收稿：2020-10-20，
纸质出版：2021-01-07
移动端阅览
对目标空间三维—光谱信息的高分辨一体化获取与应用，是对地观测技术发展的前沿科学问题。结合高光谱成像与激光雷达测距的技术优势，对地观测多光谱/高光谱激光雷达遥感技术手段应运而生，并成为遥感技术未来发展的重要方向。本文分3个阶段详细回顾了对地观测高光谱激光雷达系统的发展历程，并针对其独有数据类型阐述了数据处理研究方面的探索研究。最后，重点分析了高光谱激光雷达在测绘领域、农林业领域的重大应用潜力，展望了未来对地观测高光谱激光雷达发展面临的机遇和挑战。
In the development of earth observation technology
the integrated acquisition and application for high-resolution 3D-spectral information of targets is one of the frontier scientific issues. In order to achieve the integrated acquisition of geometric characteristics and spectral information for targets
a lot of exploration studies have been carried out at home and abroad based on the current active and passive remote sensing technology. Combining the technical advantages of hyperspectral imaging and lidar ranging
multispectral/hyperspectral lidar for earth observation came into being and has become an important direction for the future development of remote sensing.This article reviews the development of the hyperspectral lidar system for earth observation in three stages. In the initial exploration stage
the research mainly focused on dual-wavelength lidar
mainly using specific wavelength lasers for specific applications. Then
in the progressive development stage
multispectral lidar was proposed to achieve spectral information acquisition of multi-wavelengths
including prototype systems with multiple single-wavelength lasers and supercontinuum lasers. Finally
in the gradual development stage
hyperspectral lidar was developed to obtain spectral information by more wavelengths. Which can achieve wider spectrum coverage and higher spectral resolution in visible-near infrared bands.Subsequently
the exploratory research for data processing of hyperspectral lidar was expounded. It mainly involves two aspects: processing of full-waveform data in multi-bands; geometric correction and radiometric correction. In terms of full-waveform data processing
hyperspectral lidar has better capability of full-waveform decomposition for weak echo bands and low signal-to-noise bands. In terms of geometric correction
the asynchronization caused by full-waveform pulse echo in different bands needs to be solved. And radiometric correction should be mainly focused on the influence of distance
angle of incidence and roughness of the target.In addition
this paper analyzes the potential application of hyperspectral lidar in the field of surveying and mapping
agriculture and forestry. In the field of surveying and mapping
hyperspectral lidar can be widely used for classification of targets and land cover. In the field of agriculture and forestry
hyperspectral lidar can simultaneously obtain the spatial structure and spectral information of vegetation. Thus
it provides a new method for detecting the three-dimensional distribution of vegetation physiological and biochemical characteristics. Finally
we look forward to the challenges for the future development of hyperspectral lidar for earth observation. And the direction for future development is also putted forward: miniaturization
practicality and demonstration applications.
Alonzo M , Bookhagen B , and Roberts D A . 2014 . Urban tree species mapping using hyperspectral and lidar data fusion . Remote Sensing of Environment , 148 , 70 - 83
Beger R , Gedrange C , Hecht R , and Neubert M . 2011 . Data fusion of extremely high resolution aerial imagery and LiDAR data for automated railroad centre line reconstruction . ISPRS Journal of Photogrammetry and Remote Sensing , 66 ( 6 ), S40 - S51
