting Plant Diseases[J].Computers and Electronics in Agriculture,2010,72(1):1-13.
[5]Yuan Lin,Zhang Jingcheng,Zhao Jinlin,et al.Differentiation of Yellow Rust and Powdery Mildew in Winter Wheat and Retrieving of Disease Severity based on Leaf Level Spectral Analysis[J].Spectroscopy and Spectral Analysis,2013,33(6):1608-1614.[袁琳,张竞成,赵晋陵,等.基于叶片光谱分析的小麦白粉病与条锈病区分及病情反演研究[J].光谱学与光谱分析,2013,33(6):1608-1614.]
[6]Guan Q S,Huang W J,Zhao J L,et al.Quantitative Identification of Yellow Rust,Powdery Mildew and Fertilizer-water Stress in Winter Wheat Using In-situ Hyperspectral Data[J].Sensor Letters,2014,12:1-7.
[7]Zhao J L,Zhang D Y,Luo J H,et al.A Comparative Study on Monitoring Leaf-scale Wheat Aphids Using Pushbroom Imaging and Non-imaging ASD Field Spectrometers[J].International Journal of Agriculture and Biology,2012,14(1):136-140.
[8]Qiao Hongbo,Shi Yue,Si Haiping,et al.Monitoring and Classification of Wheat Take-all in Field based on Imaging Spectrometer[J].Transactions of the Chinese Society of Agricultural Engineering.2014,3(20):172-178.[乔洪波,师越,司海平,等.基于近地成像光谱的小麦全蚀病等级监测[J].农业工程学报,2014,3(20):172-178.]
[9]Jonas F,Menz G.Multi-temporal Wheat Disease Detection by Multi-spectral Remote Sensing[J].Precision Agriculture,2007,8(3):161-172.
[10]Yuan Lin.Identification and Differentiation of Wheat Diseasesand Insects with Multi-source and Multi-scale Remote Sensing Data[D].Hangzhou:Zhejiang University,2015.[袁琳.小麦病虫害多尺度遥感识别和区分方法研究[D].杭州:浙江大学,2015.]
[11]Huang Muyi,Huang Wenjiang,Liu Liangyun,et al.Spectral Reflectance Feature of Winter Wheat Single Leaf Infected with Stripe Rust and Severity Level Inversion[J].Transactions of the Chinese Society of Agricultural Engineering,2004,20(1):176-180.[黄木易,黄文江,刘良云,等.冬小麦条锈病单叶光谱特性及严重度反演[J].农业工程学报,2004,20(1):176-180.]
[12]Graeff S,Link J,Claupein W.Identification of Powdery Mildew and Take-all Disease in Wheat by Means of Leaf Reflectance Measurements[J].Central European Journal of Biology,2006,1(2):275-288.
[13]Zang Hongting.Monitoring and Evaluation the Spatial and Temporal Dynamic Changesof Corn Armyworm based on Remote Sensing Data[D].Harbin:Northeast Agricultural University,2014.[臧红婷.玉米粘虫时空动态遥感监测与评价[D].哈尔滨:东北农业大学,2014.]
[14]Liu Zhanyu.Monitoring the Rice Disease and Insect Stress with Remote Sensing[D].Hangzhou:Zhejiang University,2008.[刘占宇.水稻主要病虫害胁迫遥感监测研究[D].杭州:浙江大学,2008.]
[15]Yang C M,Cheng C H.SpectralCharacteristics of Rice Plants Infested by Brown Plant Hoppers[J].Proceedings of the National Science Council Republic of China Part B Life Sciences,2001,25(3):180-186.
[16]Yang C M,Cheng C H,Chen R K.Changes inSpectral Characteristics of Rice Canopy Infested with Brown Plant Hopper and Leaf Folder[J].Crop Science,2007,47(1):329-335.
[17]Jones C D,Jones J B,Lee W S.Diagnosis of Bacterial Spot Tomato Using Spectral Signatures[J].Computers and Electronics in Agriculture,2010,74(2):329-335.
