基于光谱信息的植被氮素快速探测仪器研究
摘要
最近几十年来,我国农业取得巨大成就的同时也面临着日益严重的危机,其中,化肥和农药过量投入问题,给生态环境、农产品安全和农业可持续发展都造成了巨大的压力。为了有效遏制这一局面,需要利用快速、无损、低成本的作物营养及长势信息探测设备来指导农业生产,实现按需施肥,增产的同时减少对环境的破坏。氮素是直接反映植被营养状况及代谢的重要组分,也是长势监测、营养诊断乃至品质评价的重要指标。便携式、实时、准确的植被氮素营养监测与诊断仪器是作物氮肥科学管理基运筹调控的必要手段和关键设备之一。本论文以研制植被冠层氮素的快速探测仪器为目标,以不同的技术方案对植被氮素含量快速探测的关键技术进行了研究,完成的主要研究成果和结论如下：
(1)研制了以太阳光为光源,以滤光片为分光器件的被动光源式植被冠层氮素探测仪器—一(NRI-0SAVI)一体化氮素测量仪。该仪器以硅光电探测器为探测传感器,通过测量570nm、670nm和800nm三个特征波长处太阳的入射光和植被冠层的反射光,计算出三个特征波长的反射率,最终计算得到NRI和OSAVI植被指数值,可同时测定植被的氮素含量和长势青况。传感器视场角为60°,测量高度可变。试验表明,该被动式氮素测量仪器的测量值与ASD光谱仪的测量数值相比具有很好的相关性。
(2)为了克服被动式光谱测量仪器受环境影响大、工作时间短的劣势,采用LED主动光源脉冲发光技术,进行了主动发光的植被氮素探测仪器研究。首先通过LED主动发出670nm和800nm两个特征波长的脉冲光到探测冠层上,然后再探测该主动光的反射能量,并减去作为背景的太阳光反射能量,计算出两个特征波长处的反射率。接着,利用反射率计算得到反映冠层氮素水平的NDVI植被指数值。该传感器在一定范围内测量结果不受探测高度的影响。实验表明,本氮素测量仪器的测量值与ASD光谱仪的测量数值相比具有很好的相关性。在不同光照条件下的测试表明,该仪器的测量值受太阳光环境影响较小。
(3)由于氮素“易运转”的特性,植被叶片氮素含量在植被上表现出明显的垂直分布特性,本论文研究引入多波段激光雷达技术,获取植被的完整的回波信息,开展了植被氮素含量垂直探测的试验研究。首先推导了复杂散射体的激光雷达方程,然后用6种波段针对3个不同的场景进行了回波模拟,探讨了多波段激光雷达在植被氮素含量方面的潜力。接着,详细介绍了多光谱全波形激光雷达样机的研制。该激光雷达以超连续谱脉冲激光器为光源,以望远镜为信号收集单元,以高速光电转换器为传感器,具有同轴发送接收,全波形记录的特点。其探测的距离分辨率约为15cm,探测的发散角为4mrad,最佳探测距离为20米。根据分光方式不同,本文提出并试验了两种光电探测方案,其一是利用滤光片分光,配合两个分立的雪崩二极管APD模块,实现2个波段的波形探测：其二是利用光栅分光,配合光电倍增管PMT阵列,实现32通道的波形探测。目前的实验表明,方案一可以获取较好的探测波形,能满足设计要求。而方案二由于PMT线阵输出的值较小,获取的波形不太理想,还需要进一步改进。试验表明,该仪器在测距精度方面优于15cm,在多光谱信息获取方面,信噪比较高,能构造植被指数实现分类,还可实现氮素含量垂直探测。整体而言,所设计的仪器具备了生产具有光谱信息的3D点云能力。
In recent years, China's agriculture has made great achievemnets as well as facing increasingly serious crisis. The excessive investment of chemical fertilizers and pesticides gave great pressure to the safety of agricultural products, ecological environment and the sustainalble development of agricuture. In order to effectively curb this situation, we need fast, non-destructive and low cost of crop nutrition and growth information detection equipment to guide the agricultural production to achieve fertilization according to needs, increase production and reduce damage to the environment. Nitrogen is a metabolism of vegetation which directly reflects the mutrition. It is an important index for monitoring of corop growth, nutrition diagnosis and quality evaluation. Portable, real-time,accurate vegetation nitrogen monitoring and diagnosis instrument is one of the necessary means and key equipment for crop nitrogen management. The goal of this thesis is to develop rapid detection instrument for the canopy nitrogen. Three different technologies were studied. The followings are the main research results and conclusions.
1) A novel instrument for measuring nitrogen refect index (NRI) and optimization soil-adjusted vegetation index (OSAV1) is introduced. Through measuring the incident light and the reflected light at570nm,670nm and800nm, the instrument could measure the vegetation index accurately according to the automatic calibration techniques based on the least squares estimation. By using the signal processing method, the problem caused by the weak signal and the sun angle was solved. This instrument measured the vegetation index conveniently, and the results had a very good correlation with the values measured by ASD.The experiments indicated that instrument could be used for non-destructive measuring the crop nitrogen. The instrument had the characters of low power consumption, high sensitivity and rapid response time. The crop nutrient measured by the instrument could be used for variable rate fertilization.
2) In order to overcome the disadvantages of passive measuring instrument, the LED active light pulse light was introduced and the active vegetation nitrogen detection instrument was researched. Firstly, the light with wavelengths at670nm and800nm was emitted by two kinds of LED and injected to the target. And the refection light was detected and the sunlight was subtracted as background. The the reflection and NDVI was calculated.The field of view of the instrument is60°, and the measuring results are not affected by the probe height. Experiments show that the result of the instrument has good correlation with the result tested by the ASD spectrometer. The environmental impact to the instrument is very little.
3) Because of nitrogen is the elements which are easy transfer, nitrogen vertical distribution is common on many vegetation. Considering the retrieval limitation relying only on solar illumination, the multispectral full-wave lidar will be studied for the retrieval of nitrogen concentration vertical distribution. Firstly, solid scatterer model according to the back scattering feature of vegetaion objects was established. Secondly, the multi-channel LiDAR waveform was simulated with the consideration of single scatter of plant radiative transfer model. The variation of LAI and chlorophyll along plant height was investigated for maize and three typical scenarios were assumed. The multi-channel return full waveform LiDAR simulation was carried out based on reflectance calculated by radiative transfer model. The simulation at specific wavelength (531nm,550nm,670nm,780nm,1064nm,1550nm) showed that the multi-channel LiDAR waveform could reflect the variation of plant physiological composition and facilitate the inversion algorithm design. At last, the multi-channel LiDAR prototype was developed. The light source used is a supercontinuum laser source with an average output power of100mW. A telescope collected the scattered laser pulse from the target. According to the different of the sensor and spectrophotometric method, we proposed two schemes. In the first scheme, the focal point of the telescope is imaged onto two avalanche photodiode sensors. And we can get two-channel LiDAR. In the second scheme, the focal point of the telescope is transformed to a grating, and the splitled light was measured by the PMT line sensor. A32-channel LiDAR was achieved. Expeiment shows that the firt scheme can obtain better waveform. Using this instrument,3D clouds with spectral information will be got.