Bi K , Niu Z , Gao S , Xiao S , Pei J , Zhang C , and Huang N . 2020 . Simultaneous extraction of plant 3-D biochemical and structural parameters using hyperspectral LiDAR . IEEE Geoscience and Remote Sensing Letters [ DOI: 10.1109/LGRS. 2020.3025321 http://dx.doi.org/10.1109/LGRS.2020.3025321 ]
Briese C , Pfennigbauer M , Ullrich A , and Doneus M . 2013 . Multi-wavelength airborne laser scanning for archaeological prospection . Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci , 40 , 119 - 124
Buller G S , Harkins R D , McCarthy A , Hiskett P A , MacKinnon G , Smith G , Sung R , Wallace A M , Lamb R , Ridley K , and Rarity J . 2005 . Multiple wavelength time-of-flight sensor based on time-correlated single-photo counting . Review of Scientific Instruments . 76 , 083112
Chen B , Shi S , Gong W , Zhang Q , Yang J , Du L , Sun J , Zhang Z , and Song S . 2017 . Multispectral LiDAR Point Cloud Classification: A Two-Step Approach . Remote Sensing , 9 ( 4 ) [DOI: 10.3390/rs9 040373]
Chen B , Shi S , Sun J , Gong W , Yang J , Du L , Guo K , Wang B , and Chen B . 2019 . Hyperspectral lidar point cloud segmentation based on geometric and spectral information . Optics Express , 27 ( 17 ), 24043 - 24059 [ DOI: 10.1364/oe.27.024043 http://dx.doi.org/10.1364/oe.27.024043 ]
Chen Y , Jiang C , Hyyppä J , Qiu S , Wang Z , Tian M , Li W , Puttonen E , Zhou H , and Feng Z . 2018 . Feasibility study of ore classification using active hyperspectral LiDAR . IEEE Geoscience and Remote Sensing Letters , 15 ( 11 ), 1785 - 1789
Chen Y , Li W , Hyyppä J , Wang N , Jiang C , Meng F , Tang L , Puttonen E , and Li C . 2019 . A 10-nm spectral resolution hyperspectral LiDAR system based on an acousto-optic tunable filter . Sensors , 19 ( 7 ), 1620 [ DOI: 10.3390/s19071620 http://dx.doi.org/10.3390/s19071620 ]
Chen Y , Raikkonen E , Kaasalainen S , Suomalainen J , Hakala T , Hyyppa J , and Chen R . 2010 . Two-channel hyperspectral LiDAR with a supercontinuum laser source . Sensors , 10 ( 7 ), 7057 - 7066 [ DOI: 1 0.3390/s100707057 http://dx.doi.org/10.3390/s100707057 ]
Dalponte M , Bruzzone L , and Gianelle D . 2008 . Fusion of hyperspectral and LIDAR remote sensing data for classification of complex forest areas . IEEE Transactions on Geoscience and Remote Sensing , 46 ( 5 ), 1416 - 1427
Dalponte M , Bruzzone L , and Gianelle D . 2012 . Tree species classification in the Southern Alps based on the fusion of very high geometrical resolution multispectral/hyperspectral images and LiDAR data . Remote Sensing of Environment , 123 , 258 - 270
Debes C , Merentitis A , Heremans R , Hahn J , Frangiadakis N , van Kasteren T , Liao W , Bellens R , Pižurica A , and Gautama S . 2014 . Hyperspectral and LiDAR data fusion: Outcome of the 2013 GRSS data fusion contest . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 7 ( 6 ), 2405 - 2418
Ding Q , Chen W , King B , Liu Y , and Liu G . 2013 . Combination of overlap-driven adjustment and Phong model for LiDAR intensity correction. ISPRS Journal of Photogrammetry & Remote Sensing, 75(JAN.) , 40 - 47
Dong J , Zhuang D , Huang Y , and Fu J . 2009 . Advances in multi-sensor data fusion: Algorithms and applications . Sensors , 9 ( 10 ), 7771 - 7784
Douglas E S , Strahler A , Martel J , Cook T , Mendillo C , Marshall R , Chakrabarti S , Schaaf C , Woodcock C , Li Z , Yang X , Culvenor D , Jupp D , Newnham G , and Lovell J . 2012 . DWEL: A dual-wavelength echidna lidar for ground-based forest scanning . IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE : 4998 - 5001