[18]Jiang Jinbao,Chen Yunhao,Huang Wenjiang.Using Hyperspectral Derivative Index to Monitor Winter Wheat Disease[J].Spectroscopy and Spectral Analysis,2007,27(12):2475-2479.[蒋金豹,陈云浩,黄文江.用高光谱微分指数监测冬小麦病害的研究[J].光谱学与光谱分析,2007,27(12):2475-2479.]
[19]Huang W J,Huang M Y,Liu L Y,et al.Inversion of the severity of Winter Wheat Yellow Rust Using Proper Hyper Spectral Index[J].Transactions of the Chinese Society of Agricultural Engineering.2005,21(4):97-103.
[20]Huang W J,Lamb D W,Niu Z,et al.Identification of Yellow Rust in Wheat Using In-situ Spectral Reflectance Measurements and Airborne Hyperspectral Imaging[J].Precision Agriculture,2007,8(5):187-197.
[21]Lu Junjing,Huang Wenjiang,Jiang Jinbao,et al.Comparison of Wavelet Features and Conventional Spectral Features on Estimating Severity of Stripe Rust in Winter Wheat[J].Journal of Triticeae Crops,2015,35(10):1456-1461.[鲁军景,黄文江,蒋金豹,等.小波特征与传统光谱特征估测冬小麦条锈病病情严重度的对比研究[J].麦类作物学报,2015,35(10):1456-1461.]
[22]Sun Jiayi.Sensitivity of Hyperspectral Reflectance to Monitor Rice Pests and the Monitor Methods for Rice Plant Hoppers[D].Nanjing:Nanjing Agricultural University,2013.[孙嘉怿.水稻叶片高光谱虫害的敏感性及稻飞虱的为害监测[D].南京:南京农业大学,2013.
[23][JP2]Zhang Jingcheng.Methods for Information Extraction of Wheat [JP]Disease based on Multi-source Remote Sensing Data[D].Hangzhou:Zhejiang University,2012.[张竞成.多源遥感数据小麦病害信息提取方法研究[D].杭州:浙江大学,2012.]
[24]Qiao Hongbo,Ma Xinming,Cheng Dengfa,et al.Detecting Infestation of Take-all Disease in Winter Wheat Using TM Image[J].Journal of Triticeae Crops,2009,29(4):716-720.[乔红波,马新明,程登发,等.基于TM影像的小麦全蚀病危害信息提取[J].麦类作物学报,2009,29(4):716-720.]
[25]Luo Juhua.Monitoring and Predicting of Aphid based on Multi-source Remote Sensing Data[D].Beijing:Beijing Normal University,2012.[罗菊花.基于多源数据的小麦蚜虫遥感监测预测研究[D].北京:北京师范大学,2012.]
[26]Lu Junjing.Remote Sensing Monitoring of Powdery Mildew and Yellow Rust in Winter Wheat based on Multi-source Data[D].Beijing:China University of Mining & Technology,2016.[鲁军景.多源数据冬小麦白粉病和条锈病遥感监测研究[D].北京:中国矿业大学,2016.]
[27]Ma Huiqin,Huang Wenjiang,Jing Yuanshu,et al.Remote Sensing Monitoring of Wheat Powdery Mildew based on AdaBoost Model Combining mRMR Algorithm[J].Transactions of the Chinese Society of Agricultural Engineering,2017,33(5):162-169.[马慧琴,黄文江,景元书,等.基于AdaBoost模型和mRMR算法的小麦白粉病遥感监测[J].农业工程学报,2017,33(5):162-169.]
[28]Nie Chenwei,Yuan Lin,Wang Baotong,et al.Monitoring Wheat Powdery Mildew based on Integrated Remote Sensing and Meteorological Information[J].Acta Phytopathologica Sinica,2016,46(2):285-288.[聂臣巍,袁琳,王保通,等.综合遥感与气象信息的小麦白粉病监测方法[J].植物病理学报,2016,46(2):285-288.]