(1)研制了以太阳光为光源,以滤光片为分光器件的被动光源式植被冠层氮素探测仪器—一(NRI-0SAVI)一体化氮素测量仪。该仪器以硅光电探测器为探测传感器,通过测量570nm、670nm和800nm三个特征波长处太阳的入射光和植被冠层的反射光,计算出三个特征波长的反射率,最终计算得到NRI和OSAVI植被指数值,可同时测定植被的氮素含量和长势青况。传感器视场角为60°,测量高度可变。试验表明,该被动式氮素测量仪器的测量值与ASD光谱仪的测量数值相比具有很好的相关性。
(2)为了克服被动式光谱测量仪器受环境影响大、工作时间短的劣势,采用LED主动光源脉冲发光技术,进行了主动发光的植被氮素探测仪器研究。首先通过LED主动发出670nm和800nm两个特征波长的脉冲光到探测冠层上,然后再探测该主动光的反射能量,并减去作为背景的太阳光反射能量,计算出两个特征波长处的反射率。接着,利用反射率计算得到反映冠层氮素水平的NDVI植被指数值。该传感器在一定范围内测量结果不受探测高度的影响。实验表明,本氮素测量仪器的测量值与ASD光谱仪的测量数值相比具有很好的相关性。在不同光照条件下的测试表明,该仪器的测量值受太阳光环境影响较小。
(3)由于氮素“易运转”的特性,植被叶片氮素含量在植被上表现出明显的垂直分布特性,本论文研究引入多波段激光雷达技术,获取植被的完整的回波信息,开展了植被氮素含量垂直探测的试验研究。首先推导了复杂散射体的激光雷达方程,然后用6种波段针对3个不同的场景进行了回波模拟,探讨了多波段激光雷达在植被氮素含量方面的潜力。接着,详细介绍了多光谱全波形激光雷达样机的研制。该激光雷达以超连续谱脉冲激光器为光源,以望远镜为信号收集单元,以高速光电转换器为传感器,具有同轴发送接收,全波形记录的特点。其探测的距离分辨率约为15cm,探测的发散角为4mrad,最佳探测距离为20米。根据分光方式不同,本文提出并试验了两种光电探测方案,其一是利用滤光片分光,配合两个分立的雪崩二极管APD模块,实现2个波段的波形探测：其二是利用光栅分光,配合光电倍增管PMT阵列,实现32通道的波形探测。目前的实验表明,方案一可以获取较好的探测波形,能满足设计要求。而方案二由于PMT线阵输出的值较小,获取的波形不太理想,还需要进一步改进。试验表明,该仪器在测距精度方面优于15cm,在多光谱信息获取方面,信噪比较高,能构造植被指数实现分类,还可实现氮素含量垂直探测。整体而言,所设计的仪器具备了生产具有光谱信息的3D点云能力。
In recent years, China's agriculture has made great achievemnets as well as facing increasingly serious crisis. The excessive investment of chemical fertilizers and pesticides gave great pressure to the safety of agricultural products, ecological environment and the sustainalble development of agricuture. In order to effectively curb this situation, we need fast, non-destructive and low cost of crop nutrition and growth information detection equipment to guide the agricultural production to achieve fertilization according to needs, increase production and reduce damage to the environment. Nitrogen is a metabolism of vegetation which directly reflects the mutrition. It is an important index for monitoring of corop growth, nutrition diagnosis and quality evaluation. Portable, real-time,accurate vegetation nitrogen monitoring and diagnosis instrument is one of the necessary means and key equipment for crop nitrogen management. The goal of this thesis is to develop rapid detection instrument for the canopy nitrogen. Three different technologies were studied. The followings are the main research results and conclusions.
1) A novel instrument for measuring nitrogen refect index (NRI) and optimization soil-adjusted vegetation index (OSAV1) is introduced. Through measuring the incident light and the reflected light at570nm,670nm and800nm, the instrument could measure the vegetation index accurately according to the automatic calibration techniques based on the least squares estimation. By using the signal processing method, the problem caused by the weak signal and the sun angle was solved. This instrument measured the vegetation index conveniently, and the results had a very good correlation with the values measured by ASD.The experiments indicated that instrument could be used for non-destructive measuring the crop nitrogen. The instrument had the characters of low power consumption, high sensitivity and rapid response time. The crop nutrient measured by the instrument could be used for variable rate fertilization.
2) In order to overcome the disadvantages of passive measuring instrument, the LED active light pulse light was introduced and the active vegetation nitrogen detection instrument was researched. Firstly, the light with wavelengths at670nm and800nm was emitted by two kinds of LED and injected to the target. And the refection light was detected and the sunlight was subtracted as background. The the reflection and NDVI was calculated.The field of view of the instrument is60°, and the measuring results are not affected by the probe height. Experiments show that the result of the instrument has good correlation with the result tested by the ASD spectrometer. The environmental impact to the instrument is very little.
3) Because of nitrogen is the elements which are easy transfer, nitrogen vertical distribution is common on many vegetation. Considering the retrieval limitation relying only on solar illumination, the multispectral full-wave lidar will be studied for the retrieval of nitrogen concentration vertical distribution. Firstly, solid scatterer model according to the back scattering feature of vegetaion objects was established. Secondly, the multi-channel LiDAR waveform was simulated with the consideration of single scatter of plant radiative transfer model. The variation of LAI and chlorophyll along plant height was investigated for maize and three typical scenarios were assumed. The multi-channel return full waveform LiDAR simulation was carried out based on reflectance calculated by radiative transfer model. The simulation at specific wavelength (531nm,550nm,670nm,780nm,1064nm,1550nm) showed that the multi-channel LiDAR waveform could reflect the variation of plant physiological composition and facilitate the inversion algorithm design. At last, the multi-channel LiDAR prototype was developed. The light source used is a supercontinuum laser source with an average output power of100mW. A telescope collected the scattered laser pulse from the target. According to the different of the sensor and spectrophotometric method, we proposed two schemes. In the first scheme, the focal point of the telescope is imaged onto two avalanche photodiode sensors. And we can get two-channel LiDAR. In the second scheme, the focal point of the telescope is transformed to a grating, and the splitled light was measured by the PMT line sensor. A32-channel LiDAR was achieved. Expeiment shows that the firt scheme can obtain better waveform. Using this instrument,3D clouds with spectral information will be got.
引文
[1]余叔文,植物学,汤章城,等.植物生理与分子生物学.北京：科学出版社,1998.
[2]Pm V, Rw H. Nitrogen limitation on land and in the sea:how can it occur?. Biogeochemistry,1991, 13:87-115.
[3]Jj E, Mes B, Ee C. Global analysis of nitrogen and phosphorus limitation of primary producers in freshwater, marine and terrestrial ecosystems. Ecology Letters,2007,10:1135-1142.
[4]S G. N:P ratios in terrestrial plants:variation and functional significance. New Phytologist,2004, 164:243-266.
[5]J. G. Towards models of resource allocation by plants. San Diego, CA, USA:Academic Press,1997.
[6]C F, Ha M. On the Economy of Plant form and Function. Cambridge, UK.:Cambridge University Press,1986.
[7]Sterner R W, Elser J J. Ecological stoichiometry:the biology of elements from molecules to the biosphere. Princeton University Press,2002.
[8]Sj M, Rs S, Mr F, et al. Recent advances in ecological stoichiometry:insights for population and community ecology. Oikos,2005,2005(109):29-39.
[9]Jc Y, Dd B, A G, et al. Microbial soil respiration and its dependency on carbon inputs, soil temperature and moisture.. Global Change Biology,2007,13:1-8.
[10]Chapin Iii F S, Matson P P A. Principles of terrestrial ecosystem ecology. Springer,2011.
[11]牛铮,王长耀.碳循环遥感基础与应用.北京：科学出版社,2008.
[12]王军邦,牛铮,胡秉民,等.定量遥感在生态学研究中的基础应用.生态学杂志,2004,23(2)：152-157.
[13]张卫峰,马林,黄高强,等.中国氮肥发展、贡献和挑战.中国农业科学,2013,(15)：3161-3171.
[14]龚子同,黄标,欧阳洮.我国土壤地球化学及其在农业生产中的意义.地理科学,1998,18(1)：1-9.
[15]李志博,王起超,陈静.农业生态系统的氮素循环研究进展.土壤与环境,2002,11(4)：417-421.
[16]李家康,林葆,梁国庆,等.对我国化肥使用前景的剖析.植物营养与肥料学报,2001,7(1)：1.
[17]庄亚辉,曹美秋,王效科,等.中国地区生物质燃烧释放的含碳痕量气体.环境科学学报,1998,(04)：3-9.