Du L , Gong W , Shi S , Yang P , Sun J , Zhu B , and Song S . 2016 . Estimation of rice leaf nitrogen contents based on hyperspectral LIDAR . International Journal of Applied Earth Observation and Geoinformation , 44 , 136 - 143 [ DOI: 10.1016/j.jag.2015.08.008 http://dx.doi.org/10.1016/j.jag.2015.08.008 ]
Du L , Gong W , Yang J . 2018 . Application of spectral indices and reflectance spectrum on leaf nitrogen content analysis derived from hyperspectral LiDAR data . Optics and Laser Technology , 107 : 372 - 379
Eitel J U , Magney T S , Vierling L A , and Dittmar G . 2014 . Assessment of crop foliar nitrogen using a novel dual-wavelength laser system and implications for conducting laser-based plant physiology . ISPRS Journal of Photogrammetry and Remote Sensing , 97 , 229 - 240
Fernandez-Diaz J , Carter W , Glennie C , Shrestha R , Pan Z , Ekhtari N , Singhania A , Hauser D , and Sartori M . 2016 . Capability assessment and performance metrics for the Titan multispectral mapping lidar . Remote Sensing , 8 ( 11 ), 936 [ DOI: 10.3390/rs8110936 http://dx.doi.org/10.3390/rs8110936 ]
Gaulton R , Danson F , Ramirez F , and Gunawan O . 2013 . The potential of dual-wavelength laser scanning for estimating vegetation moisture content . Remote Sensing of Environment , 132 , 32 - 39
Gmachl C , Sivco D , Colombelli R , Capasso F , and Cho A Y . 2002 . Ultra-broadband semiconductor laser . Nature , 415 , 883 - 887
Gong W , Song S , Zhu B , Shi S , Li F , and Cheng X . 2012 . Multi-wavelength canopy LiDAR for remote sensing of vegetation: Design and system performance . ISPRS Journal of Photogrammetry and Remote Sensing , 69 , 1 - 9 [ DOI: 10.1016/j.isprsjprs.201 2.02.001 http://dx.doi.org/10.1016/j.isprsjprs.2012.02.001 ]
Gong W , Sun J , Shi S , Yang J , Du L , Zhu B , and Song S . 2015 . Investigating the potential of using the spatial and spectral information of multispectral LiDAR for object classification . Sensors , 15 ( 9 ), 21989 - 22002 [ DOI: 10.3390/s150921989 http://dx.doi.org/10.3390/s150921989 ]
Guo Z , Liu Y , Zheng X , and Yin K . 2019 . Active hyperspectral imaging with a supercontinuum laser source in the dark . Chinese Physics B , 028 ( 003 ), 193 - 197
Hakala T , Suomalainen J , Kaasalainen S , and Chen Y . 2012 . Full waveform hyperspectral LiDAR for terrestrial laser scanning . Optics Express , 20 ( 7 ), 7119 - 7127
Hermann G , and Boris J . 2010 . Investigations on surface reflection models for intensity normalization in airborne laser scanning (ALS) data . Photogrammetric Engineering & Remote Sensing , 76 ( 9 ), 1051 - 1060
Höfle B , and Pfeifer N . 2007 . Correction of laser scanning intensity data: Data and model-driven approaches . ISPRS Journal of Photogrammetry and Remote Sensing , 62 ( 6 ), 415 - 433
Johnson B , Joseph R , Nischan M L , Newbury A B , Kerekes J P , Barclay H T , Willard B C , and Zayhowski J J . 1999 . Compact active hyperspectral imaging system for the detection of concealed targets . Detection and Remediation Technologies for Mines and Minelike Targets IV . 3710 , 144-153
Jones T G , Coops N C , and Sharma T . 2010 . Assessing the utility of airborne hyperspectral and LiDAR data for species distribution mapping in the coastal Pacific Northwest, Canada . Remote Sensing of Environment , 114 ( 12 ), 2841 - 2852
Junttila S , Kaasalainen S , Vastaranta M , Hakala T , Nevalainen O , and Holopainen M . 2015 . Investigating bi-temporal hyperspectral lidar measurements from declined trees—experiences from laboratory test . Remote Sensing , 7 ( 10 ), 13863 - 13877 [ DOI: 10.3390/rs710 13863 http://dx.doi.org/10.3390/rs71013863 ]