[29]Ma Ning,Meng Zhijun,Wang Pei,et al.Research Summary on Forecasting Methods of Crop Pests and Diseases[J].Journal of Heilongjiang Bayi Agricultural University,2016,28(1):15-18.[马宁,孟志军,王培,等.农作物病虫害预报方法研究综述[J].黑龙江八一农垦大学学报,2016,28(1):15-18.]
[30]Scherm H,Yang X B.Atmospheric Teleconnection Patterns Associated with Wheat Stripe Rust Disease in North China[J].International Journal of Biometeorology,Berlin,Germany,1998.42(1):28-33.
[31]Maelzer D A,Zalucki M P.Long Range Forecasts of the Numbers of Helicoverpa Punctigera and H.armigera(Lepidoptera:Noctuidae) in Australia Using the Southern Oscillation Index and the Sea Surface Temperature[J].Bulletin of Entomological Research.2000,90(2):133-146.
[32]Huo Zhiguo,Ye Cailing,Qian Shuan,et al.Relationship between Climatic Anomaly and Prevailling of the Wheat Powdery Mildew in China[J].Journal of Natural Disasters,2002,11(1):85-90.[霍治国,叶彩玲,钱栓,等.气候异常与中国小麦白粉病灾害流行关系的研究[J].自然灾害学报,2002,11(1):85-90.]
[33]Yang Hongsheng,Ji Rong,Wang Ting.Atmospheric Circulation Background and Long-term Prediction of Grasshopper Occurrence in Xinjiang[J].Chinese Journal of Ecology,2008,27(2):218-222.[杨洪升,季荣,王婷.新疆蝗虫发生的大气环流背景及长期预测[J].生态学杂志,2008,27(2):218-222.]
[34]Strand J F.Some Agrometeorological Aspects of Pest and Disease Management for the 21st Century[J].Agricultural and Forest Meteorology,2000,103(1-2):73-82.
[35]Baker K M,Kirk W W.Comparative Analysis of Models Integrating Synoptic Forecast Data into Potato Late Blight Risk Estimate Systems[J].Computers and Electronics in Agriculture,2007,57(1):23-32.
[36]Tan W Z,Li C W,Bi C W,et al.A Computer Software-Epitimulator for Simulating Temporal Dynamics of Plant Disease Epidemic Progress[J].Agricultural Sciences in China,2010,9(2):242-248.
[37]Zhang Lei.Variation and Regional Dynamic Warning of Crop Disease and Pests under Climate Change[D].Beijing:Chinese Academy of Meteorological Sciences,2013.[张蕾.气候变化背景下农作物病虫害的变化及区域动态预警研究[D].北京:中国气象科学研究院,2013.]
[38]Tang Cuicui,Huang Wenjiang,Luo Juhua,et al.Forecasting Wheat Aphid with Remote Sensing based on Relevance Vector Machine[J].Transactions of the Chinese Society of Agricultural Engineering,2015,31(6):201-207.[唐翠翠,黄文江,罗菊花,等.基于相关向量机的冬小麦蚜虫遥感预测[J].农业工程学报,2015,31(6):201-207.]
[39]Dutta S,Singh S K,Khullar M.A Case Study on Forewarning of Yellow Rust Affected Areas on Wheat Crop Using Satellite Data[J].Journal of the Indian Society of Remote Sensing,2014,42(2):335-342.
[40]Ma Huiqin,Huang Wenjiang,Jing Yuanshu.Wheat Powdery Mildew Forecasting in Filling Stage based on Remote Sensing and Meteorological Data[J].Transactions of the Chinese Society of Agricultural Engineering,2016,32(9):165-172.[马慧琴,黄文江,景元书.遥感与气象数据结合预测小麦灌浆期白粉病[J].农业工程学报,2016,32(9):165-172.]
