26 July 2022 Data-driven approach for 2D shoreline, and 3D volumetric change detection analysis: a case study for Jupiter inlet lighthouse outstanding natural area
Pandiyan Kesavan, Sudhagar Nagarajan, Peter De Witt
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Abstract

Coastal areas are constantly changing and are influenced by a variety of variables, including environmental, ecological, geological, and anthropological factors. The plethora of coastal change has created substantial challenges for coastal land infrastructures, animal habitat, vegetation conservation, and monitoring. It is important to track these changes, monitor, predict, and preserve the future of coastal areas. Shoreline mapping has mostly concentrated on two-dimensional (2D) distance changes along the coast due to the lack of coastal elevational data and the precise information required to construct the three-dimensional (3D) surface. Modern technology has covered the gaps by developing a range of sensors and algorithms for data analysis on 3D coastal erosion and accretion changes throughout the beach topography, which has become crucial. The ultimate goal is to develop a cost-effective mapping procedure for an area that includes a high-resolution mapping system that abstracts evidence of coastal areas for long-term 2D change rates from 1953 to 2020 and short-term 3D volumetric changes of sand erosion and accretion rates from 2018 to 2020. This would be accomplished through Unmanned Aircraft Systems Mapping, which employs digital photogrammetry principles including comprehensive geospatial information systems spatial data and linear regression analysis to investigate massive quantities of data. The feasibility of this methodology was applied to the Jupiter Inlet Lighthouse Outstanding Natural Area in Jupiter, Florida, a study coastal area that had receded almost 27 m in the last 67 years. The outcomes of a short-term coastal analysis quantify the amount of soil erosion and accretion that occurred along the shore over two years as a result of rising sea levels. The long-term change analysis indicates how much sand was eroded each year as a result of several variables affecting shoreline changes, which will help the land management team in developing new sustainable policies for future coastal environmental conservation.

© 2022 Society of Photo-Optical Instrumentation Engineers (SPIE)
Pandiyan Kesavan, Sudhagar Nagarajan, and Peter De Witt "Data-driven approach for 2D shoreline, and 3D volumetric change detection analysis: a case study for Jupiter inlet lighthouse outstanding natural area," Journal of Applied Remote Sensing 16(3), 034509 (26 July 2022). https://doi.org/10.1117/1.JRS.16.034509
Received: 21 December 2021; Accepted: 5 July 2022; Published: 26 July 2022
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KEYWORDS
3D image processing

Jupiter

Clouds

RGB color model

3D modeling

Associative arrays

Image processing

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