Kaasalainen S , Jaakkola A , Kaasalainen M , Krooks A , and Kukko A . 2011 . Analysis of incidence angle and distance effects on terrestrial laser scanner intensity: Search for correction methods . Remote Sensing , 3 ( 10 ), 2207 - 2221
Kaasalainen S , Krooks A , Kukko A , and Kaartinen H . 2009 . Radiometric calibration of terrestrial laser scanners with external reference targets . Remote Sensing , 1 ( 3 ), 144 - 158
Kaasalainen S , Hakala T , Nevalainen O , Puttonen E , and Anttila K . 2014 . Hyperspectral lidar in non-destructive 4D monitoring of climate variables. ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL- 7 , 109 - 111 [ DOI: 10.5194/isprsarchives-XL-7-1 09-2014 http://dx.doi.org/10.5194/isprsarchives-XL-7-109-2014 ]
Kashani A G , Olsen M J , Parrish C E , and Wilson N . 2015 . A review of LiDAR radiometric processing: From ad hoc intensity correction to rigorous radiometric calibration . Sensors , 15 ( 11 ), 28099 - 28128
Kereszturi G , Schaefer L N , Schleiffarth W K , Procter J , Pullanagari R R , Mead S , and Kennedy B . 2018 . Integrating airborne hyperspectral imagery and LiDAR for volcano mapping and monitoring through image classification . International Journal of Applied Earth Observation and Geoinformation , 73 , 323 - 339
Khodadadzadeh M , Li J , Prasad S , and Plaza A . 2015 . Fusion of hyperspectral and LiDAR remote sensing data using multiple feature learning . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 8 ( 6 ), 2971 - 2983
Kumar B , Pandey G , Lohani B , and Misra S C . 2019 . A multi-faceted CNN architecture for automatic classification of mobile LiDAR data and an algorithm to reproduce point cloud samples for enhanced training . ISPRS Journal of Photogrammetry and Remote Sensing , 147 , 80 - 89
Li W , Niu Z , Sun G , Gao S , and Wu M . 2016 . Deriving backscatter reflective factors from 32-channel full-waveform LiDAR data for the estimation of leaf biochemical contents . Optic Express , 24 ( 5 ), 4771 - 4785 [ DOI: 10.1364/OE.24.004771 http://dx.doi.org/10.1364/OE.24.004771 ]
Li W , Jiang C , Chen Y , Hyyppä J , Tang L , Li C , and Wang S . 2018 . A Liquid Crystal Tunable Filter-Based Hyperspectral LiDAR System and Its Application on Vegetation Red Edge Detection . IEEE Geoscience and Remote Sensing Letters , 16 ( 2 ), 291 - 295
Lim K , Treitz P , Wulder M , St-Onge B , and Flood M . 2003 . LiDAR remote sensing of forest structure . Progress in Physical Geography , 27 ( 1 ), 88 - 106
Man Q , Dong P , and Guo H . 2015 . Pixel-and feature-level fusion of hyperspectral and lidar data for urban land-use classification . International Journal of Remote Sensing , 36 ( 6 ), 1618 - 1644
Morsdorf F , Nichol C , Malthus T , and Woodhouse I H . 2009 . Assessing forest structural and physiological information content of multi-spectral LiDAR waveforms by radiative transfer modelling . Remote Sensing of Environment , 113 ( 10 ), 2152 - 2163 [ DOI: 10.1 016/j.rse.2009.05.019 http://dx.doi.org/10.1016/j.rse.2009.05.019 ]
Mundt J T , Streutker D R , and Glenn N F . 2006 . Mapping sagebrush distribution using fusion of hyperspectral and lidar classifications . Photogrammetric Engineering & Remote Sensing , 72 ( 1 ), 47 - 54
Nevalainen O , Hakala T , Suomalainen J , and Kaasalainen S . 2013 . Nitrogen concentration estimation with hyperspectral LiDAR. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, II-5/W 2 , 205 - 210 [ DOI: 10.5194/isprsannals-II-5-W2-205-2013 http://dx.doi.org/10.5194/isprsannals-II-5-W2-205-2013 ]