[18]庄亚辉,李长生,高拯民.复合生态系统元素循环.北京：中国环境科学出版社,1995.
[19]李庆逵.我国土壤科学发展的回顾与展望.土壤科学进展,1989,17(4)：1-16.
[20]N G J. The global nitrogen cycle:change and consequences. Environmental Pollutiong,1998,102: 153.
[21]张福锁,王激清,张卫峰,等.中国主要粮食作物肥料利用率现状与提高途径,土壤学报,2008,45(5)：915-924.
[22]贾良良,陈新平,张福锁.作物氮营养诊断的无损测试技术.世界农业,2001,(6)：36-37.
[23]志宏,张云贵,刘宏斌.叶绿素仪在夏玉米氮营养诊断中的应用.植物营养与肥料学报,2005,11(6)：764-768.
[24]于渤,孙明,韩书庆,等.小麦叶绿素,氮素,水分一体化测定仪的开发与测试.光谱学与光谱分析,2011,31(8)：2294.
[25]于渤.小麦养分水分一体化测定仪开发：[硕士学位论文].中国农业大学,2010.
[26]武维华.植物生理学.北京：科学出版社,2005.
[27]李修华.基于光谱学和遥感技术的作物生长实时检测研究：[博士学位论文].北京：中国农业大学,2012.
[28]朱兆良.农田中氮肥的损失与对策.土壤与环境,2000,9(1)：1-6.
[29]孙志梅,武志杰,陈利军,等.农业生产中的氮肥施用现状及其环境效应研究进展.土壤通报,2006,(04)：782-786.
[30]串丽敏,赵同科,安志装,等.土壤硝态氮淋溶及氮素利用研究进展.中国农学通报,2010,(11)：200-205.
[31]刘晓晨,孙占祥.地下水硝态氮污染现状及研究进展.辽宁农业科学,2008,(05)：41-45.
[32]吕殿青,同延安,孙本华,等.氮肥施用对环境污染影响的研究.植物营养与肥料学报,1998,(01)：8-15.
[33]A W C, D A J, L P D. An evaluation of imaging spectrometry for estimating forest canopy chemistry. International Journal of Remote Sensing,1989,10:1293-1316.
[34]Wenjiang H, Jihua W, Zhijie W, et al. Inversion of foliar biochemical parameters at various physiological stages and grain quality indicators of winter wheat withcanopy reflectance. International Journal of Remote Sensing,2004,25(12):2409-2419.
[35]Thomas J, Oerther G. Estimating nitrogen content of sweet pepper leaves by reflectance measurements. Agronomy Journal,1972,64(1):11-13.
[36]薛利红,曹卫星,罗卫红,等.小麦叶片氮素状况与光谱特性的相关性研究.植物生态学报,2004,28(2)：172-177.
[37]张瑶,郑立华,李民赞,等.苹果叶片氮素含量快速检测模型.农业机械学报,2012,43(增刊)：300-304.
[38]张雪红,刘绍民,何蓓蓓.基于包络线消除法的油菜氮素营养高光谱评价.农业工程学报,2008,24(10)：151-155.
[39]徐新刚,赵春江,王纪华,等.新型光谱曲线特征参数与水稻叶绿素含量间的关系研究.光谱学与光谱分析,2011,31(1)：188.
[40]易秋香,黄敬峰,王秀珍,等.玉米全氮含量高光谱遥感估算模型研究.农业工程学报,2006,22(9)：138-143.
[41]Horler D, Dockray M, Barber J. The red edge of plant leaf reflectance. International Journal of Remote Sensing,1983,4(2):273-288.
[42]王秀珍,王人潮,李云梅,等.不同氮素营养水平的水稻冠层光谱红边参数及其应用研究.浙江大学学报：农业与生命科学版,2001,27(3)：301-306.
[43]吴连喜,胡军杰,游党呈,等.高光谱在水稻含氮量测定中的应用研究.安徽农业科学,2013,(2)：471-472.
[44]Sims D A, Gamon J A. Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages. Remote sensing of environment,2002, 81(2):337-354.
[45]Zhu Y, Yao X, Tian Y, et al. Analysis of common canopy vegetation indices for indicating leaf nitrogen accumulations in wheat and rice. International Journal of Applied Earth Observation and Geoinformation,2008,10(1):1-10.
[46]李佛琳.基于光谱的烟草生长于品质监测研究：[博士学位论文].南京：南京农业大学,2006.
[47]熊鹰,刘波,岳跃民.基于ASD和FISS的植被叶片氮素含量反演研究.生态环境学报,2013,22(4)：582-587.
[48]Miao Y, Mulla D J, Randall G W, et al. Combining chlorophyll meter readings and high spatial resolution remote sensing images for in-season site-specific nitrogen management of corn. Precision agriculture,2009,10(1):45-62.
[49]浦瑞良,宫鹏.森林生物化学与CAS1高光谱分辨率遥感数据的相关分析.遥感学报,1997,1(2)：115-123.
[50]郭建华,王秀,孟志军,等.主动遥感光谱仪Greenseeker与SPAD对玉米氮素营养诊断的研究.植物营养与肥料学报,2008,14(1)：43-47.
[51]胡昊,白由路,杨俐苹,等.基于SPAD-502与GreenSeeker的冬小麦.中国生态农业学报,2010,18(4)：748-752.
[52]L tscher M, Stroh K, Schnyder H. Vertical leaf nitrogen distribution in relation to nitrogen status in grassland plants. Annals of Botany,2003,92(5):679-688.
[53]Hirose T, Werger M, Pons T, et al. Canopy structure and leaf nitrogen distribution in a stand of Lysimachia vulgaris L. as influenced by stand density. Oecologia,1988,77(2):145-150.
[54]Eklundh L, Harrie L, Kuusk A. Investigating relationships between Landsat ETM+ sensor data and leaf area index in a boreal conifer forest. Remote Sensing of Environment,2001,78(3):239-251.
[55]A K, T N. A directional multispectral forest reflectance model. Remote Sensing of Environment, 2000,72(2):244-252.
[56]A K, T N, M P, et al. Validation of the forest radiative transfer model FRT. Remote Sensing of Environment,2008,112(1):51-58.
[57]王纪华,王之杰,黄文江,等.冬小麦冠层氮素垂直分布及光谱相应.遥感学报,2004,8(7)：309-316.
[58]X L, H S A, E W C. A hybrid geometric optical-radiative transfer approach for modeling albedo and directional reflectance of discontinuous canopies. IEEE Transactions on Geoscience and Remote Sensing,1995,33(2):466-480.
[59]赵春江,黄文江,王纪华,等.用多角度光谱信息反演冬小麦氮素含量垂直分布.农业工程学报,2006,22(6)：104-109.
[60]谢东辉,朱启疆,王锦地,等.基于真实三维结构的玉米冠层生化参数垂直分布的定量化分析.北京师范大学学报,2007,43(6)：337-342.
[61]Coren F, Sterzai P. Radiometric correction in laser scanning. International Journal of Remote Sensing,2006,27(15):3097-3104.
[62]Wagner W, Ullrich A, Ducic V, et al. Gaussian decomposition and calibration of a novel small-footprint full-waveform digitising airborne laser scanner. ISPRS Journal of Photogrammetry and Remote Sensing,2006,60(2):100-112.
[63]刘清旺,李增元,陈尔学,等.森林冠层探测激光雷达的波形特征分析.中国科学：地球科学,2012,41(11)：1670-1678.
[64]G S, J R K. Modeling lidar returns from forest canopies. IEEE Transactions on Geoscience and Remote Sensing,2000,38(6):2617-2626.
[65]W N-M, B J D L, R D. Modeling lidar waveforms in heterogeneous and discrete canopies. IEEE Transactions on Geoscience and Remote Sensing,2001,39(9):1943-1958.
[66]Y K S, V S N, Y K, et al. Modeling lidar waveforms with time-dependent stochastic radiative transfer theory for remote estimations of forest structure. Journal of Geophysical Research,2003,108.
