[1] Vahtmäe E, Paavel B, Kutser T. How much benthic information can be retrieved with hyperspectral sensor from the optically complex coastal waters? [J]. J Appl Remote Sens, 2020, 14(1): 016504. doi:  10.1117/1.JRS.14.016504
[2] Klemas V V. Coastal and environmental remote sensing from unmanned aerial vehicles:An overview [J]. Journal of Coastal Research, 2015, 31(5): 1260-1267. doi:  10.2112/JCOASTRES-D-15-00005.1
[3] Lou Xiulin, Hu Chuanmin. Diurnal changes of a harmful algal bloom in the East China Sea: Observations from GOCI [J]. Remote Sensing of Environment, 2014, 140: 562-572. doi:  10.1016/j.rse.2013.09.031
[4] Pettersen R, Johnsen G, Bruheim P, et al. Development of hyperspectral imaging as a bio-optical taxonomic tool for pigmented marine organisms [J]. Organisms Diversity & Evolution, 2014, 14(2): 237-246.
[5] Bansod B, Singh R, Thakur R. Analysis of water quality parameters by hyperspectral imaging in Ganges River [J]. Spatial Information Research, 2018, 26: 203-211. doi:  10.1007/s41324-018-0164-4
[6] Jia Beibei, Yoon Seung-Chul, Zhuang Hong, et al. Prediction of pH of fresh chicken breast fillets by VNIR hyperspectral imaging [J]. Journal of Food Engineering, 2017, 208: 57-65. doi:  10.1016/j.jfoodeng.2017.03.023
[7] Cai F, Lu W, Shi W, et al. A mobile device-based imaging spectrometer for environmental monitoring by attaching a lightweight small module to a commercial digital camera [J]. Scientific Reports, 2017, 7(1): 15602. doi:  10.1038/s41598-017-15848-x
[8] Gardner B, Reddy R, Mayerich D, et al. Application of vibrational spectroscopy and imaging to point-of-care medicine: A review [J]. Appl Spectrosc, 2018, 72(S1): 52-84.
[9] Cai F, Dan W, Min Z, et al. Pencil-like imaging spectrometer for bio-samples sensing [J]. Biomedical Optics Express, 2017, 8(12): 5427. doi:  10.1364/BOE.8.005427
[10] Yao Xinli, Li Shuo, He Sailing. Dual-mode hyperspectral bio-imager with a conjugated camera for quick object-selection and focusing [J]. Progress in Electromagnetics Research, 2020, 168: 133-143. doi:  10.2528/PIER20080308
[11] Wei Lin, Su Kang, Zhu Siqi, et al. Identification of microalgae by hyperspectral microscopic imaging system [J]. Spectroscopy Letters, 2017, 50(1): 59-63. doi:  10.1080/00387010.2017.1287094
[12] Chang Chih-Chung, Lin Chih-Jen. Libsvm: A library for support vector machines [J]. ACM Transactions on Intelligent Systems and Technology, 2011, 2(3): 1-27. doi:  10.1145/1961189.1961199
[13] Kong Z, Liu Z, Zhang L, et al. Atmospheric pollution monitoring in urban area by employing a 450-nm Lidar system [J]. Sensors (Basel), 2018, 18(6): 1880. doi:  10.3390/s18061880
[14] Kong Z, Ma T, Cheng Y, et al. Feasibility investigation of a monostatic imaging lidar with a parallel-placed image sensor for atmospheric remote sensing [J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 2020, 254: 107212. doi:  10.1016/j.jqsrt.2020.107212
[15] Mei L, Brydegaard M. Atmospheric aerosol monitoring by an elastic Scheimpflug lidar system [J]. Opt Express, 2015, 23(24): A1613-A1628. doi:  10.1364/OE.23.0A1613
[16] Mei L, Guan P, Yang Y, et al. Atmospheric extinction coefficient retrieval and validation for the single-band Mie-scattering Scheimpflug lidar technique [J]. Opt Express, 2017, 25(16): A628-A638. doi:  10.1364/OE.25.00A628
[17] Gao Fei, Li Jingwei, Lin Hongze, et al. Oil pollution discrimination by an inelastic hyperspectral Scheimpflug lidar system [J]. Opt Express, 2017, 25(21): 25515-25522. doi:  10.1364/OE.25.025515
[18] Malmqvist E, Brydegaard M, Alden M, et al. Scheimpflug lidar for combustion diagnostics [J]. Opt Express, 2018, 26(12): 14842-14858. doi:  10.1364/OE.26.014842
[19] Duan Z, Yuan Y, Lu J C, et al. Underwater spatially, spectrally, and temporally resolved optical monitoring of aquatic fauna [J]. Opt Express, 2020, 28(2): 2600-2610. doi:  10.1364/OE.383061
[20] Zhao G, Malmqvist E, Rydhmer K, et al. Inelastic hyperspectral lidar for aquatic ecosystems monitoring and landscape plant scanning test[C]//The 28th International Laser Radar Conference (ILRC 28), EPJ Web of Conferences, 2018, 176: 01003.
