[1] Ma Y, Zhang J, Zhang J Y et al. Progress in shallow water depth mapping from optical remote sensing[J]. Advances in Marine Science, 36, 331-351(2018).

[2] Zhang Y Y, Huang R Y, Yu K F et al. Estimation of shallow water depth based on satellite hyperspectral images[J]. Journal of Geo-Information Science, 22, 1567-1577(2020).

[3] Li J, Tian H J, Xu W B et al. Study on water depth derived models based on remote sensing in the coastal seawaters of Bohai Bay[J]. Science of Surveying and Mapping, 40, 56-60(2015).

[4] Guo X L. Study on water depth inversion in shallow water with satellite multi-spectral image[D]. Shanghai: Shanghai Ocean University(2017).

[5] Li K, Zhang Y S, Liu X D et al. Study on airborne laser bathymetric system receiver field of view[J]. Acta Optica Sinica, 35, 0701005(2015).

[6] Zhang X C, Ma Y, Zhang J Y et al. Research on the remote sensing inversion fusion model of shallow water depth based on the piecewise adaptive algorithm[J]. Marine Sciences, 44, 1-11(2020).

[7] Tanis F J, Byrne H J. Optimization of multispectral sensors for bathymetry application. [C]∥Proceeding of 19th International Symposium of Remote Sensing of Environment, January 1, 1986, Ann Arbor, Michigan, USA. Washington D.C.: NTRS, 865-874(1986).

[8] Ji W, Civco D L, Kennard W C et al. 2020-10-12]. https:∥www.researchgate.net/publication/294795262_Satellite_remote_bathymetry_a_new_mechanisms_for_modeling.(1992).

[9] Paredes J M, Spero R E. Water depth mapping from passive remote sensing data under a generalized ratio assumption[J]. Applied Optics, 22, 1134-1135(1983).

[10] Stumpf R P, Holderied K, Sinclair M et al. Determination of water depth with high-resolution satellite imagery over variable bottom types[J]. Limnology and Oceanography, 48, 547-556(2003).

[11] Tian Z. Study of bathymetry inversion models using multispectral or hyperspectral data and bathy orographical mapping technology[D]. Qingdao: Shandong University of Science and Technology(2015).

[12] Cao B, Qiu Z G, Cao B C. Comparison among four inverse algorithms of water depth[J]. Journal of Geomatics Science and Technology, 33, 388-393(2016).

[13] Wen K X, Li Y, Wang H et al. Estimating inland water depth based on remote sensing and machine learning technique[J]. Tropical Geography, 40, 314-322(2020).

[14] Xia H Y. Research on bathymetry algorithm without ground data based on multispectral remote sensing image for shallow water of islands[D]. Hangzhou: Zhejiang University(2020).

[15] Pan X L, Zhang Z, Jiang T et al. An approach of the convolutional long short-term memory network for NDVI prediction[J]. Geomatics World, 27, 60-67(2020).

[16] Zhang Z H, Fang W, Du L L et al. Semantic segmentation of remote sensing image based on encoder-decoder convolutional neural network[J]. Acta Optica Sinica, 40, 0310001(2020).

[17] Pan X L, Jiang T, Zhang Z et al. A new method for extracting laver culture carriers based on inaccurate supervised classification with FCN-CRF[J]. Journal of Marine Science and Engineering, 8, 274(2020). http://www.researchgate.net/publication/340604158_A_New_Method_for_Extracting_Laver_Culture_Carriers_Based_on_Inaccurate_Supervised_Classification_with_FCN-CRF

[18] Kong F Q, Zhou Y B, Shen Q et al. End-to-end multispectral image compression using convolutional neural network[J]. Chinese Journal of Lasers, 46, 1009001(2019).

[19] Hochreiter S, Schmidhuber J. Long short-term memory[J]. Neural Computation, 9, 1735-1780(1997).

[20] Graves A. Supervised sequence labelling with recurrent neural networks[M]. Berlin, Heidelberg: Springer.(2008).

[21] Yang H J, Yan Z, Wu Z L et al. Extraction method of interest text in image based on recurrent neural network[J]. Laser & Optoelectronics Progress, 56, 241501(2019).

[22] Graves A, Schmidhuber J. Framewise phoneme classification with bidirectional LSTM and other neural network architectures[J]. Neural Networks, 18, 602-610(2005). http://www.sciencedirect.com/science/article/pii/S0893608005001206