[41]Delwiche S R,Kim M S.Hyperspectral Imaging for Detection of Scab in Wheat[C]∥Environmental and Industrial Sensing:Biological Quality and Precision Agriculture Ⅱ,Proceedings of SPIE,2000,4203:13-20.
[42]Moshou D,Bravo C,West J,et al.Automatic Detection of Yellow Rust in Wheat Using Reflectance Measurements and Neural Networks[J].Computers and Electronics in Agriculture,2004,44:173-188.
[43]Liu Liangyun,Huang Muyi,Huang Wenjiang,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.[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.遥感学报,2004,8(3):275-281.]
[44]Liu Z Y,Wu H F,Huang J F.Application of Neural Networks to Discriminate Fungal Infection Levels in Rice Panicles Using Hyperspectral Reflectance and Principal Components Analysis[J].Computers and Electronics in Agriculture,2010,70(2):99-106.
[45]Demetriades-Shah T H,Steven M D,Clark J A.High Resolution Derivative Spectra in Remote Sensing[J].Remote Sensing of Environment,1990,33(1):55-64.
[46][JP2]Gamon J A,Penuelas J,Field C B.A Narrow-waveband Spectral Index That Tracks Diurnal Changes in Photosynthetic Efciency[J].Remote Sensing of Environment,1992,41:35-44.[JP]
[47]Naidu R A,Perry E M,Pierce F J,et al.The Potential of Spectral Reflectance Technique for the Detection of Grapevine Leaf Roll-associated Virus-3 in Two Red-berried Wine Grape Cultivars[J].Computers and Electronics in Agriculture,2009,66(1):38-45.
[48]Huang W J,Guan Q S,Luo J H,et al.New Optimized Spectral Indices for Identifying and Monitoring Winter Wheat Diseases[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2014,7(6):2516-2524.
[49]Cheng T,Rivard B,Sanchenz-azofeifa G A.Spectroscopic Determination of Leaf Water Content Using Continuous Wavelet Analysis[J].Remote Sensing of Environment,2011,115(2):662.
[50]Cheng T,Rivard B,Sánchez-Azofeifa A,et al.Continuous Wavelet Analysis for the Detection of Green Attack Damage due to Mountain Pine Beetle Infestation[J].Remote Sensing of Environment,2010,114(4):899-910.
[51]Zhang J C,Yuan L,Pu R L,et al.Comparison between Wavelet Spectral Features and Conventional Spectral Features in Detecting Yellow Rust for Winter Wheat[J].Computers and Electronics in Agriculture,2014,100:79-87.
[52]Shi Y,Huang W J,Zhou XF,et al.Evaluation of Wavelet Spectral Features in Pathological Detection and Discrimination of Yellow Rust and Powdery Mildew in Winter Wheat with Hyperspectral Reflectance Data[J].Journal of AppliedRemote Sensing,2017,11(2):026025.
[53]Shi Y,Huang W J,González-Moreno P,et al.Wavelet-based Rust Spectral Feature Set(WRSFs):A Novel Spectral Feature Set based on Continuous Wavelet Transformation for Tracking Progressive Host-Pathogen Interaction of Yellow Rust on Wheat[J].Remote Sensing,2018,10(4):525.
[54]Huang W J,Lu J J,Ye H C,et al.Quantitative Identification of Crop Disease and Nitrogen-water Stress in Winter Wheat Using Continuous Wavelet Analysis[J].International Journal of Agricultural and Biological Engineering,2018,11(2):145-152.
[55]Xie Fei.Research and Implementation of Image Texture Feature Extraction and Image Classification System[D].Beijing:University of Electronic Science and Technology of China,2009.[谢菲.图像纹理特征的提取和图像分类系统研究及实现[D].北京:电子科技大学,2009.]
[56]Zhu Yun.The Detection of Fruit Tree Pests based on Digital Image Processing[D].Zhengzhou:North China University of Water Resources and Electric Power,2012.[朱云.基于数字图像处理的果树病虫害智能化检测[D].郑州:华北水利水电学院,2012.]
