基于多项式回归模型的岛礁遥感浅海水深反演

王燕红; 陈义兰; 周兴华; 杨磊; 付延光

doi:10.3969/j.issn.0253-4193.2018.03.012

基于多项式回归模型的岛礁遥感浅海水深反演

doi: 10.3969/j.issn.0253-4193.2018.03.012

1.
国家海洋局第一海洋研究所, 山东青岛 266061
2.
国家海洋局第一海洋研究所, 山东青岛 266061;山东科技大学测绘科学与工程学院, 山东青岛 266590
3.
山东科技大学测绘科学与工程学院, 山东青岛 266590

基金项目: 海洋卫星业务应用与无线电管理。

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出版历程
- 收稿日期: 2017-03-28

Research on reef bathymetry using remote sensing based on polynomial regression model

1.
The First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China
2.
The First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China;Geometrics College, Shandong University of Science and Technology, Qingdao 266590, China
3.
Geometrics College, Shandong University of Science and Technology, Qingdao 266590, China

摘要

摘要: Lyzenga's模型由于简单有效得到广泛应用，但是模型易欠拟合导致精度不高。本文提出了一种基于Lyzenga's模型的改进模型，通过增加多项式次数的方法，扩大模型特征维度，使得反演模型正确拟合，从而提高反演精度。基于WorldView-2遥感影像和0~30 m实测水深数据反演岛礁周围浅水水深，使用10折交叉验证和模型残差分析两种方法验证了改进模型的有效性和鲁棒性。结果表明，改进模型精度更高，在多项式次数为3时，模型最优。最后，根据改进模型反演得到的水深建立岛礁水下地形模型，能够直观、丰富地表达岛礁礁盘的微地形信息。
- 岛礁 /
- 水深反演 /
- 改进Lyzenga's模型 /
- 多项式回归
Abstract: The method proposed by Lyzenga et al., due to its simplicity and effectiveness, has been widely applied to shallow-water bathymetry. However, this method is easy to underfit which will lead to low precision. We propose a modified model to improve the precision which will fit more correctly by amplifying the characteristic dimension and adding the degree of polynomial. We use the proposed model with WorldView-2 multispectral images and the measured 0-30 m water depth data to estimate the shallow water depth around the reef, and the 10-fold cross validation and residual analysis to validate the model. The results indicate that our model can improve the precision and is optimal using the degree of polynomial 3. At last, the water depth estimated by our model is used to calculate the terrain model around the reef, which can express the topographic feature intuitively and abundantly.
- reef /
- bathymetry /
- modify Lyzenga's method /
- polynomial regression

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参考文献(13)

李丽. 基于WorldView-2数据的西沙群岛遥感水深反演——以赵述岛和南岛为例[J]. 国土资源遥感, 2016, 28(4):170-175. Li Li. Remote sensing bathymetric inversion for the Xisha Islands based on WorldView-2 data:A case study of Zhaoshu Island and South Island[J]. Remote Sensing for Land and Resources, 2016, 28(4):170-175.

盛琳, 王双亭, 周高伟, 等. 非线性模型岛礁礁盘遥感水深反演[J]. 测绘科学, 2015, 40(10):43-47. Sheng Lin,Wang Shuangting, Zhou Gaowei, et al. Research on reefs bathymetry estimation by remote sensing based on nonlinear model[J]. Science of Surveying and Mapping, 2015, 40(10):43-47.

曹斌, 邱振戈, 曹彬才. 四种遥感浅海水深反演算法的比较[J]. 测绘科学技术学报, 2016(4):388-393. Cao Bin,Qiu Zhenge,Cao Bincai. Comparison among four inverse algorithms of water depth[J]. Journal of Geomatics Science and Technology, 2016(4):388-393.

Lyzenga D R. Passive remote sensing techniques for mapping water depth and bottom features[J]. Applied Optics, 1978, 17(3):379-383.

Lyzenga D R, Malinas N P, Tanis F J. Multispectral bathymetry using a simple physically based algorithm[J]. IEEE Transactions on Geoscience & Remote Sensing, 2006, 44(8):2251-2259.

Kanno A, Tanaka Y. Modified Lyzenga's method for estimating generalized coefficients of satellite-based predictor of shallow water depth[J]. IEEE Geoscience & Remote Sensing Letters, 2012, 9(4):715-719.

Figueiredo I N, Pinto L, Goncalves G. A modified Lyzenga's model for multispectral bathymetry using tikhonov regularization[J]. IEEE Geoscience & Remote Sensing Letters, 2015, 13(1):1-5.

Stumpf R P, Holderied K, Sinclair M. Determination of water depth with high-resolution satellite imagery over variable bottom types[J]. Limnology & Oceanography, 2003, 48(1):547-556.

田庆久, 王晶晶, 杜心栋. 江苏近海岸水深遥感研究[J]. 遥感学报, 2007(3):373-379. Tian Qingjiu, Wang Jingjing, Du Xindong. Study on water depth extraction from remote sensing imagery in Jiangsu coadtal zone[J]. Journal of Remote Sensing, 2007(3):373-379.

党福星, 丁谦. 利用多波段卫星数据进行浅海水深方法研究[J]. 海洋通报, 2003(3):55-60. Dang Fuxing, Ding Qian. A technique for extracting water depth information from multispectral scanner data in the South China Sea[J]. Marine Science Bulletin, 2003(3):55-60.

Su Haibin, Liu Hongxing, Wang Lei, et al. Geographically adaptive inversion model for improving bathymetric retrieval from satellite multispectral imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(1):465-476.

梁志诚, 黄文骞, 杨杨, 等,基于神经网络技术的多因子遥感水深反演模型[J]. 测绘工程, 2012, 21(8):17-21. Liang Zhicheng, Huang Wenqian, Yang Yang, et al. Study of the water depth retrieval based on artificial neural network[J]. Engineering of Surveying and Mapping, 2012, 21(8):17-21.

张靖宇. 浅海水深多维度遥感反演融合方法研究——以南海岛礁为例[D]. 青岛:国家海洋局第一海洋研究所,2015. Zhang Jingyu. Study on fusion models of multi-dimensional bathymetry inversion in shallow sea with remote sensing-A case study of the islands and reefs in South China Sea[D]. Qingdao:The First Institute of Oceanography, State Oceanic Administration, 2015.

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