Nevalainen O , Hakala T , Suomalainen J , Mäkipää R , Peltoniemi M , Krooks A , and Kaasalainen S . 2014 . Fast and nondestructive method for leaf level chlorophyll estimation using hyperspectral LiDAR . Agricultural and Forest Meteorology , 198 - 199 , 250 - 258 [ DOI: 10.1016/j.agrformet.2014.08.018 http://dx.doi.org/10.1016/j.agrformet.2014.08.018 ]
Nischan M L , Joseph R M , Libby J C , and Kerekes J P . 2003 . Active spectral imaging. Lincoln Lab. J . 14 , 131 - 144
Niu Z , Xu Z G , Sun G , Huang W J , Wang L , Feng M B , Li W , He W B and Gao S . 2015 . Design of a new multispectral waveform LiDAR instrument to monitor vegetation . IEEE Geoscience and Remote Sensing Letters , 12 ( 7 ), 1506 - 1510 [ DOI: 10.1109/lgrs.2015.2410788 http://dx.doi.org/10.1109/lgrs.2015.2410788 ]
Ortenberg F , Thenkabail P , Lyon J , and Huete A . 2011 . Hyperspectral sensor characteristics: airborne, spaceborne, hand-held, and truck-mounted; Integration of hyperspectral data with Lidar . Hyperspectral Remote Sensing of Vegetation , 39 - 68
Painter T H , Berisford D F , Boardman J W , Bormann K J , Deems J S , Gehrke F , Hedrick A , Joyce M , Laidlaw R , and Marks D . 2016 . The airborne snow observatory: Fusion of scanning lidar, imaging spectrometer, and physically-based modeling for mapping snow water equivalent and snow albedo . Remote Sensing of Environment , 184 , 139 - 152
Pan S , and Guan H . 2018 . Object Classification Using Airborne Multispectral LiDAR Data . Acta Geodaetica et Cartographica Sinica , 47 ( 2 ), 198 - 207 [ DOI: 10.11947/j.AGCS.2018.20170512 http://dx.doi.org/10.11947/j.AGCS.2018.20170512 ]
Pan S , Guan H , Yu Y , Li J , and Peng D . 2019 . A Comparative Land-Cover Classification Feature Study of Learning Algorithms: DBM, PCA, and RF Using Multispectral LiDAR Data . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 12 ( 4 ), 1314 - 1326 [ DOI: 10.1109/jstars.2019. 2899033 http://dx.doi.org/10.1109/jstars.2019.2899033 ]
Powers M A , and Davis C C . 2012 . Spectral LADAR: active range-resolved three-dimensional imaging spectroscopy . Applied Optics , 51 ( 10 ), 1468 - 1478
Puttonen E , Suomalainen J , Hakala T , Räikkönen E , Kaartinen H , Kaasalainen S , and Litkey P . 2010 . Tree species classification from fused active hyperspectral reflectance and LIDAR measurements . Forest Ecology and Management , 260 ( 10 ), 1843 - 1852
Rall J A , and Knox R G . 2004 . Spectral ratio biospheric lidar . Geoscience and Remote Sensing Symposium, 2004 . IEEE International Geoscience and Remote Sensing Symposium (IGARSS) . IEEE: 3 , 1951 - 1954
Reutebuch S E , McGaughey R J , Andersen H-E , and Carson W W . 2003 . Accuracy of a high-resolution lidar terrain model under a conifer forest canopy . Canadian Journal of Remote Sensing , 29 ( 5 ), 527 - 535
Sankey T , Donager J , McVay J , and Sankey J B . 2017 . UAV lidar and hyperspectral fusion for forest monitoring in the southwestern USA . Remote Sensing of Environment , 195 , 30 - 43
Sasaki T , Imanishi J , Ioki K , Morimoto Y , and Kitada K . 2012 . Object-based classification of land cover and tree species by integrating airborne LiDAR and high spatial resolution imagery data . Landscape and Ecological Engineering , 8 ( 2 ), 157 - 171
Shao H , Chen Y , Yang Z , Jiang C , Li W , Wu H , Wen Z , Wang S , Puttnon E , and Hyyppä J . 2019 . A 91-Channel Hyperspectral LiDAR for Coal/Rock Classification . IEEE Geoscience and Remote Sensing Letters