[57]Bu Yadong.Research of Image Texture Feature Extraction[D].Ji’nan:Shandong Normal University,2012.[步亚东.图像纹理特征提取的研究[D].济南:山东师范大学,2012.]
[58]Guo Qing,Wang Liwen,Dong Fangmin,et al.Identification of Wheat Stripe Rust and Powdery Mildew Using Orientation Coherence Feature[J].Transactions of the Chinese Society of Agricultural Machinery,2015,46(1):26-34.[郭青,王骊雯,董方敏,等.基于方向一致性特征的小麦条锈病与白粉病识别[J].农业机械学报,2015,46(1):26-34.]
[59]Chestmore D,Bernard T,Inman A J,et al.Image Analysis for the Identification of the Quarantine Pest Tilletia Indica[J].EPPO Bulletin,2003,3(3):495-499.
[60]Ahmad I S,Reid J F.Evaluation of Colour Representations for Maize Images[J].Journal of Agricultural Engineering Research,1996,63:185-196.
[61]Martin D P,Rybicki E P.Microcomputer-based Quantification of Maize Streak Virus Symptom in Zeamays[J].Phtopathology,1998,88(5):422-427.
[62]Shatadal P,Tan J.Identifying Damaged Soybeans by Color Image Analysis[J].Applied Engineering in Agriculture,2003,9(1):65-69.
[63]Hu Chunhua,Li Pingping.Application of Image Processing to Diagnose Cucumbers Short of Mg and N[J].Journal of Jiangsu University:Natural Science Edition,2004,25(1):9-12.[胡春华,李萍萍.基于图像处理的黄瓜缺氮与缺镁判别的研究[J].江苏大学学报:自然科学版,2004,25(1):9-12.]
[64]Ma Xiaodan,Qi Guangyun.Investigation and Recognition on Diseased Spots of Soybean Laminae based on Neural Network[J].Journal of Heilongjiang August First Land Reclamation University,2006,18(2):84-87.[马晓丹,祁广云.基于神经网络的大豆叶片病斑的识别与研究[J].黑龙江八一农垦大学学报,2006,18(2):84-87.]
[65]Lai Junchen.Research on Maize Diseases Intelligent Diagnosis based on Disease Images[D].Shihezi:Shihezi University,2010.[赖军臣.基于病症图像的玉米病害智能诊断研究[D].石河子:石河子大学,2010.]
[66]Wang Keru.Diagnosis of Crop Disease,Insect Pest and Weed based on Image Recognition[D].Beijng:Chinese Academy of Agricultural Science,2005.[王克如.基于图像识别的作物病虫草害诊断研究[D].北京:中国农业科学院,2005.]
[67]Zhang Jing,Wang Shuangxi,Dong Xiaozhi,et al.A Study on Method of Extract of Texture Characteristic Value in Image Processing for Plant Disease of Greenhouse[J].Journal of Shenyang Agricultural University,2006,37(3):282-285.[张静,王双喜,董晓志,等.基于温室植物叶片纹理的病害图像处理及特征提值取方法的研究[J].沈阳农业大学学报.2006,37(3):282-285.]
[68]Qi Xinglan,Study on Information Extraction Technology of Dendrolimus Punctatus Damage based on SPOT-5 Remote Sensing Images[D].Fuzhou:Fujian Agriculture and Forestry University,2011.[亓兴兰.SPOT-5遥感影像马尾松毛虫害信息提取技术研究[D].福州:福建农林大学,2011.]
[69]Xu Guili,Mao Hanping,Li Pingping.Research on Extraction Leaf Texture Features as Sample of Nutrient Shortage by Percent Histogram of Differentiation[J].Transactions of the Chinese Society of Agricultural Machinery,2003,34(2):76-79.[徐贵力,毛罕平,李萍萍.差分百分率直方图法提取缺素叶片纹理特征[J].农业机械学报,2003,34(2):76-79.]
