Shoreline Change Analysis of Pontang Cape of Serang Regency of Banten Province

Coastal areas, being vulnerable to environmental problems, have one of the most frequent problems which are the change in the shorelines. Shoreline changes, namely abrasions, can cause problems such as land degradations or loss of land in a coastal zone. This problem occurs in many areas, one of which is Pontang Cape. This study aims to determine the distance and rate of shoreline changes that occured in the Cape and its surroundings, as well as explaining the analysis points based on similar studies that had been conducted. This research used ArcMap software and Digital Shoreline Analysis System (DSAS) toolset to determine the distance and rate of shoreline changes for 19 years (1999-2018). Based on the results, there were two shoreline segments where different phenomena of shoreline change took place, namely Banten Bay (accretion) and Pontang Cape-Lontar (abrasion). The most likely causes of changes in the shorelines are sediment runoffs from rivers that lead to bay and sediment transports that affect Banten Bay accretions, while sea sand mining and conversions of mangrove swamps into fishery ponds are factors affecting abrasions in Pontang Cape.Keywords: Abrasion, Accretion, Pontang Cape, Banten Bay, DSAS

THE DEVELOPMENT AND RESEARCH TREND OF USING DSAS TOOL FOR SHORELINE CHANGE ANALYSIS: A SCIENTOMETRIC ANALYSIS

The sensitivity of research on shoreline monitoring of coastal erosion is justified due to high density population, climate changes impacts, and intensified development, which are squeezing the ecosystem of coastal zones around the world. The budding fields of optical remote sensing such source medium and high-resolution satellite imagery in conjunction with avenue programming of Digital Shoreline Analysis System (DSAS) are widely used extended tools for analyzing the rate of coastal erosion and deposition. Although, there is a geometric growth in the research published documents in the last decades after the start of DSAS in 1990, but its broad insight into global peer groups, its scientometrics, pattern and trends in research activities in monitoring coastal erosion or shoreline change is missing. To breach this gap, 99 bibliographic records published in the Web of Science core collection for the period of 1994–2019 were analyzed using the VOSviewer software. Further, the analysis about global insight of research activities using DSAS in shoreline change analysis focused on (i) general scientometric characteristics of published output, (ii) experts in research themes and their cooperation, (iii) publishable journal list, (iv) institutional distribution and international collaboration, and (v) potential hotspot areas. This systematic analysis of the theme, graphically using rigorous scientmetric tools, will help coastal researchers to visualize the current research trends and prospective guideline for future research. The output of the present study will provide a robust road map to early carrier researchers for their advance inquiry in these fields in coming days.

Contemporary challenges for Shoreline Change Analysis

<p>Shoreline change analysis has been deployed across a range of spatio-temporal scales. Accordingly, shoreline change studies have sought to capture shoreline dynamics at a variety of scales, ranging from the local impacts of individual storms to global trends measured over multiple decades. The scale at which we can approach the issue of shoreline change is, to a large extent, determined by the availability of data over time and space. With existing threats from the interactions between accelerated sea level rise, changing storminess and human intervention, shoreline change analysis has never been more relevant or challenging. Historic, centennial-scale shoreline change analysis relies on historic maps where there is normally just a single proxy indicator for consistent shoreline position; the mean water level of ordinary tides on UK Ordnance Survey maps, for example. Occasionally where there are specific coastal landforms that can be mapped, there might be a second proxy such as cliff top position. Shoreline change rates can be determined by extracting these proxies from sequential map surveys, provided the survey dates (ie: not the map publication date) are known.</p><p> </p><p>Shoreline change quantification for more recent decadal-scale periods has been greatly enhanced by increased data availability. This is exemplified by analyses that use widespread coverage available from aerial photographs (past 3 decades). Even more recently on near-annual scales Light Detection and Ranging (LiDAR) data are becoming the norm for capturing storm impacts and shoreline change, enabling volumetric assessments of change in addition to the more traditional linear approaches. LiDAR is enhanced by ground survey Real Time Kinematic (RTK) Instrumentation that can be timed to coincide with storms. As the frequency of dataset capture has increased so has the spatial scale of coverage. Hence the latest shoreline change assessments are global in scale and use Landsat images to focus on hotspots of shoreline change (advance as well as retreat) over the past 30 years. Considering all scales together raises three central questions for shoreline change analysis and these are addressed in this paper.</p><p> </p><p>Firstly, what methodological approach is most suitable for delimiting shorelines and generating the underpinning digitised shorelines for shoreline change assessment?</p><p>Secondly, what lessons can be learnt from using an approach that combines both proxy-based (visually discernible signatures) and datum-based (related to a particular water level) shorelines that change differentially with respect to different process-drivers?</p><p>Thirdly, given the current state-of-the-art around data availability, what is the most appropriate scale to approach shoreline change assessments?</p>