Citation

Cohen MCL, de Souza AV, Liu KB, Yao Q. MethodsX 2023; 10: e102065.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.mex.2023.102065

PMID

36845369

PMCID

PMC9945794

Abstract

To mitigate floods and storm surges, coastal communities across the globe are under the pressure of high-cost interventions, such as coastal barriers, jetties, and renourishment projects, especially in areas prone to hurricanes and other natural disturbances. To evaluate the effectiveness of these coastal projects in a timely fashion, this methodology is supported by a Geographic Information System that is instaneously fed by regional and local data obtained shortly (24 h) after the disturbance event. Our study assesses the application of 3D models based on aerophotogrammetry from a Phantom 4 RTK drone, following a methodological flowchart with three phases. The Digital Elevation Models (DEMs) based on aerophotogrammetry obtained from a Phantom 4 RTK drone presented a low margin of error (± 5 cm) to dispense Ground Control Points. This technique enables a rapid assessment of inaccessible coastal areas due, for instance, to hurricane impacts. Evaluation of DEMs before and after the disturbance event allows quantifying the magnitudes of shoreline retreat, storm surges, difference in coastal sedimentary volumes, and identifying areas where erosion and sediment accretion occur. Orthomosaics permit the individualization and quantification of changes in vegetation units/geomorphological areas and damages to urban and coastal infrastructure. Our experience monitoring coastal dynamics in North and South America during the last decade indicates that this methodology provides an essential data flow for short and long-term decision-making regarding strategies to mitigate disaster impacts.•Permanent and regional monitoring with spatial-temporal analysis based on satellite/aerial images and lidar data prior to the event.•Local DEMs based on drone aerophotogrammetry after the event.•Integration of regional and local planialtimetric/environmental data.

Language: en

Keywords

Natural disaster; Drone; Landscape dynamics; Satellite imagery; Spatial-temporal analysis; Spatial-temporal analysis using drone and satellite imagery