Abstract
Abstract. The remote sensing method for water depth inversion is fast, flexible, and low in cost, which has become an important means of method for water depth detection. This paper takes the coastal area where is around Gulangyu Island as the research area. Based on the spectral reflectance, sea surface temperature (SST) and measured water depth data, a nonlinear inversion model of water depth is established by using BP neural network. Combined with the tide data, the water depth and underwater topography in coastal area is obtained. The average relative error is 0.27. The root mean square error is 1.92. The results show that the participation of sea surface temperature in the model construction can improve the inversion error of offshore water depth to a certain extent, and can help improve the accuracy of the model.
Highlights
Shallow water depth is an important element of underwater topography
It is helpful to better understand the topography of the coastal area and develop the marine resources by measuring the water depth. echo sounding sounder is used in traditional water depth measurement. echo sounding sounder has the characteristics of high measurement accuracy and full coverage
The results show that the average relative error of the two inversion results is 0.11, which can be ignored for 30-meter resolution data
Summary
Shallow water depth is an important element of underwater topography. It is helpful to better understand the topography of the coastal area and develop the marine resources by measuring the water depth. echo sounding sounder is used in traditional water depth measurement. echo sounding sounder has the characteristics of high measurement accuracy and full coverage. Echo sounding sounder is used in traditional water depth measurement. Echo sounding sounder has the characteristics of high measurement accuracy and full coverage This method is constrained by its inefficiency in shallow waters and very high operating logistic costs (Gao J, 2009;Jawak S D, et al.,2015). Satellite remote sensing has becoming a efficient and cost-effective supplement to traditional measurements of water depth because of its high spatial, temporal and spectral resolution, as well as its advantages of immediacy, dynamic, accuracy and comprehensiveness (Su, et al.,2015), especially in remote and broad areas. According to the theory of radiative transfer in the sea, the vertical water temperature has a certain relationship with water depth especially in the coastal area because of the underwater bottom topography. We can explore the feasibility of temperature assisted extraction of water depth
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