Shoreline Change Analysis Using Historical Multispectral Landsat Images of the Pacific Coast of Panama

Abstract

The shoreline is the interface between sea and land influenced by natural, anthropogenic factors and climate change. The study of the evolution of the shoreline provides information to evaluate accretion or erosion processes. Shoreline erosion represents a threat to the safety of the coastal population, reducing the extension of the beach zone and making human settlements vulnerable to extreme events. This research presents the analysis of the evolution of the shoreline by multispectral images from Landsat satellites and the Digital Shoreline Analysis System (DSAS) of the Pacific Coast of Panama for the period of 1998–2021. The automated shoreline extraction was generated by combining remote sensing techniques, such as the Histogram Threshold Method and the Band Ratio Method, to generate binary images delineating the land and water zone. The most vulnerable zone, due to erosion processes and the exposition of urban areas, corresponds to the zone of Serena beach and Coronado beach with an average negative distance movement of −23.95 m. Finally, it was concluded that there is a general tendency of erosion processes in the study zone with a rate for long-term analysis of −1.12 m/y (zone I), −1.01 m/y (zone II), and −1.08 m/y (zone III).

Quantifying Aperiodic Cliff Top and Cliff Face Retreat Rates for an Eroding Drumlin on Ireland’s Atlantic Coast Using Structure-from-Motion

“…Overall, the higher rates along the western section reflect the removal of the talus slope (circa 5 m), but this spatial variability was reduced after this sediment was removed. The restricted interval (three days) between our 2 October 2019 and 5 October 2019 surveys coincided with Storm Lorenzo, which passed over Ireland on 3 October 2019 [75]. According to our storm detection analysis, this system failed to satisfy the criteria for being categorised as a storm when it passed Silverstrand.…”

Level of Climate Change-Related Coastline Change Case Study: East Coast Tourism Area of Surabaya, Indonesia

“…It is particularly advantageous for extensive areas with a significant number of transects, making it highly scalable and suitable for large-scale applications [23]. Additionally, DSAS facilitates the comparison of coastline changes across different years, allowing for a comprehensive assessment of temporal variations in coastal landscapes [24]. Moreover, the method's predictive capabilities extend to forecasting future coastline changes, enhancing its utility as a forward-looking tool for anticipating and understanding coastal transformations over time [24].…”

“…Additionally, DSAS facilitates the comparison of coastline changes across different years, allowing for a comprehensive assessment of temporal variations in coastal landscapes [24]. Moreover, the method's predictive capabilities extend to forecasting future coastline changes, enhancing its utility as a forward-looking tool for anticipating and understanding coastal transformations over time [24]. The analysis of shoreline change aims to obtain data on the extent of accretion and abrasion and the annual rate of shoreline change.…”

Measuring Cliff Top and Cliff Face Retreat Rates of a Coastal Drumlin Using Structure-from-Motion in Galway Bay, Ireland.

“…We used DSAS to compute changes in shoreline position over the four periods depicted in Table 4. DSAS is a freely available add-on tool for Esri ArcGis and is applied widely in coastal research [14,15,26,27,[70][71][72]. To detect spatial patterns in shoreline changes and erosion rates, we computed perpendicular shoreline transects every metre along the cliff base.…”