[67]孙国清,KJR,张钟军.利用激光雷达和多角度频谱成像仪数据估测森林垂直参数.遥感学报,2006,10(4).
[68]周梦维,柳钦火,刘强,等.机载激光雷达的作物叶面积指数定量反演.农业工程学报,2011,27(4).
[69]史硕,龚威,祝波,等.基于Lab VIEW实现的多光谱激光雷达数据采集与处理系统.光学与光电技术,2012,10(12)：39-42.
[70]V T, A F D, H M J, et al. Spatial modelling of the fraction of photosynthetically active radiation absorbed by a boreal mixedwood forest using a lidar-hyperspectral approach. Agricultural and Forest Meteorology,2006,140(14):287-307.
[71]T M J, R S D, F G N. Mapping sagebrush distribution using fusion of hyperspectral and lidar classifications. Photogrammetric engineering and remote sensing,2006,72(1):47.
[72]P H, R D, W W, et al. Mapping forest structure for wildlife habitat analysis using multi-sensor (LiDAR, SAR/InSAR, ETM+, Quickbird) synergy.102,2006,12(63-73).
[73]王成,程峰.基于ICESat GLAS和MODIS数据的植被平均高度反演——以东北三省为例.2010.
[74]覃驭楚.面向城市植被参数提取的激光雷达与光学影像融合方法研究：[博士学位论文].中国科学院遥感应用研究所,2010.
[75]TH,JS, SK, et al. Full waveform hyperspectral LiDAR for terrestrial laser scanning. Optics Express,2012,20(7).
[76]Puttonen E, Suomalainen J, Hakala T, et al. Tree species classification from fused active hyperspectral reflectance and LIDAR measurements. Forest Ecology and Management,2010,260(10): 1843-1852.
[77]Kaasalainen S, Suomalainen J, Hakala T, et al. Active hyperspectral LIDAR methods for object classification[C]. Hyperspectral Image and Signal Processing:Evolution in Remote Sensing (WHISPERS),2010 2nd Workshop on,2010:1-4.
[78]Stone M, Solie J, Whitney R, et al. Sensors for detection of nitrogen in winter wheat. Society of Automotive Engineers,1996.
[79]Link A, Panitzki M, Reusch S, et al. Hydro N-Sensor:tractor-mounted remote sensing for variable nitrogen fertilization[C]. Proceedings of the 6th International Conference on Precision Agriculture and Other Precision Resources Management, Minneapolis, MN, USA,14-17 July,2002.,2003:1012-1017.
[80]Wei G, Shalei S, Bo Z, et al. Multi-wavelength canopy LiDAR for remote sensing of vegetation: Design and system performance. ISPRS Journal of Photogrammetry and Remote Sensing,2012,69:1-9.
[81]赵春江,刘良云,周汉昌,等.归一化差异植被指数仪的研制与应用.光学技术,2004,(03)：324-326+329.
[82]王秀,赵春江,周汉昌,等.冬小麦生长便携式NDVI测量仪的研制与试验.农业工程学报,2004,(04)：95-98.
[83]张喜杰,李民赞,崔笛,等.温室作物长势的光谱学诊断方法研究与仪器开发.光谱学与光谱分析,2006,(05)：887-890.
[84]李修华,李民赞,崔笛.基于光谱学原理的无损式作物冠层分析仪.农业机械学报,2009,(S1)：252-255+227.
[85]李修华,李民赞,崔笛,等.基于双波段作物长势分析仪的东北水稻长势监测.农业工程学报,2011,(08)：206-210.
[86]李修华,张锋,李民赞,等.四波段作物冠层分析仪设计.农业机械学报,2011,(11)：169-173.
[87]杨建宁,张井超,朱艳,等.便携式作物生长监测诊断仪性能试验.农业机械学报,2013,(04)：208-212+201.
[88]倪军,姚霞,田永超,等.便携式作物生长监测诊断仪的设计与试验.农业工程学报,2013,(06)：150-156.
[89]倪军,王婷婷,姚霞,等.作物生长信息获取多光谱传感器设计与试验.农业机械学报,2013,(05)：207-212.
[90]邢艳秋,黄超,陈世宏.SPAD叶绿素仪在评价树木叶片光环境和健康水平上的应用初探.森林工程,2011,27(1)：1-4.
[91]杨玮.基于光谱分析的作物长势检测及变量施肥技术研究：[博士学位论文].北京：中国农业大学,2008.
[92]Rall J A, Knox R G. Spectral ratio biospheric lidar. Geoscience and Remote Sensing Symposium, 2004. IGARSS'04. Proceedings.2004 IEEE International,2004:1951-1954.
[93]Chen Y, Raikkonen E, Kaasalainen S, et al. Two-channel hyperspectral LiDAR with a supercontinuum laser source. Sensors,2010,10(7):7057-7066.
[94]Dabney P, Harding D, Abshire J, et al. The Slope Imaging Multi-polarization Photon-counting Lidar:development and performance results. Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International,2010:653-656.
[95]Johnson B, Joseph R, Nischan M L, et al. Compact active hyperspectral imaging system for the detection of concealed targets. AeroSense'99,1999:144-153.
[96]Nischan M, Joseph R, Libby J, et al. Active spectral imaging,2003.
[97]Tan S, Narayanan R M. Design and performance of a multiwavelength airborne polarimetric lidar for vegetation remote sensing. Applied optics,2004,43(11):2360-2368.
[98]Pfennigbauer M, Ullrich A. Multi-wavelength airborne laser scanning. Proceedings of the International Lidar Mapping Forum, ILMF, New Orleans,2011.
[99]Guenther G C, Larocque P E, Lillycrop W J. Multiple surface channels in Scanning Hydrographic Operational Airborne Lidar Survey (SHOALS) airborne lidar. Ocean Optics Ⅻ,1994:422-430.
[100]Winker D M, Pelon J, Mccormick M P. The CALIPSO mission:Spaceborne lidar for observation of aerosols and clouds. Proc. Spie,2003:11.
[101]Abshire J B, Sun X, Riris H, et al. Geoscience Laser Altimeter System (GLAS) on the ICESat Mission:On-orbit measurement performance. Geophysical Research Letters,2005,32(21).
[102]Hakala T, Suomalainen J, Kaasalainen S, et al. Full waveform hyperspectral LiDAR for terrestrial laser scanning. Optics Express,2012,20(7):7119-7127.
[103]Ramirez D M, Buller G S, Mccarthy A, et al. Developing Hyperspectral LiDAR for Structural and Biochemical Analysis of Forest Data.
[104]叶晓青,邹勇,余志虹,等.烤烟冠层光谱参数与氮素垂直分布相关性研究.农业机械学报,2013,(05)：219-225.
[105]王建宇,洪光烈.激光主动遥感技术及其应用.激光与红外,2006,36(9)：742.
[106]庞勇,李增元,陈尔学,等.激光雷达技术及其在林业上的应用.林业科学,2005,41(3)：8.
[107]李民赞.光谱分析技术及其应用.北京：科学出版社,2006.
[108]姚霞.小麦冠层和单叶氮素营养指标的高光谱仪监测研究：[博士学位论文].南京：南京农业大学,2009.
[109]Huete A R. A soil-adjusted vegetation index (SAVI). Remote sensing of environment,1988,25(3): 295-309,
[110]Rondeaux G, Steven M, Baret F. Optimization of soil-adjusted vegetation indices. Remote Sensing of Environment,1996,55(2):95-107.
[111]Gitelson A A, Merzlyak M N. Remote estimation of chlorophyll content in higher plant leaves. International Journal of Remote Sensing,1997,18(12):2691-2697.
[112]杨洋,王晓欧,陈历学,等.106μm激光雷达目标散射特性的实验研究.红外与激光工程,2000,29(3)：52-55.
[113]戴永江.激光雷达原理.北京：国防工业出版社,2002.
