Analysis and Prediction of Changes in Coastline Morphology in the Bohai Sea, China, Using Remote Sensing

Abstract

Abstract:Coastline change reflects the dynamics of natural processes and human activity, and influences the ecology and environment of the coastal strip. This study researched the change in coastline and sea area of the Bohai Sea, China, over a 30-year period using Landsat TM and OLI remote sensing data. The total change in coastline length, sea area, and the centroid of the sea surface were quantified. Variations in the coastline morphology were measured using four shape indexes: fractal dimension, compact ratio, circularity, and square degree. Equations describing fit of the shape index, coastline length, and marine area were built. Then the marine area 10 years later was predicted using the model that had the highest prediction accuracy. The results showed that the highest prediction accuracy for the coastline length was obtained using a compound function. When a cubic function was used to predict the compact ratio, then the highest prediction accuracy was obtained using this compact ratio and a quadratic function to predict sea area. This study can provide theoretical support for the coastal development planning and ecological environment protection around the Bohai Sea.

Analyzing the Topographical Evolution Characteristics of a Bay over the Last 50 Years

“…First, coordinate systems of five phases of coastline data must be unified because of different coordinate reference systems and the projection mode of the spatial data from different sources [25][26][27]. The coastline data adopted CGCS2000 coordinate systems and Gauss-Kruger projection of central longitude 120 degrees.…”

Applying Geospatial Technology in Assessing the Coastal Vulnerability of Zaranik Protectorate to Sea-Level Rise.

“…Remote sensing (RS) technology, as a source of information, offered the availability of coherent time series of satellite image required for shoreline monitoring, in which the same area can be observed repeatedly at scales impractical to cover with traditional field techniques (Khalil et al, 2016). In coastal waters, shoreline development was successfully analyzed from Landsat images (Emam, 2016 andFu et al, 2017). Geographic information system (GIS), as a tool, offers a suitable platform that creates, integrates, stores, visualizes, and analyzes geographically referenced data to solve problems, make decisions and manage ecosystems properly (Emam, 2016).…”

Long Time-Series Mapping and Change Detection of Coastal Zone Land Use Based on Google Earth Engine and Multi-Source Data Fusion

“…The recently developed Google Earth Engine (GEE), a cloud platform for geospatial data analysis, provides alternatives for analyzing the long-term and large-area land-use changes [19]. Significant progress has been made in the GEE application for coastal zones, e.g., coastal mudflats [20,21], wetlands [22,23], mangroves [24,25], shorelines [26][27][28], and coastal development activities such as aquaculture nets [29], aquaculture ponds [30][31][32], and land reclamation [33,34]. Current studies mainly focus on limited land use in coastal zones, lacking the full-coverage classification of coastal zone land use, especially the sealand integration [13,35,36].…”