Shi S , Gong W , Du L , Sun J , and Yang J . 2016 . Potential application of novel hyperspectral lidar for monitoring crops nitrogen stress. XXIII ISPRS Congress, Commission VIII . Vol . 41 , pp. 1043 - 1047
Shi S , Song S , Gong W , Du L , Zhu B , and Huang X . 2015 . Improving backscatter intensity calibration for multispectral LiDAR . IEEE Geoscience and Remote Sensing Letters , 12 ( 7 ), 1421 - 1425 [ DOI: 10.1109/lgrs.2015.2405573 http://dx.doi.org/10.1109/lgrs.2015.2405573 ]
Sohn G , and Dowman I . 2007 . Data fusion of high-resolution satellite imagery and LiDAR data for automatic building extraction . ISPRS Journal of Photogrammetry and Remote Sensing , 62 ( 1 ), 43 - 63
Song S , Li P , Gong W , Ma Y , and Li J . 2008 . Application and key techniques of multi-wavelength lidar . Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Advanced Spatial Data Models and Analyses . 7146 , 71461 O
Song S , Wang B , Gong W , Chen Z , Lin X , Sun J , and Shi S . 2019 . A new waveform decomposition method for multispectral LiDAR . ISPRS Journal of Photogrammetry and Remote Sensing , 149 , 40 - 49 [ DOI: 10.1016/j.isprsjprs.2019.01.014 http://dx.doi.org/10.1016/j.isprsjprs.2019.01.014 ]
Sun G , Niu Z , Gao S , Huang W , Wang L , Li W , and Feng M . 2014 . 32-channel hyperspectral waveform LiDAR instrument to monitor vegetation: design and initial performance trials. Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology , Techniques and Applications V . 9263 , 926331
Sun J , Yang J , Shi S , Chen B , Du L , Gong W , and Song S . 2017a . Estimating Rice Leaf Nitrogen Concentration: Influence of Regression Algorithms Based on Passive and Active Leaf Reflectance . Remote Sensing , 9 ( 951 ) [DOI: 10.3390/ rs9090951]
Sun J , Shi S , Gong W , Yang J , Du L , Song S , Chen B , and Zhang Z . 2017b . Evaluation of hyperspectral LiDAR for monitoring rice leaf nitrogen by comparison with multispectral LiDAR and passive spectrometer . Scientific Reports , 2017 , 7 [ DOI: 10.1038/srep40362 http://dx.doi.org/10.1038/srep40362 ]
Sun J , Shi S , Yang J , Chen B , Gong W , Du L , Mao F , and Song S . 2018 . Estimating leaf chlorophyll status using hyperspectral lidar measurements by PROSPECT model inversion . Remote Sensing of Environment , 212 , 1 - 7 [ DOI: 10.1016/j.rse.201 8.04.024 http://dx.doi.org/10.1016/j.rse.2018.04.024 ]
Hakala T , Suomalainen J , Kaasalainen S , and Chen Y . 2012 . Full waveform hyperspectral LiDAR for terrestrial laser scanning . Optics Express , 20 ( 7 ), 7119 - 7127
Tan S , and Narayanan R M . 2002 . A multiwavelength airborne polarimetric lidar for vegetation remote sensing: instrumentation and preliminary test results . IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE : 5 , 2675 - 2677
Teo T-A , and Wu H-M . 2017 . Analysis of land cover classification using multi-wavelength LiDAR system . Applied Sciences , 7 ( 7 ), 663 [ DOI: 10.339 0/app7070663 http://dx.doi.org/10.3390/app7070663 ]
Wagner W . 2010 . Radiometric calibration of small-footprint full-waveform airborne laser scanner measurements: Basic physical concepts . ISPRS Journal of Photogrammetry and Remote Sensing , 65 ( 6 ), 505 - 513
Wallace A M , McCarthy A , Nichol C J , Ximing R , Morak S , Martinez-Ramirez D , Woodhouse I H , and Buller G S . 2014 . Design and evaluation of multispectral LiDAR for the recovery of arboreal parameters . IEEE Transactions on Geoscience and Remote Sensing , 52 ( 8 ), 4942 - 4954 [ DOI: 10.1109/tgrs.2013.2285942 http://dx.doi.org/10.1109/tgrs.2013.2285942 ]
Wang B , Song S , Gong W , Cao X , He D , Chen Z , Lin X , Li F , and Sun J . 2020 . Color restoration for full-waveform multispectral LiDAR data . Remote Sensing , 12 ( 4 ), 593