[114]郭建华,赵春江,王秀,等.作物氮素营养诊断方法的研究现状及进展.中国土壤与肥料,2008,4：10-14.
[115]田永超,朱艳,姚霞,等.基于光谱信息的作物氮素营养无损监测技术.生态学杂志,2007,26(9)：1454-1463.
[116]巨晓棠,张福锁.关于氮肥利用率的思考.生态环境,2003,(02)：192-197.
[117]赵天奇.面向变量施肥应用的OSAVI测量仪的设计：[硕士学位论文].北京化工大学,2009.
[118]梁红霞,赵春江,黄文江,等.利用光谱指数进行冬小麦变量施肥的可行性及其效益评价.遥感技术与应用,2005,(05)：13-17.
[119]蒋阿宁,黄文江,赵春江,等.基于光谱指数的冬小麦变量施肥效应研究.中国农业科学,2007,(09)：1907-1913.
[120]蒋阿宁,黄文江,赵春江,等.基于光谱指数的变量施肥对冬小麦产量构成的影响及其效益分析.麦类作物学报,2007,(01)：122-126.
[121]Raun W, Solie J, Stone M, et al. Optical Sensor-Based Algorithm for Crop Nitrogen Fertilization. Communications in Soil Science and Plant Analysis,2005,36(19-20):2759-2781.
[122]Zhang X, Li M, Zhang Y. A new multispectral detector of crop growth condition based on fiber optics[C]. Optics & Photonics 2005,2005:58810K-58810K-9.
[123]王金刚,宫霄霖,苏淇.JTAG调试技术及其ARM仿真器应用.电子测量技术,2004,(4)：24-25.
[124]洪利,章扬,李世宝.MSP430单片机原理与应用实例详解.北京：北京航空航天大学出版社,2010.
[125]郑文刚,孙刚,申长军,等.可见-近红外作物氮素光电测量仪开发.农业工程学报,2010,(003)：178-182.
[126]翟霄翔,郝久玉,郑军.电阻式触摸屏在嵌入式系统中的应用.电子测量技术,2006,29(2)：36-37.
[127]李萍,单葆悦,刘晓东,等.USB芯片CH376在智能仪器仪表中的应用.计量与测试技术,2011,38(002)：9-10.
[128]王永虹,徐炜,郝立平.STM32系列ARM Cortex-M3微控制器原理与实践.北京航空航天大学出版社,2008.
[129]马利群,李爱农.激光雷达在森林垂直结构参数估算中的应用.世界林业研究,2011,24(1)：42-45.
[130]何祺胜,陈尔学,曹春香,等.基于LIDAR数据的森林参数反演方法研究.地球科学进展,2009,24(7)：748-755.
[131]Popescu S C, Wynne R H, Nelson R F. Estimating plot-level tree heights with lidar:local filtering with a canopy-height based variable window size. Computers and Electronics in Agriculture,2002, 37(1):71-95.
[132]Andersen H-E, Mcgaughey R J, Reutebuch S E. Estimating forest canopy fuel parameters using LIDAR data. Remote sensing of Environment,2005,94(4):441-449.
[133]Jelalian A V. Laser radar systems. EASCON'80; Electronics and Aerospace Systems Conference, 1980:546-554.
[134]Wagner W, Ullrich A, Melzer T, et al. From single-pulse to full-waveform airborne laser scanners: potential and practical challenges. International Archives of Photogrammetry and Remote Sensing, 2004,35(B3):201-206.
[135]Vandapel N, Amidi O, Miller J R. Toward laser pulse waveform analysis for scene interpretation. Robotics and Automation,2004. Proceedings. ICRA'04.2004 IEEE International Conference on,2004: 950-955.
[136]Steinvall O, Larsson H, Gustafsson F, et al. Performance of 3 D laser radar through vegetation and camouflage. Proceedings of SPIE,2005:129-142.
[137]Kuusk A. A two-layer canopy reflectance model. Journal of Quantitative Spectroscopy and Radiative Transfer,2001,71(1):1-9.
[138]Jacquemoud S, Baret F. PROSPECT:A model of leaf optical properties spectra. Remote Sensing of Environment,1990,34(2):75-91.
[139]Vermote E F, Tanre D, Deuze J L, et al. Second Simulation of the Satellite Signal in the Solar Spectrum,6S:An overview. Ieee Transactions on Geoscience and Remote Sensing,1997,35(3):675-686.
[140]Sun G, Ranson K J. Modeling Iidar returns from forest canopies. Geoscience and Remote Sensing, IEEE Transactions on,2000,38(6):2617-2626.
[141]Boedhram N, Arkebauer T J, Batchelor W D. Season-long characterization of vertical distribution of leaf area in corn. Agronomy Journal,2001,93(6):1235-1242.
[142]Yang J Z, Alley M. A mechanistic model for describing corn plant leaf area distribution. Agronomy Journal,2005,97(1):41-48.
[143]Veronica Ciganda A G,* and James Schepers. Vertical Profile and Temporal Variation of Chlorophyll in Maize Canopy:Quantitative "Crop Vigor" Indicator by Means of Refl ectance-Based Techniques,2008.
[144]Gamon J, Serrano L, Surfus J. The photochemical reflectance index:an optical indicator of photosynthetic radiation use efficiency across species, functional types, and nutrient levels. Oecologia, 1997,112(4):492-501.
[145]Tucker C J. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment,1979,8(2):127-150.
[146]许洪,王向军.多光谱,超光谱成像技术在军事上的应用.红外与激光工程,2007,36(1)：13-17.
[147]郑玉权,禹秉熙.成像光谱仪分光技术概览.遥感学报,2002,(01)：75-80.
[148]苏丽娟.成像光谱仪分光技术研究：[博士学位论文].中国科学院研究生院(西安光学精密机械研究所),2006.
[149]杨怀栋,陈科新,黄星月,等.常规光谱仪器分光系统的比较.光谱学与光谱分析,2009,29(6)：1707-1712.
[150]高雅允,高岳.光电检测技术.北京：国防工业出版社,1995.
[151]张光斌,林世鸣,渠波,等.激光雷达中雪崩光电二极管的智能应用,光电子.激光2000,11(5)：465-468.
[152]江华,周媛媛.光电倍增管的结构与性能研究.舰船电子工程,2009,29(1)：193-196.
[153]张鹏飞,周金运.单光子探测器及其发展.传感器世界,2003,10(9)：6-10.
[154]梁创,廖静,梁冰,等.硅雪崩光电二极管单光子探测器.光子学报,2000,29(12)：1142-1147.
[155]宋登元,王小平.APD, PMT及其混合型高灵敏度光电探测器.半导体技术,2000,25(3)：5-8.
[156]王忠立,刘佳音,贾云得.基于CCD与CMOS的图像传感技术.光学技术,2003,29(3)：361-364.
[2]Pm V, Rw H. Nitrogen limitation on land and in the sea:how can it occur?. Biogeochemistry,1991, 13:87-115.
[3]Jj E, Mes B, Ee C. Global analysis of nitrogen and phosphorus limitation of primary producers in freshwater, marine and terrestrial ecosystems. Ecology Letters,2007,10:1135-1142.
[4]S G. N:P ratios in terrestrial plants:variation and functional significance. New Phytologist,2004, 164:243-266.
[5]J. G. Towards models of resource allocation by plants. San Diego, CA, USA:Academic Press,1997.
[6]C F, Ha M. On the Economy of Plant form and Function. Cambridge, UK.:Cambridge University Press,1986.
[7]Sterner R W, Elser J J. Ecological stoichiometry:the biology of elements from molecules to the biosphere. Princeton University Press,2002.
[8]Sj M, Rs S, Mr F, et al. Recent advances in ecological stoichiometry:insights for population and community ecology. Oikos,2005,2005(109):29-39.
[9]Jc Y, Dd B, A G, et al. Microbial soil respiration and its dependency on carbon inputs, soil temperature and moisture.. Global Change Biology,2007,13:1-8.