[70]Patil J K,Kumar R.Feature Extraction of Diseased Leaf Images[J].Journal of Signal and Image Processing,2012,3(1):60-63.
[71]Bryceson K P.Digitally Processed Satellite Data as A Tool in Detecting Potential Australian Plague Locust Outbreak Areas[J].Journal of Environmental Management,1990,30:191-207.
[72]Bryceson K P.TheUse of Landsat MSS Data to Determine the Distribution of Locust Eggbeds in the Riverina Region of New South Wales[J].Australia International Journal of Remote Sensing,1989,10:1749-1762.
[73]Bryceson K P,Wright D E.AnAnalysis of the 1984 Locust Plague in Australia Using Multitemporal Landsat Multispectral Data and ASimulation Model of Locust Development[J].Agriculture,Ecosystems and Environment,1986,16:87-102.
[74]Michael C,Pierre M,Etienne B,et al.Spot Vegetation Contribution to Desert Locust Habitat Monitoring[C]∥Vegetation 2000 Conference,2017,CD-ROM :247-258.
[75]Wolter P T,Townsend P A,Sturtevant B R,et al.Remote Sensing of the Distribution and Abundance of Host Species for Spruce Budworm in Northern Minnesota and Ontario[J].Remote Sensing of Environment,2008,112:3971-3982.
[76]Baret F,Vanderbilt V C,Steven M D,et al.Use of Spectral Analogy to Evaluate Canopy Reflectance Sensitivity to Leaf Optical Properties[J].Remote Sensing of Environment,1994,48(2):253-260.
[77]Rouse J W,Haas R H,Schell J A,et al.Monitoring Vegetation Systems in the Great Plains with ERTS[J].Third ERTS Symposium,NASA SP-351,NASA,1973,1:309-317.
[78]Chen J M.Evaluation ofVegetation Indices and A Modified Simple Ratio for Boreal Applications[J].Canadian Journal of Remote Sensing,1996,22:229-242.
[79]Gitelson A A,Merzlyak M N,Chivkunova O B.Optical Properties and Nondestructive Estimation of Anthocyanin Content in Plant Leaves[J].Photochemistry and Photobiology,2001,74:38-45.
[80]Roujean J L,Breon F M.Estimating PAR Absorbed by Vegetation from Bidirectional Reflectance Measurements[J].Remote Sensing of Environment,1995,51:375-384.
[81]Devadas R,Lamb D W,Simpfendorfer S,et al.Evaluating Ten Spectral Vegetation Indices for Identifying Rust Infection in Individual Wheat Leaves[J].Precision Agriculture,2009,10:459-470.
[82]Rondeaux G,Steven M,Baret F.Optimization of Soil-adjusted Vegetation Indices[J].Remote Sensing Environment,1996,55(2):95-107.
[83]Kim M S,Daughtry C S T,Chappelle E W,et al.The Use of High Spectral Resolution Bands for Estimating Absorbed Photosynthetically Active Radiation(APAR)[C]∥Proceedings of the 6th International Symposium on Physical Measurements and Signatures in Remote Sensing,France:Val d’Isere,1994:299-306.
[84]Haboudane D,Miller J R,Tremblay N,et al.Integrated Narrowband Vegetation Indices for Prediction of Crop Chlorophyll content for Application to Precision Agriculture[J].Remote Sensing of Environment,2002,81:416-426.
[85]Merton R,Huntington J.Early Simulation of the ARIES-1 Satellite Sensor for Multi-temporal Vegetation Research derived from AVIRIS[R].Summaries of the Eight JPL Airborne Earth Science Workshop.Pasadena,CA:JPL Publication,1999:299-307.
[86]Gong P,Pu R L,Heald R C.Analysis of in Situ Hyperspectral Data for Nutrient Estimation of Giant Sequoia[J].International Journal of Remote Sensing,2002,23(9):1827-1850.
[87]Pu R L,Ge S,Kelly N M,et al. Spectral Absorption Features as Indicators of Water Status in Coast Live Oak(Quercus Agrifolia) Leaves[J].International Journal of Remote Sensing,2003,24(9):1799-1810.
