Estimating muddy intertidal flat slopes under varied coastal morphology using sequential satellite data and spatial analysis

Zhou, Yong; Zhang, Dong; Cutler, Mark E. J.; Xu, Nan; Wang, Xiaohua; Sha, Hongjie; Shen, Yongming

doi:10.1016/j.ecss.2021.107183

Cited by 8 publications

(5 citation statements)

References 25 publications

(35 reference statements)

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“…Then, T_TIDE, a MATLAB-version tidal harmonic analysis software package, was applied to obtain the harmonic parameters for each gauge station [28]. Eight fundamental tidal constituents, K1, O1, M2, S2, N2, K2, M4, and MS4, were selected to represent the effects of tidal forcing in the Liangsha area [29,30]. As the tidal harmonic constituents, station latitudes, and satellite overpassing times were input into the T_TIDE package, the tidal height at each image acquisition time, together with the error estimation, was obtained.…”

Section: Tidal-height Datamentioning

confidence: 99%

“…Hence, an improved image compositing approach [20] was applied to obtain the representative synthetic waterline from the generated composite image to solve this problem. For the five selected remote sensing image datasets corresponding to the grouped waterlines, the modified normalized difference water index (MNDWI) was adopted for the image composition owing to its ability to effectively enhance the characteristics of open water and suppress the soil noise in exposed offshore sand bodies [30,31]. Considering that there were less than 7 images participating in the layer stacking process and no extreme values existed, the average-value calculation of the MNDWI was more suitable than the median-based calculation.…”

Section: Ois Dem Constructionmentioning

confidence: 99%

“…Therefore, combined with the average value of the MNDWI for each pixel, five stacked images were respectively generated. By detecting the land-sea edges from the threshold-segmented MNDWI compositing images using a Sobel operator [30], the corresponding synthetic waterlines were produced. They could effectively represent the average locations and height characteristics of these clustered waterlines.…”

Section: Ois Dem Constructionmentioning

confidence: 99%

“…(3) Tidal channel embedment All the waterlines, including directly extracted and synthetic, were then separated into discrete points with an interval of 30 m. After assigning tidal-height values to these discrete points, the initial DEM for the studied OIS could be interpolated using an inverse distance weighting method [12,30]. However, the interpolation process for the generation of DEM smoothed the tiny undulations of the intertidal flat surface, especially within the height difference of 30 to 50 cm, which was equivalent to the depth of the small tidal channel winding on the sandbank.…”

Section: Ois Dem Constructionmentioning

confidence: 99%

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An Evaluation of Wind Turbine-Induced Topographic Change in the Offshore Intertidal Sandbank Using Remote Sensing-Constructed Digital Elevation Model Data

Zhang

Zhou

et al. 2022

Remote Sensing

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With the rapid development of wind power generation, many marine wind farms have been developed on the offshore intertidal sandbank (OIS) along the coastal regions of Jiangsu Province, China during the last decade. In order to quantitatively assess the stability of offshore wind turbines and their induced topographic changes on the OIS, a digital elevation model (DEM)-based analysis supported by satellite remote sensing is adopted in the present study. Taking the Liangsha OIS at the middle of Jiangsu coast, China as the research area, we first used an enhanced waterline method (EWM) to construct the 30 m resolution DEMs for the years 2014 and 2018 with the embedment of tidal creeks to effectively express the detailed characteristics of the micro-terrain. Then, a hypothetical sandbank surface discrimination method (HSSDM) was proposed. By comparing the height difference between the hypothetical and the real terrain surface during the operation period, the wind turbine-induced topographic change rate (TCR) was estimated from the DEM of 2018. The results show that 73.47% of the 49 wind turbines in the Liangsha OIS have an erosional/depositional balanced influence on the intertidal sand body, 8.16% show a weak depositional influence, and 18.36% lead to weak erosion. The average erosional depth, 58.6 cm, reached nearly 6% to 10% of the maximum possible erosion estimated by the hydrodynamic model. Furtherly, using two DEMs for the years 2014 and 2018, the topographic change depths at the location of wind turbines were calculated. By comparing the wind turbine-induced terrain change with the naturally erosional/depositional depths of the OIS, the average contribution rate caused by the wind turbines achieved 42.17%, which meant that the impact of wind turbines on terrain changes could not be ignored. This work shows the potential of utilizing satellite-based remote sensing to monitor topographic changes in the OIS and to assess the influence of morphological variations caused by wind turbines, which will be helpful for offshore wind farm planning and intertidal environment protection.