[21] Zhao G, Ljungholm M, Malmqvist E, et al. Inelastic hyperspectral lidar for profiling aquatic ecosystems [J]. Laser & Photonics Reviews, 2016, 10(5): 807-813. doi:  10.1002/lpor.201600093
[22] Chen Kun, Gao Fei, Chen Xiang, et al. Overwater light-sheet Scheimpflug lidar system for an underwater three-dimensional profile bathymetry [J]. Appl Opt, 2019, 58(27): 7643-7648. doi:  10.1364/AO.58.007643
[23] Gao Fei, Lin Hongze, Chen Kun, et al. Light-sheet based two-dimensional Scheimpflug lidar system for profile measurements [J]. Opt Express, 2018, 26(21): 27179-27188. doi:  10.1364/OE.26.027179
[24] He Sailing, Chen Xiang, Li Shuo, et al. Small hyperspectral imagers and lidars and their marine applications [J]. Infrared and Laser Engineering, 2020, 49(2): 0203001. (in Chinese) doi:  10.3788/IRLA202049.0203001
[25] Lin Hongze, Zhang Yao, Mei Liang. Fluorescence Scheimpflug LiDAR developed for the three-dimension profiling of plants [J]. Opt Express, 2020, 28(7): 9269-9279. doi:  10.1364/OE.389043
[26] Luo Longqiang, Chen Xiang, Xu Zhanpeng, et al. A parameter-free calibration process for a Scheimpflug LIDAR for volumetric profiling [J]. Progress in Electromagnetics Research, 2020, 169: 117-127. doi:  10.2528/PIER20120701
[27] Xu Zhanpeng, Jiang Yiming, He Sailing. Multi-mode microscopic hyperspectral imager for the sensing of biological samples [J]. Applied Sciences, 2020, 10(14): 4876. doi:  10.3390/app10144876
[28] Cai Fuhong, Chen Jie, Xie Xiaofeng, et al. The design and implementation of portable rotational scanning imaging spectrometer [J]. Opt Commun, 2020, 459: 125016. doi:  10.1016/j.optcom.2019.125016
[29] Luo Longqiang, Li Shuo, Yao Xinli, et al. Rotational hyperspectral scanner and related image reconstruction algorithm [J]. Sci Rep, 2021, 11: 3296. doi:  10.1038/s41598-021-82819-8
[30] Xu Zhanpeng, Jiang Yiming, Ji Jiali, et al. Classification, identification, and growth stage estimation of microalgae based on transmission hyperspectral microscopic imaging and machine learning [J]. Opt Express, 2020, 28(21): 30686-30700. doi:  10.1364/OE.406036
[31] Kürüm U, Wiecha P R, French R, et al. Deep learning enabled real time speckle recognition and hyperspectral imaging using a multimode fiber array [J]. Opt Express, 2019, 27(15): 20965-20979. doi:  10.1364/OE.27.020965
[32] Luo Jing, Li Shuo, Forsberg Erik, et al. 4D surface shape measurement system with high spectral resolution and great depth accuracy [J]. Opt Express, 2021, 29(9): 13048-13070. doi:  10.1364/OE.423755