[88]Muhammed H H,Larsolle A.FeatureVector based Analysis of Hyperspectral Crop Reflectance Data for Discrimination and Quantification of Fungal Disease Severity in Wheat[J].Biosystems Engineering,2003,86(2):125-134.
[89]Li Bo,Liu Zhanyu,Huang Jingfeng.Hyperspectral Identification of Rice Diseases and Pests based on Principal Pomponent Analysis and Probabilistic Neural Network[J].Transactions of the Chinese Society of Agricultural Engineering,2009,25(9):143-147.[李波,刘占宇,黄敬峰,等.基于PCA 和PNN 的水稻病虫害高光谱识别[J].农业工程学报,2009,25(9):143-147.]
[90]Costa G,Noferini M,Fiori G,et al.Innovative Application of Non-destructive Techniques for Fruit Quality and Disease Diagnosis[J].Acta Horticulturae,2007,753(1):275-282.
[91]Shen Wenying,Li Yingxue,Feng Wei,et al.Inversion Model for Severity of Powdery Mildew in Wheat Leaves based on Factor Analysis-BP Neural Network[J].Transactions of the Chinese Society of Agricultural Engineering,2015,22(31):183-190.[沈文颖,李映雪,冯伟,等.基于因子分析-BP神经网络的小麦叶片白粉病反演模型[J].农业工程学报,2015,22(31):183-190.]
[92]Lin Na,Yang Wunian.Hyperspectral Remote Sensing Image Feature Extraction based on Kernel Mininum Noise Fraction Transformation[J].Remote Sensing Technology and Application,2013,28(2):245-251.[林娜,杨武年.基于核最小噪声分离变换的高光谱遥感影像特征提取研究[J].遥感技术与应用,2013,28(2):245-251.]
[93]Bai Lin,Hui Meng.Classification and Feature Extraction of Hyperspectral Images based on Improved Minimum Noise Fraction Transformation[J].Computer Engineering & Science,2015,37(7):1344-1348.[白璘,惠萌.基于改进最小噪声分离变换的特征提取与分类[J].计算机工程与科学,2015,37(7):1344-1348.]
[94]Zhu Yubo.Hyperspectral Monitoring the Damage of Rice by Leaf Folder Cnaphalocrocis Medinalis GENE[D].Nanjing:Nanjing Agricultural University,2012.[朱宇波.稻纵卷叶螟危害水稻的高光谱监测方法研究[D].南京:南京农业大学,2012.]
[95]Ji Huihua.Early Detection of Rice Disease and Pests Using Spectrum Analysis Technology[D].Hangzhou:China Jiliang University,2013.[季慧华.基于光谱分析技术的水稻病虫害早期检测研究[D].杭州:中国计量学院,2013.]
[96]Mi Yating,Research on Greenhouse Tomato Disease Diagnosis based on GA-BP Network[D].Harbin:Norseast Forest University,2016.[米雅婷.基于GA-BP神经网络的温室番茄病害诊断研究[D].哈尔滨:东北林业大学,2016.]
[97]Gao Guolong,Du Huaqiang,Han Ning,et al.Mapping of Moso Bamboo Forest Using Object-based Approach based on the Optimal Features[J].Scientia Silvae Sinicae,2016,9(52):77-85.[高国龙,杜华强,韩凝,等.基于特征优选的面向对象毛竹林分布信息提取[J].林业科学,2016,9(52):77-85.]