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Section: Tidal-height Datamentioning

confidence: 99%

Section: Ois Dem Constructionmentioning

confidence: 99%

Section: Ois Dem Constructionmentioning

confidence: 99%

Section: Ois Dem Constructionmentioning

confidence: 99%

See 2 more Smart Citations

An Evaluation of Wind Turbine-Induced Topographic Change in the Offshore Intertidal Sandbank Using Remote Sensing-Constructed Digital Elevation Model Data

Zhang

Zhou

et al. 2022

Remote Sensing

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“…From that, a DEM can be constructed (Ryu et al, 2008). Satellite-derived waterlines can be used as a method for estimating slopes while taking into account nearshore topography (Zhou et al, 2021). Accurate and consistent mapping of the boundary between land and water (the 'waterline') is critical for tracking coastal change and coastal management.…”

Section: Introductionmentioning

confidence: 99%

Sentinel-2 Derived Waterlines for Coastal Monitoring Applications: A New Approach for Quantifying Vertical and Horizontal Accuracies

Castillo-Campo,

Monteys,

Beck

et al. 2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Accurate and consistent mapping of the boundary between land and water (the ‘waterline’) is critical for tracking coastal change and coastal management. Earth Observation satellite remote sensing provides a unique cost-effective alternative to traditional methods. Waterlines from satellites are often derived by methods based on spectral indices that lead to the separation between land and water. The validation strategy for these products requires a complex approach from accuracy assessment (quantifying error) to verification of its suitability for monitoring applications. Traditionally the accuracy of EO products is reduced and simplified to the resolution of the sensor or satellite that collects the data. However, environmental variables (sea conditions, weather, vegetation, anthropic) that may have a direct effect on the sensor and on the coastline that we are trying to monitor are not taken into consideration. Segments of Sentinel-2-derived waterlines were selected in North Bull Island for further analysis in the creation of a new benchmark dataset for understanding the waterline models of eastern Ireland. In our novel approach, we propose that horizontal accuracy assessment is performed by using the mean absolute distance between the GNSS reference line and the Sentinel-2-derived waterline. The vertical accuracy assessment was then calculated by the difference between the attributed waterline height compared with the mean GNSS elevation at the intersection points. Results were then compared with Dublin Port tide gauge height record. The development of reference validation models can allow more efficient application of satellite data for monitoring, and understanding how environmental variables affect each case study.

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Extracting waterline and inverting tidal flats topography based on Sentinel-2 remote sensing images: A case study of the northern part of the North Jiangsu radial sand ridges

Cao,

Liu,

et al. 2024

Geomorphology

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Estimating muddy intertidal flat slopes under varied coastal morphology using sequential satellite data and spatial analysis

Cited by 8 publications

References 25 publications

An Evaluation of Wind Turbine-Induced Topographic Change in the Offshore Intertidal Sandbank Using Remote Sensing-Constructed Digital Elevation Model Data

An Evaluation of Wind Turbine-Induced Topographic Change in the Offshore Intertidal Sandbank Using Remote Sensing-Constructed Digital Elevation Model Data

Sentinel-2 Derived Waterlines for Coastal Monitoring Applications: A New Approach for Quantifying Vertical and Horizontal Accuracies

Extracting waterline and inverting tidal flats topography based on Sentinel-2 remote sensing images: A case study of the northern part of the North Jiangsu radial sand ridges

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