[10]Chapin Iii F S, Matson P P A. Principles of terrestrial ecosystem ecology. Springer,2011.
[11]牛铮,王长耀.碳循环遥感基础与应用.北京：科学出版社,2008.
[12]王军邦,牛铮,胡秉民,等.定量遥感在生态学研究中的基础应用.生态学杂志,2004,23(2)：152-157.
[13]张卫峰,马林,黄高强,等.中国氮肥发展、贡献和挑战.中国农业科学,2013,(15)：3161-3171.
[14]龚子同,黄标,欧阳洮.我国土壤地球化学及其在农业生产中的意义.地理科学,1998,18(1)：1-9.
[15]李志博,王起超,陈静.农业生态系统的氮素循环研究进展.土壤与环境,2002,11(4)：417-421.
[16]李家康,林葆,梁国庆,等.对我国化肥使用前景的剖析.植物营养与肥料学报,2001,7(1)：1.
[17]庄亚辉,曹美秋,王效科,等.中国地区生物质燃烧释放的含碳痕量气体.环境科学学报,1998,(04)：3-9.
[18]庄亚辉,李长生,高拯民.复合生态系统元素循环.北京：中国环境科学出版社,1995.
[19]李庆逵.我国土壤科学发展的回顾与展望.土壤科学进展,1989,17(4)：1-16.
[20]N G J. The global nitrogen cycle:change and consequences. Environmental Pollutiong,1998,102: 153.
[21]张福锁,王激清,张卫峰,等.中国主要粮食作物肥料利用率现状与提高途径,土壤学报,2008,45(5)：915-924.
[22]贾良良,陈新平,张福锁.作物氮营养诊断的无损测试技术.世界农业,2001,(6)：36-37.
[23]志宏,张云贵,刘宏斌.叶绿素仪在夏玉米氮营养诊断中的应用.植物营养与肥料学报,2005,11(6)：764-768.
[24]于渤,孙明,韩书庆,等.小麦叶绿素,氮素,水分一体化测定仪的开发与测试.光谱学与光谱分析,2011,31(8)：2294.
[25]于渤.小麦养分水分一体化测定仪开发：[硕士学位论文].中国农业大学,2010.
[26]武维华.植物生理学.北京：科学出版社,2005.
[27]李修华.基于光谱学和遥感技术的作物生长实时检测研究：[博士学位论文].北京：中国农业大学,2012.
[28]朱兆良.农田中氮肥的损失与对策.土壤与环境,2000,9(1)：1-6.
[29]孙志梅,武志杰,陈利军,等.农业生产中的氮肥施用现状及其环境效应研究进展.土壤通报,2006,(04)：782-786.
[30]串丽敏,赵同科,安志装,等.土壤硝态氮淋溶及氮素利用研究进展.中国农学通报,2010,(11)：200-205.
[31]刘晓晨,孙占祥.地下水硝态氮污染现状及研究进展.辽宁农业科学,2008,(05)：41-45.
[32]吕殿青,同延安,孙本华,等.氮肥施用对环境污染影响的研究.植物营养与肥料学报,1998,(01)：8-15.
[33]A W C, D A J, L P D. An evaluation of imaging spectrometry for estimating forest canopy chemistry. International Journal of Remote Sensing,1989,10:1293-1316.
[34]Wenjiang H, Jihua W, Zhijie W, et al. Inversion of foliar biochemical parameters at various physiological stages and grain quality indicators of winter wheat withcanopy reflectance. International Journal of Remote Sensing,2004,25(12):2409-2419.
[35]Thomas J, Oerther G. Estimating nitrogen content of sweet pepper leaves by reflectance measurements. Agronomy Journal,1972,64(1):11-13.
[36]薛利红,曹卫星,罗卫红,等.小麦叶片氮素状况与光谱特性的相关性研究.植物生态学报,2004,28(2)：172-177.
[37]张瑶,郑立华,李民赞,等.苹果叶片氮素含量快速检测模型.农业机械学报,2012,43(增刊)：300-304.
[38]张雪红,刘绍民,何蓓蓓.基于包络线消除法的油菜氮素营养高光谱评价.农业工程学报,2008,24(10)：151-155.
[39]徐新刚,赵春江,王纪华,等.新型光谱曲线特征参数与水稻叶绿素含量间的关系研究.光谱学与光谱分析,2011,31(1)：188.
[40]易秋香,黄敬峰,王秀珍,等.玉米全氮含量高光谱遥感估算模型研究.农业工程学报,2006,22(9)：138-143.
[41]Horler D, Dockray M, Barber J. The red edge of plant leaf reflectance. International Journal of Remote Sensing,1983,4(2):273-288.
[42]王秀珍,王人潮,李云梅,等.不同氮素营养水平的水稻冠层光谱红边参数及其应用研究.浙江大学学报：农业与生命科学版,2001,27(3)：301-306.
[43]吴连喜,胡军杰,游党呈,等.高光谱在水稻含氮量测定中的应用研究.安徽农业科学,2013,(2)：471-472.
[44]Sims D A, Gamon J A. Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages. Remote sensing of environment,2002, 81(2):337-354.
[45]Zhu Y, Yao X, Tian Y, et al. Analysis of common canopy vegetation indices for indicating leaf nitrogen accumulations in wheat and rice. International Journal of Applied Earth Observation and Geoinformation,2008,10(1):1-10.
[46]李佛琳.基于光谱的烟草生长于品质监测研究：[博士学位论文].南京：南京农业大学,2006.
[47]熊鹰,刘波,岳跃民.基于ASD和FISS的植被叶片氮素含量反演研究.生态环境学报,2013,22(4)：582-587.
[48]Miao Y, Mulla D J, Randall G W, et al. Combining chlorophyll meter readings and high spatial resolution remote sensing images for in-season site-specific nitrogen management of corn. Precision agriculture,2009,10(1):45-62.
[49]浦瑞良,宫鹏.森林生物化学与CAS1高光谱分辨率遥感数据的相关分析.遥感学报,1997,1(2)：115-123.
[50]郭建华,王秀,孟志军,等.主动遥感光谱仪Greenseeker与SPAD对玉米氮素营养诊断的研究.植物营养与肥料学报,2008,14(1)：43-47.
[51]胡昊,白由路,杨俐苹,等.基于SPAD-502与GreenSeeker的冬小麦.中国生态农业学报,2010,18(4)：748-752.
[52]L tscher M, Stroh K, Schnyder H. Vertical leaf nitrogen distribution in relation to nitrogen status in grassland plants. Annals of Botany,2003,92(5):679-688.
[53]Hirose T, Werger M, Pons T, et al. Canopy structure and leaf nitrogen distribution in a stand of Lysimachia vulgaris L. as influenced by stand density. Oecologia,1988,77(2):145-150.
[54]Eklundh L, Harrie L, Kuusk A. Investigating relationships between Landsat ETM+ sensor data and leaf area index in a boreal conifer forest. Remote Sensing of Environment,2001,78(3):239-251.
[55]A K, T N. A directional multispectral forest reflectance model. Remote Sensing of Environment, 2000,72(2):244-252.
[56]A K, T N, M P, et al. Validation of the forest radiative transfer model FRT. Remote Sensing of Environment,2008,112(1):51-58.
[57]王纪华,王之杰,黄文江,等.冬小麦冠层氮素垂直分布及光谱相应.遥感学报,2004,8(7)：309-316.
[58]X L, H S A, E W C. A hybrid geometric optical-radiative transfer approach for modeling albedo and directional reflectance of discontinuous canopies. IEEE Transactions on Geoscience and Remote Sensing,1995,33(2):466-480.
[59]赵春江,黄文江,王纪华,等.用多角度光谱信息反演冬小麦氮素含量垂直分布.农业工程学报,2006,22(6)：104-109.
[60]谢东辉,朱启疆,王锦地,等.基于真实三维结构的玉米冠层生化参数垂直分布的定量化分析.北京师范大学学报,2007,43(6)：337-342.