[98][JP2]Xiao Yan,Jiang Qigang,Wang Bin,et al.Objectbased Land-use Classification based on Hybrid Feature Selection Method of Combing ReliefF and PSO[J].Transactions of the Chinese Society of Agricultural Engineering,2016,32(4):211-216.[肖艳,姜琦刚,王斌,等.基于ReliefF和PSO混合特征选择的面向对象土地利用分类[J].农业工程学报,2016,32(4):211-216.][JP]
[99]Wang Lu,Gong Guanghong.Multiple Features Remote Sensing Image Classification based on Combining RelieF and mRMR[J].Chinese Journal of Stereology and Image Analysis,2014,19(3):250-257.[王露,龚光红.基于ReliefF+mRMR特征降维算法的多特征遥感图像分类[J].中国体视学与图像分析,2014,19(3):250-257.][ZK)]
[100]Cheng Ximeng,Sheng Zhanfeng,Xing Tingyan,et al.Efficiency and Accuracy of Multispectral Image Classification based on mRMR Feature Selection Method[J].Journal of Geo-information Science,2016,6(18):815-823.[程希萌,沈占锋,邢廷炎,等.基于mRMR特征优选算法的多光谱遥感影像分类效率精度分析[J].地理信息科学学报,2016,6(18):815-823.][ZK)]
[101]Zhang Yadong.Research on Buildings Extraction of Remote Sensing Image based on Morphology[D].Changchun:Jilin University,2017.[张亚东.基于形态学的遥感影像房屋提取研究[D].长春:吉林大学,2017.]
[102]Jiang Y,Li C Y.mRMR-based Feature Selection for Classification of Cotton Foreign Matter Using Hyperspectral Imaging[J].Computers and Electronics in Agriculture.2015,119:191-200.
[103]Muhammed H H.Hyperspectral Crop Reflectance Data for Characterizing and Estimating Fungal Disease Severity in Wheat[J].Biosystems Engineering,2005,91(1):9-20.
[104]Wang Jing,Jing Yuanshu,Huang Wenjiang,et al.Comparative Research on Estimating the Severity of Yellow Rust in Winter Wheat[J].Spectroscopy and Spectral Analysis,2015,35(6):1649-1653.[王静,景元书,黄文江,等.冬小麦条锈病严重度不同估算方法对比研究[J].光谱学与光谱分析.2015,35(6):1649-1653.]
[105]Shi Y,Huang W J,Ye H C,et al.Partial Least Square Discriminant Analysis based on Normalized Two-stage Vegetation Indices for Mapping Damage from Rice Diseases Using Planet Scope Datasets[J].Sensors,2018,18(6):1901.
[106]Zheng Q,Huang W J,Cui X M,et al.New Spectral Index for Detecting Wheat Yellow Rust Using Sentinel-2 Multispectral Imagery[J].Sensors,2018,18(3):868.
[107]Shi Jingjing,Liu Zhanyu,Zhang Lili.Hyperspectral Recognition of Rice Damage by Rice Leaf Roller based on Supper Vector Machine[J].Chinese Journal of Rice Science,2009,23(3):331-334.[石晶晶,刘占宇,张莉丽.基于支持向量机(SVM)的稻纵卷叶螟危害水稻高光谱遥感识别[J].中国水稻科学,2009,23(3):331-334.]
[108]Sun Jun,Tan Wenjun,Mao Hanping,et al.Recognition of Multiple Plant Leaf Diseases based onImproved Convolutional Neural Network[J].Transactions of the Chinese Society of Agricultural Engineering,2017,33(19):209-215.[孙俊,谭文军,毛罕平,等.基于改进卷积盛景网络的多种植物叶片病害识别[J].农业工程学报,2017,33(19):209-215.]
[109]Zhang Chu.Detection Mechanism and Methodology of Brassicanapus Disease Using Spectroscopy and Spectral Imaging Technologies[D].Hangzhou:Zhejiang University,2016.[张初.基于光谱与光谱成像技术的油菜病害监测机理与方法研究[D].杭州:浙江大学,2016.]
[110]Feng Jie.Multispectral Imaging System for the Plant Diseases and Insect Pests Diagnosis[J].Spectral and Spectral Analysis,2009,29(4):1008-1012.[冯洁.用于植物病虫害诊断的多光谱成像系统[J].光谱学与光谱分析,2009,29(4):1008-1012.] |
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|