A More Accurate Method of Extracting Tidal Flats Data Affected by Irregular Tides Using Surface Humidity Difference: Reducing the Dependence on High Matching Between High and Low Tide Times and Satellite Transit Times

Abstract

As a key part of coastal wetlands, the accurate distribution data of tidal flats is of great significance for the protection and management of coastal ecosystems. Current techniques for extracting tidal flats from remote sensing imagery predominantly focus on detecting the distribution range of temporary water bodies. This requires a higher degree of synchronicity between high and low tides and satellite transit time, so the existing extraction methods often result in low spatial accuracy in irregular tidal areas. To address these limitations, we selected the Yellow River Delta (YRD) as our study area and utilized the Google Earth Engine (GEE) cloud computing platform combined with time-series Landsat images to propose a new method for extracting tidal flats affected by irregular tides based on surface humidity differences. This method successfully identified the tidal flats of the YRD and was validated temporally within the study area. Additionally, promotion verification was carried out in other coastal areas affected by irregular tides, revealing strong levels of universality and robustness. Notably, in the study area, the extraction method’s accuracy improved by about 25% compared with other methods. Consequently, tidal flat mapping based on this method can provide critical data support for ecological protection of coastal zones and assist in the formulation of sustainable coastal zone management policies.

Keywords

• Google Earth engine (GEE)
• irregular tides
• surface humidity
• the Yellow River Delta (YRD)
• tidal flats