[61]Coren F, Sterzai P. Radiometric correction in laser scanning. International Journal of Remote Sensing,2006,27(15):3097-3104.
[62]Wagner W, Ullrich A, Ducic V, et al. Gaussian decomposition and calibration of a novel small-footprint full-waveform digitising airborne laser scanner. ISPRS Journal of Photogrammetry and Remote Sensing,2006,60(2):100-112.
[63]刘清旺,李增元,陈尔学,等.森林冠层探测激光雷达的波形特征分析.中国科学：地球科学,2012,41(11)：1670-1678.
[64]G S, J R K. Modeling lidar returns from forest canopies. IEEE Transactions on Geoscience and Remote Sensing,2000,38(6):2617-2626.
[65]W N-M, B J D L, R D. Modeling lidar waveforms in heterogeneous and discrete canopies. IEEE Transactions on Geoscience and Remote Sensing,2001,39(9):1943-1958.
[66]Y K S, V S N, Y K, et al. Modeling lidar waveforms with time-dependent stochastic radiative transfer theory for remote estimations of forest structure. Journal of Geophysical Research,2003,108.
[67]孙国清,KJR,张钟军.利用激光雷达和多角度频谱成像仪数据估测森林垂直参数.遥感学报,2006,10(4).
[68]周梦维,柳钦火,刘强,等.机载激光雷达的作物叶面积指数定量反演.农业工程学报,2011,27(4).
[69]史硕,龚威,祝波,等.基于Lab VIEW实现的多光谱激光雷达数据采集与处理系统.光学与光电技术,2012,10(12)：39-42.
[70]V T, A F D, H M J, et al. Spatial modelling of the fraction of photosynthetically active radiation absorbed by a boreal mixedwood forest using a lidar-hyperspectral approach. Agricultural and Forest Meteorology,2006,140(14):287-307.
[71]T M J, R S D, F G N. Mapping sagebrush distribution using fusion of hyperspectral and lidar classifications. Photogrammetric engineering and remote sensing,2006,72(1):47.
[72]P H, R D, W W, et al. Mapping forest structure for wildlife habitat analysis using multi-sensor (LiDAR, SAR/InSAR, ETM+, Quickbird) synergy.102,2006,12(63-73).
[73]王成,程峰.基于ICESat GLAS和MODIS数据的植被平均高度反演——以东北三省为例.2010.
[74]覃驭楚.面向城市植被参数提取的激光雷达与光学影像融合方法研究：[博士学位论文].中国科学院遥感应用研究所,2010.
[75]TH,JS, SK, et al. Full waveform hyperspectral LiDAR for terrestrial laser scanning. Optics Express,2012,20(7).
[76]Puttonen E, Suomalainen J, Hakala T, et al. Tree species classification from fused active hyperspectral reflectance and LIDAR measurements. Forest Ecology and Management,2010,260(10): 1843-1852.
[77]Kaasalainen S, Suomalainen J, Hakala T, et al. Active hyperspectral LIDAR methods for object classification[C]. Hyperspectral Image and Signal Processing:Evolution in Remote Sensing (WHISPERS),2010 2nd Workshop on,2010:1-4.
[78]Stone M, Solie J, Whitney R, et al. Sensors for detection of nitrogen in winter wheat. Society of Automotive Engineers,1996.
[79]Link A, Panitzki M, Reusch S, et al. Hydro N-Sensor:tractor-mounted remote sensing for variable nitrogen fertilization[C]. Proceedings of the 6th International Conference on Precision Agriculture and Other Precision Resources Management, Minneapolis, MN, USA,14-17 July,2002.,2003:1012-1017.
[80]Wei G, Shalei S, Bo Z, et al. Multi-wavelength canopy LiDAR for remote sensing of vegetation: Design and system performance. ISPRS Journal of Photogrammetry and Remote Sensing,2012,69:1-9.
[81]赵春江,刘良云,周汉昌,等.归一化差异植被指数仪的研制与应用.光学技术,2004,(03)：324-326+329.
[82]王秀,赵春江,周汉昌,等.冬小麦生长便携式NDVI测量仪的研制与试验.农业工程学报,2004,(04)：95-98.
[83]张喜杰,李民赞,崔笛,等.温室作物长势的光谱学诊断方法研究与仪器开发.光谱学与光谱分析,2006,(05)：887-890.
[84]李修华,李民赞,崔笛.基于光谱学原理的无损式作物冠层分析仪.农业机械学报,2009,(S1)：252-255+227.
[85]李修华,李民赞,崔笛,等.基于双波段作物长势分析仪的东北水稻长势监测.农业工程学报,2011,(08)：206-210.
[86]李修华,张锋,李民赞,等.四波段作物冠层分析仪设计.农业机械学报,2011,(11)：169-173.
[87]杨建宁,张井超,朱艳,等.便携式作物生长监测诊断仪性能试验.农业机械学报,2013,(04)：208-212+201.
[88]倪军,姚霞,田永超,等.便携式作物生长监测诊断仪的设计与试验.农业工程学报,2013,(06)：150-156.
[89]倪军,王婷婷,姚霞,等.作物生长信息获取多光谱传感器设计与试验.农业机械学报,2013,(05)：207-212.
[90]邢艳秋,黄超,陈世宏.SPAD叶绿素仪在评价树木叶片光环境和健康水平上的应用初探.森林工程,2011,27(1)：1-4.
[91]杨玮.基于光谱分析的作物长势检测及变量施肥技术研究：[博士学位论文].北京：中国农业大学,2008.
[92]Rall J A, Knox R G. Spectral ratio biospheric lidar. Geoscience and Remote Sensing Symposium, 2004. IGARSS'04. Proceedings.2004 IEEE International,2004:1951-1954.
[93]Chen Y, Raikkonen E, Kaasalainen S, et al. Two-channel hyperspectral LiDAR with a supercontinuum laser source. Sensors,2010,10(7):7057-7066.
[94]Dabney P, Harding D, Abshire J, et al. The Slope Imaging Multi-polarization Photon-counting Lidar:development and performance results. Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International,2010:653-656.
[95]Johnson B, Joseph R, Nischan M L, et al. Compact active hyperspectral imaging system for the detection of concealed targets. AeroSense'99,1999:144-153.
[96]Nischan M, Joseph R, Libby J, et al. Active spectral imaging,2003.
[97]Tan S, Narayanan R M. Design and performance of a multiwavelength airborne polarimetric lidar for vegetation remote sensing. Applied optics,2004,43(11):2360-2368.
[98]Pfennigbauer M, Ullrich A. Multi-wavelength airborne laser scanning. Proceedings of the International Lidar Mapping Forum, ILMF, New Orleans,2011.
[99]Guenther G C, Larocque P E, Lillycrop W J. Multiple surface channels in Scanning Hydrographic Operational Airborne Lidar Survey (SHOALS) airborne lidar. Ocean Optics Ⅻ,1994:422-430.
[100]Winker D M, Pelon J, Mccormick M P. The CALIPSO mission:Spaceborne lidar for observation of aerosols and clouds. Proc. Spie,2003:11.
[101]Abshire J B, Sun X, Riris H, et al. Geoscience Laser Altimeter System (GLAS) on the ICESat Mission:On-orbit measurement performance. Geophysical Research Letters,2005,32(21).
[102]Hakala T, Suomalainen J, Kaasalainen S, et al. Full waveform hyperspectral LiDAR for terrestrial laser scanning. Optics Express,2012,20(7):7119-7127.
[103]Ramirez D M, Buller G S, Mccarthy A, et al. Developing Hyperspectral LiDAR for Structural and Biochemical Analysis of Forest Data.
[104]叶晓青,邹勇,余志虹,等.烤烟冠层光谱参数与氮素垂直分布相关性研究.农业机械学报,2013,(05)：219-225.
