Shallow water bathymetry from WorldView-2 stereo imagery using two-media photogrammetry

Cao, Baoxiang; Fang, Yong; Jiang, Zhengzhi; Gao, Li; Hu, Haiyan

doi:10.1080/22797254.2019.1658542

Cited by 34 publications

(18 citation statements)

References 24 publications

(34 reference statements)

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“…Based on the WorldView-2 high resolution multispectral images, a new empirical model for shallow water depth bathymetry is proposed. Similarly, many other methods have also been developed using WorldView-2 data, such as a two-media photogrammetry technique for WorldView-2 stereo multispectral imagery proposed by Cao et al [35]. The research areas selected in the article are also located in the Paracel Islands (Zhaoshu Island and Ganquan Island) in the South China Sea.…”

Section: Discussionmentioning

confidence: 99%

Shallow Water Bathymetry Based on Inherent Optical Properties Using High Spatial Resolution Multispectral Imagery

Zhang

2020

Remote Sensing

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Bathymetric surveys are of great importance for submarine topography mapping and coastal construction projects. They are also of great significance for terrain surveys of islands and coastal zones, maritime navigation and marine management planning. Traditional ship-borne water depth measurement methods are costly and time-consuming, therefore, in recent years, passive optical remote sensing technology has become an important means for shallow water depth measurements. In addition, multispectral water depth optical remote sensing has wide application values. Considering the relationship between water depth and the inherent optical characteristics of water column, an inherent optical parameters linear model (IOPLM) is developed to estimate shallow water bathymetry from high spatial resolution multispectral images. Experiments were carried out in the shallow waters (≤20 m) around Dongdao Island in China’s Paracel Islands and Saipan Island in the Northern Mariana Islands. Different accuracy evaluation indexes were used to verify the model. The comparisons with the traditional log-linear model and the Stumpf model show that in terms of overall accuracy and accuracy in different water depths, the IOPLM has slightly better results and stronger retrieval capabilities than the other models. The mean absolute error (MAE) of Dongdao Island and Saipan Island reached 1.17 m and 1.92 m, and the root mean square error (RMSE) was 1.49 m and 2.4 m, respectively.

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Section: Discussionmentioning

confidence: 99%

Shallow Water Bathymetry Based on Inherent Optical Properties Using High Spatial Resolution Multispectral Imagery

Zhang

2020

Remote Sensing

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“…The SIFT algorithm is used to provide accurate local feature points for correcting wrong disparities in weak texture or occluded areas, generated by the SGM algorithm. Cao et al described the detailed procedure of the combined algorithms, and showed the practical performance [47].…”

Section: ) Bathymetric Retrieval Algorithm Based On Multi-angular Immentioning

confidence: 99%

Bathymetric Retrieval Selectively Using Multiangular High-Spatial-Resolution Satellite Imagery

Cao

Deng

Liu

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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This paper introduces multi-angular imagery into physics-based bathymetry in order to compensate for the shortage of bathymetric spectral bands caused by the low spectral resolution of current high-spatial-resolution satellite multispectral imagery. The focus is to propose a selective bathymetric retrieval method to eliminate the negative effect of non-optimal image data on depth retrieval in multi-angular imagery-based bathymetry. The elimination of the negative effect is implemented by excluding non-optimal pixels in every individual image from bathymetric retrieval. An empirical criterion is designed for the determination of non-optimal pixels. The proposed method can uses multi-angular image data selectively, avoiding situations where bathymetric retrieval results from the whole multi-angular imagery are poorer than that from part of the individual images. The method was tested in two typical areas within the Xisha (Paracel) Islands of the South China Sea using two-angle WorldView-2 multispectral images. The test showed that the derived depths of the method (i.e., depths derived from the selective image data) provided a better fit to the validation depths than those from the entirety of both images. The underestimation of depths derived from the entirety of both images was also improved to some extent.

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“…Another approach which utilizes satellite imagery is two-media photogrammetry, which is a method that has been around for a long time [3,4]. In recent years, WordView-2 stereo imagery has been used to derive bathymetry estimates for depths ranging between 5 and 20 m with Root Mean Square Errors (RMSE) around 1-2 m [5,6]. In addition to satellite imagery, air-borne or even images from drones can be used to derive shallow water bathymetry.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of a Statistical Approach for Extracting Shallow Water Bathymetry Signals from ICESat-2 ATL03 Photon Data

et al. 2021

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In this study we present and validate a simple empirical method to obtain bathymetry profiles using the geolocated photon data from the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) mission, which was launched by NASA in September 2018. The satellite carries the Advanced Topographic Laser Altimeter System (ATLAS), which is a lidar that can detect single photons and calculate their bounce point positions. ATLAS uses a green laser, causing some of the photons to penetrate the air–water interface. Under the right conditions and in shallow waters (<40 m), these photons are reflected back to ATLAS after interaction with the ocean bottom. Using ICESat-2 data from four different overflights above the Heron Reef, Australia, a comparison with SDB data showed a median absolute deviation of approximately 18 cm and Root Mean Square Errors (RMSEs) down to 28 cm. Crossovers between two different overflights above the Heron Reef showed a median absolute difference of 13 cm. For an area north-west of Sisimiut, Greenland, the comparison was done with multibeam echo sounding data, with RMSEs down to between 35 cm, and correspondingly showed median absolute deviations between 33 and 49 cm. The proposed method works well under good conditions with clear waters such as in the Great Barrier Reef; however, for more difficult areas a more advanced machine learning technique should be investigated in order to find an automated method that can distinguish between bathymetry and other signals and noise.

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Shallow water bathymetry from WorldView-2 stereo imagery using two-media photogrammetry

Cited by 34 publications

References 24 publications

Shallow Water Bathymetry Based on Inherent Optical Properties Using High Spatial Resolution Multispectral Imagery

Shallow Water Bathymetry Based on Inherent Optical Properties Using High Spatial Resolution Multispectral Imagery

Bathymetric Retrieval Selectively Using Multiangular High-Spatial-Resolution Satellite Imagery

Evaluation of a Statistical Approach for Extracting Shallow Water Bathymetry Signals from ICESat-2 ATL03 Photon Data

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