Wang Z , Chen Y , Li C , Tian M , Zhou M , He W , Wu H , Zhang H , Tang L , Wang Y , Zhou H , Puttonen E , and Hyyppä J . 2018 . A hyperspectral LiDAR with eight channels covering from VIS to SWIR . IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE : 4293 - 4296
Wichmann V , Bremer M , Lindenberger J , Rutzinger M , Georges C , and Petrini-Monteferri F . 2015 . Evaluating the potential of multispectral airborne lidar for topographic mapping and land cover classification. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, II-3/W 5 , 113 - 119 [ DOI: 10.5194/isprsannals-II-3-W 5-113-2015 http://dx.doi.org/10.5194/isprsannals-II-3-W5-113-2015 ]
Woodhouse I , H , Nichol C , Sinclair P , Jack J , Morsdorf F , Malthus T J , and Patenaude G . 2011 . A Multispectral Canopy LiDAR Demonstrator Project . IEEE Geoscience and Remote Sensing Letters , 8 ( 5 ), 839 - 843
Xi Z , Wang T , Darvishzadeh R , Skidmore A K , and Niemann K O . 2015 . 3D leaf water content mapping using terrestrial laser scanner backscatter intensity with radiometric correction . ISPRS Journal of Photogrammetry & Remote Sensing , 110 , 14 - 23
Yan W Y , Shaker A , Habib A , and Kersting A P . 2012 . Improving classification accuracy of airborne LiDAR intensity data by geometric calibration and radiometric correction. ISPRS Journal of Photogrammetry & Remote Sensing, 67(Jan.) , p. 35 - 44
Yang X , Wang C , Xi X . 2019 . Multiple scattering effect on forest physiological parameters of multi-spectral lidar canopy waveforms. 8467-8469 . 10 . 1109/IGARSS . 2019 . 8898303
Zhang C , Gao S , Niu Z , Pei J , Bi K , and Sun G . 2019 . Calibration of the pulse signal decay effect of full-waveform hyperspectral LiDAR . Sensors , 19 ( 23 ) [DOI: 10.3390/s19235263]
Zhang J , and Lin X . 2017 . Advances in fusion of optical imagery and LiDAR point cloud applied to photogrammetry and remote sensing . International Journal of Image and Data Fusion , 8 ( 1 ), 1 - 31
Cao Q , Ma A L , Zhong Y F , Zhao J , Zhao B and Zhang L P . 2019 . Urban classification by multi-feature fusion of hyperspectral image and LiDAR data . Journal of Remote sensing , 23 ( 5 ): 892 - 903
曹琼 , 马爱龙 , 钟燕飞 , 赵济 , 赵贝 , 张良培 . 2019 . 高光谱-LiDAR 多级融合城区地表覆盖分类 . 遥感学报 ， 2019 ， 23 ( 5 ) : 892 - 903
Du Lin , Ma Yingying , Zhu Bo , Shi Shuo , Gong Wei , Song Shalei . A Method to Select Receiving Channels for the Multi-Spectral Earth Observation LiDAR [J]. Acta Optica Sinica , 2014 , 34 ( 8 ): 0828001
杜霖 , 马盈盈 , 祝波 , 史硕 , 龚威 , 宋沙磊 . 2014 . 多光谱对地观测激光雷达接收通道选择方法 . 光学学报( 08 ), 304 - 311
FU Cheng-qun ， FANG Liang ， XIE Li-jun ， WANG Yong . Joint Survey Design and Test of Common Optical Path of Hyperspectral Lidar [J]. Acta Armamentarii , 2016 , 37 ( 11 ): 2002 - 2009
付成群 , 方亮 , 谢立军 , 王勇 . 2016 . 高光谱—激光共光路联测设计与试验 . 兵工学报 . 37 ( 11 ), 2002 - 2009
Gao S , Niu Z , Sun G , Qin Y C , Li W and Tian H F . 2018 . Vertical distribution inversion of biochemical parameters using hyperspectral LiDAR . Journal of Remote sensing , 22 ( 5 ): 737 - 744
高帅 , 牛铮 , 孙刚 , 覃驭楚 , 李旺 , 田海峰 . 2018 . 高光谱激光雷达提取植被生化组分垂直分布 . 遥感学报 . 22 ( 5 ): 737 - 44
Gong W , Song S L , Zhu B , Lv L L , Zhang D X and Shi S . 2009 . Multispectral earth observation LiDAR system . CN , No .
ZL 200910266255.1 龚威 , 宋沙磊 , 祝波 , 吕丽蕾 , 张道熙 , 史硕 . 2009 . 多光谱对地观测激光雷达系统. 中国, No . ZL 200910266255.1
Gong W , Zhu Z Ｍ ， Song S L , Ma Y Y , Hao Z Y , Liu M Y and Li J . 2006 . A vegetation normalization index remote sensing instrument CN, No . ZL