[105]王建宇,洪光烈.激光主动遥感技术及其应用.激光与红外,2006,36(9)：742.
[106]庞勇,李增元,陈尔学,等.激光雷达技术及其在林业上的应用.林业科学,2005,41(3)：8.
[107]李民赞.光谱分析技术及其应用.北京：科学出版社,2006.
[108]姚霞.小麦冠层和单叶氮素营养指标的高光谱仪监测研究：[博士学位论文].南京：南京农业大学,2009.
[109]Huete A R. A soil-adjusted vegetation index (SAVI). Remote sensing of environment,1988,25(3): 295-309,
[110]Rondeaux G, Steven M, Baret F. Optimization of soil-adjusted vegetation indices. Remote Sensing of Environment,1996,55(2):95-107.
[111]Gitelson A A, Merzlyak M N. Remote estimation of chlorophyll content in higher plant leaves. International Journal of Remote Sensing,1997,18(12):2691-2697.
[112]杨洋,王晓欧,陈历学,等.106μm激光雷达目标散射特性的实验研究.红外与激光工程,2000,29(3)：52-55.
[113]戴永江.激光雷达原理.北京：国防工业出版社,2002.
[114]郭建华,赵春江,王秀,等.作物氮素营养诊断方法的研究现状及进展.中国土壤与肥料,2008,4：10-14.
[115]田永超,朱艳,姚霞,等.基于光谱信息的作物氮素营养无损监测技术.生态学杂志,2007,26(9)：1454-1463.
[116]巨晓棠,张福锁.关于氮肥利用率的思考.生态环境,2003,(02)：192-197.
[117]赵天奇.面向变量施肥应用的OSAVI测量仪的设计：[硕士学位论文].北京化工大学,2009.
[118]梁红霞,赵春江,黄文江,等.利用光谱指数进行冬小麦变量施肥的可行性及其效益评价.遥感技术与应用,2005,(05)：13-17.
[119]蒋阿宁,黄文江,赵春江,等.基于光谱指数的冬小麦变量施肥效应研究.中国农业科学,2007,(09)：1907-1913.
[120]蒋阿宁,黄文江,赵春江,等.基于光谱指数的变量施肥对冬小麦产量构成的影响及其效益分析.麦类作物学报,2007,(01)：122-126.
[121]Raun W, Solie J, Stone M, et al. Optical Sensor-Based Algorithm for Crop Nitrogen Fertilization. Communications in Soil Science and Plant Analysis,2005,36(19-20):2759-2781.
[122]Zhang X, Li M, Zhang Y. A new multispectral detector of crop growth condition based on fiber optics[C]. Optics & Photonics 2005,2005:58810K-58810K-9.
[123]王金刚,宫霄霖,苏淇.JTAG调试技术及其ARM仿真器应用.电子测量技术,2004,(4)：24-25.
[124]洪利,章扬,李世宝.MSP430单片机原理与应用实例详解.北京：北京航空航天大学出版社,2010.
[125]郑文刚,孙刚,申长军,等.可见-近红外作物氮素光电测量仪开发.农业工程学报,2010,(003)：178-182.
[126]翟霄翔,郝久玉,郑军.电阻式触摸屏在嵌入式系统中的应用.电子测量技术,2006,29(2)：36-37.
[127]李萍,单葆悦,刘晓东,等.USB芯片CH376在智能仪器仪表中的应用.计量与测试技术,2011,38(002)：9-10.
[128]王永虹,徐炜,郝立平.STM32系列ARM Cortex-M3微控制器原理与实践.北京航空航天大学出版社,2008.
[129]马利群,李爱农.激光雷达在森林垂直结构参数估算中的应用.世界林业研究,2011,24(1)：42-45.
[130]何祺胜,陈尔学,曹春香,等.基于LIDAR数据的森林参数反演方法研究.地球科学进展,2009,24(7)：748-755.
[131]Popescu S C, Wynne R H, Nelson R F. Estimating plot-level tree heights with lidar:local filtering with a canopy-height based variable window size. Computers and Electronics in Agriculture,2002, 37(1):71-95.
[132]Andersen H-E, Mcgaughey R J, Reutebuch S E. Estimating forest canopy fuel parameters using LIDAR data. Remote sensing of Environment,2005,94(4):441-449.
[133]Jelalian A V. Laser radar systems. EASCON'80; Electronics and Aerospace Systems Conference, 1980:546-554.
[134]Wagner W, Ullrich A, Melzer T, et al. From single-pulse to full-waveform airborne laser scanners: potential and practical challenges. International Archives of Photogrammetry and Remote Sensing, 2004,35(B3):201-206.
[135]Vandapel N, Amidi O, Miller J R. Toward laser pulse waveform analysis for scene interpretation. Robotics and Automation,2004. Proceedings. ICRA'04.2004 IEEE International Conference on,2004: 950-955.
[136]Steinvall O, Larsson H, Gustafsson F, et al. Performance of 3 D laser radar through vegetation and camouflage. Proceedings of SPIE,2005:129-142.
[137]Kuusk A. A two-layer canopy reflectance model. Journal of Quantitative Spectroscopy and Radiative Transfer,2001,71(1):1-9.
[138]Jacquemoud S, Baret F. PROSPECT:A model of leaf optical properties spectra. Remote Sensing of Environment,1990,34(2):75-91.
[139]Vermote E F, Tanre D, Deuze J L, et al. Second Simulation of the Satellite Signal in the Solar Spectrum,6S:An overview. Ieee Transactions on Geoscience and Remote Sensing,1997,35(3):675-686.
[140]Sun G, Ranson K J. Modeling Iidar returns from forest canopies. Geoscience and Remote Sensing, IEEE Transactions on,2000,38(6):2617-2626.
[141]Boedhram N, Arkebauer T J, Batchelor W D. Season-long characterization of vertical distribution of leaf area in corn. Agronomy Journal,2001,93(6):1235-1242.
[142]Yang J Z, Alley M. A mechanistic model for describing corn plant leaf area distribution. Agronomy Journal,2005,97(1):41-48.
[143]Veronica Ciganda A G,* and James Schepers. Vertical Profile and Temporal Variation of Chlorophyll in Maize Canopy:Quantitative "Crop Vigor" Indicator by Means of Refl ectance-Based Techniques,2008.
[144]Gamon J, Serrano L, Surfus J. The photochemical reflectance index:an optical indicator of photosynthetic radiation use efficiency across species, functional types, and nutrient levels. Oecologia, 1997,112(4):492-501.
[145]Tucker C J. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment,1979,8(2):127-150.
[146]许洪,王向军.多光谱,超光谱成像技术在军事上的应用.红外与激光工程,2007,36(1)：13-17.
[147]郑玉权,禹秉熙.成像光谱仪分光技术概览.遥感学报,2002,(01)：75-80.
[148]苏丽娟.成像光谱仪分光技术研究：[博士学位论文].中国科学院研究生院(西安光学精密机械研究所),2006.
[149]杨怀栋,陈科新,黄星月,等.常规光谱仪器分光系统的比较.光谱学与光谱分析,2009,29(6)：1707-1712.
[150]高雅允,高岳.光电检测技术.北京：国防工业出版社,1995.
[151]张光斌,林世鸣,渠波,等.激光雷达中雪崩光电二极管的智能应用,光电子.激光2000,11(5)：465-468.
[152]江华,周媛媛.光电倍增管的结构与性能研究.舰船电子工程,2009,29(1)：193-196.
[153]张鹏飞,周金运.单光子探测器及其发展.传感器世界,2003,10(9)：6-10.
[154]梁创,廖静,梁冰,等.硅雪崩光电二极管单光子探测器.光子学报,2000,29(12)：1142-1147.
[155]宋登元,王小平.APD, PMT及其混合型高灵敏度光电探测器.半导体技术,2000,25(3)：5-8.
[156]王忠立,刘佳音,贾云得.基于CCD与CMOS的图像传感技术.光学技术,2003,29(3)：361-364.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |