Abstract
Measurement of beach heights in the intertidal zone has great importance for dynamic geomorphology research, coastal zone management, and the protection of ecological resources. Based on satellite images, the waterline method based on satellite images is one of the most effective methods for constructing digital elevation models (DEMs) for large-scale tidal flats. However, for fast-changing areas, such as Tiaozini in the Jiangsu coast, timely and detailed topographical data are difficult to obtain due to the insufficient images over a short period of time. In this study, as a supplement to the waterline method, an artificial neural network (ANN) model with the multi-layer feed-forward back propagation algorithm was developed to simulate the topography of variable Tiaozini tidal flats. The “7-15-15-1” double hidden layers with optimized training structures were confirmed via continuous training and comparisons. The input parameters included spectral bands (HJ-1 images B1~B4), geographical coordinates (X, Y), and the distance (D) to waterlines, and the output parameter was the elevation. The model training data were the HJ-1 image for 21 March 2014, and the corresponding topographic data obtained from the waterline method. Then, this ANN model was used to simulate synchronous DEMs corresponding to remote sensing images on 11 February 2012, and 11 July 2013, under low tide conditions. The height accuracy (root mean square error) of the two DEMs was about 0.3–0.4 m based on three transects of the in-situ measured data, and the horizontal accuracy was 30 m—the same as the spatial resolution of the HJ-1 image. Although its vertical accuracy is not very high, this ANN model can quickly provide the basic geomorphological framework for tidal flats based on only one image. This model, therefore, provides an effective way to monitor rapidly changing tidal flats.
Highlights
Tidal flats are intertidal, soft sediment habitats, found between mean higher high water (MHHW)and mean lower low water (MLLW) lines [1,2] and are present at various locations around the world.Tidal flats are an important part of the coastal zone and play an important role in improving coastal protection, increasing potential land resources, and conserving biodiversity [3,4]
The elevation estimations obtained for the testing and training datasets based on the HJ-1 image (21 March 2014) were compared to the digital elevation models (DEMs) data by the waterline method
The elevation estimations obtained for the testing and training datasets based on the HJ-1 image (21 March 2014) were compared to the initial DEM (Figure 2d) obtained by the waterline method
Summary
Soft sediment habitats, found between mean higher high water (MHHW)and mean lower low water (MLLW) lines [1,2] and are present at various locations around the world.Tidal flats are an important part of the coastal zone and play an important role in improving coastal protection, increasing potential land resources, and conserving biodiversity [3,4]. Soft sediment habitats, found between mean higher high water (MHHW). Mean lower low water (MLLW) lines [1,2] and are present at various locations around the world. Tidal flats are an important part of the coastal zone and play an important role in improving coastal protection, increasing potential land resources, and conserving biodiversity [3,4]. The monitoring of tidal flats has great importance for morphological evolution, sediment transformation, and hydrodynamic research [5]. In order to understand the dynamic changes of intertidal areas, topographic monitoring provides the most objective and foundational bases. This topographic information remains limited in most coastal areas [6].
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