200610124713.4. 龚威 , 朱忠敏 , 宋沙磊 , 马盈盈 , 郝中豫 , 刘梦雨 , 李俊 . 2006 . 一种植物归一化指数遥感装置. 中国, No . ZL 200610124713.4
Jang J S . 2006 . consideration on China’s Earth observation technology—current situation and future directions . Chinese Engineering Science . 8 ( 11 ), 19 - 24
姜景山 . 2006 . 中国对地观测技术发展现状及未来发展的若干思考 . 中国工程科学 . 8 ( 11 ), 19 - 24
LI G H , WANG C , XI X H , ZHENG Z J , LUO S Z and YUE C R . Extraction of glacier snowline based on airborne LiDAR and hyperspectral data fusion . REMOTE SENSING FOR LAND & RESOURCES , 2013 , 25 ( 3 ): 79 - 84
李光辉 , 王成 , 习晓环 , 郑照军 , 骆社周 , 岳彩荣 . 2013 . 机载 LiDAR 和高光谱数据融合提取冰川雪线 . 国土资源遥感 , 25 ( 3 ), 79 - 84
LIN Y , Eetu P and Juha H . 2017 . Hyperspectral LiDAR:A New Era of 3D Biophysichemical Ecometrics . Remote Sensing Information . 2017 , 32 ( 01 ): 5 - 9
林沂 , Eetu PUTTONEN , Juha HYYPPA . 2017 . 高光谱激光雷达:三维生物物理化学生态测量学 [J]. 遥感信息 , 32 ( 01 ): 5 - 9
Lin Y , Zhang M D , Zhang L F and Jiang M . Exploration of the Angular Effect in Hyperspectral LiDAR Spectrum-Location-Synchronous Data Collection . Remote Sensing Technology and Application , 2019 , 34 ( 2 ): 225 - 231
林沂 , 张萌丹 , 张立福 , 江淼 . 2019 . 高光谱激光雷达谱位合一的角度效应分析 . 遥感技术与应用 , 34 ( 2 ), 225 - 231
Liu L J , Pang Y , Fan W Y , Li Z Y , Zhang D R , Li M Z . 2013 . Fused airborne LiDAR and hyperspectral data for tree species identification in a natural temperate forest . journal of remote sensing , 17 ( 3 ), 679 - 695
刘丽娟 , 庞勇 , 范文义 , 李增元 , 张登荣 , 李明泽 . 2013 . 机载 LiDAR 和高光谱融合实现温带天然林树种识别 . 遥感学报 , 17 ( 3 ), 679 - 695
Shi S , Gong W , Zhu B and Song S L . 2013 . A novel multi-Spectral LiDAR for earth observation and implementation of Control System Geomatics and Information Science of Wuhan University , 38 ( 11 ): 1294 - 1297
史硕 , 龚威 , 祝波 , 宋沙磊 . 2013 . 新型对地观测多光谱激光雷达及其控制实现 . 武汉大学学报(信息科学版) , 38 ( 11 ), 1294 - 1297
Song S L . 2010 . Principles and key techniques of multispectral LiDAR for Earth observation . Wuhan : Wuhan University
宋沙磊 . 2010 . 对地观测多光谱激光雷达基本原理及关键技术 . 武汉 ： 武汉大学
Qin Y C , Li B , Niu Z , et al . Stepwise decomposition and relative radiometric normalization for small footprint LiDAR waveform . Sci China Earth Sci ,2010 覃驭楚 , 李斌 , 牛铮 , 黄文江 , 王长耀 . 2011 . 小光斑激光雷达全波形数据递进分解与相对辐射校正 . 中国科学 : 地球科学 , 41 ( 1 ), 103 - 109 [ DOI: 10.1007/s11430-01 0-4120-y http://dx.doi.org/10.1007/s11430-010-4120-y ]
Tan K and Cheng X J . 2015 . TLS Laser Intensity Correction Based on Polynomial Mode , Chinese Journal of Lasers , 42 ( 3 ), 0314002
谭凯 , 程效军 . 2015 . 基于多项式模型的 TLS 激光强度值改正 . 中国激光 , 42 ( 3 ), 0314002
Wang B H , Song S L , Gong W , Chen Z W , Lin X , Cheng X W , Li F Q , Shi S . 2017 . Optimization decomposition method of full-waveform LiDAR . Acta Geodaetica et Cartographica Sinica , 2017 , 46 ( 11 ): 1859 - 1867
王滨辉 , 宋沙磊 , 龚威 , 陈振威 , 林鑫 , 程学武 , 李发泉 , 史硕 . 2017 . 全波形激光雷达的波形优化分解算法 . 测绘学报 , 46 ( 11 ), 1859 - 1867 [ DOI: 10.11947/j.AGCS.2017. 20170045 http://dx.doi.org/10.11947/j.AGCS.2017.20170045 ]
Wang C , Menenti M , StollM P , Li C R , Tang L L . 2007 . Error Analysis & Correction of Airborne LiDAR Data . journal of remote sensing , 11 ( 3 ), 390 - 397
王成 , Menenti M , StollM P , 李传荣 , 唐伶俐 . 2007 . 机载激光雷达数据的误差分析及校正 . 遥感学报 , 11 ( 3 ), 390 - 397
Wang Y Z , Tao Y L , Rong W and Luo P P . 2015 . A hyperspectral spectral optical path integration system with LiDAR . CN , No . ZL 201520173212 . X （王玉诏 , 陶宇亮 , 荣微 , 罗萍萍 . 2015 . 一种高光谱与激光雷达共光路一体化分光系统 . 中国 , No . ZL 201520173212 . X）
Zhu B . 2015 . Principles and Key Techniques of Hyperspectral-LIF Joint Observation LiDAR . Wuhan : Wuhan University
祝波 . 2015 . 高光谱与诱导荧光联合观测激光雷达原理及关键技术 . 武汉 ： 武汉大学
相关作者
相关机构
京公网安备11010802024621
