Mapping and Electronic Publishing of Shoreline Changes using UAV Remote Sensing and GIS

Shenbagaraj, N.; Kumar, K. Senthil; Rasheed, Anjum; Leostalin, J.; Kumar, Manoj

doi:10.1007/s12524-020-01287-1

Cited by 12 publications

(5 citation statements)

References 13 publications

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“…RS images can be integrated with LiDAR data to improve geo-positioning accuracy in metropolitan areas [36,37]. Aerial images, 3D laser scans, and GIS have been integrated into inundation dynamics, shoreline changes, and other domains [38][39][40] in order to enrich the data representation of the urban context. Moreover, photogrammetry technologies have been applied to produce 3D models of streets, buildings, and city details [41,42].…”

Section: Related Studiesmentioning

confidence: 99%

Nested Fabric Adaptation to New Urban Heritage Development

Shih

Qiu

2023

Remote Sensing

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Old urban reform usually reactivates the urban fabric in a new era of sustainable development. However, what remains of the former fabric and how it interacts with the new one often inspires curiosity. How the old residents adapt their lives to the new layout should be explored qualitatively and quantitatively. This research aimed to assess the old and new fabrics in the downtown area of Keelung, Taiwan, by considering the interactions between truncated layout, proportion, and infill orientation in the mature and immature interfaces. According to the historical reform map made in 1907, the newly constructed area occupied the old constructed area in seven downtown blocks. On average, the area composed of new buildings ranged from 135.60% to 239.20% of the old area, and the average volume of the buildings reached a maximum of 41.72 m when compared to the old buildings in place prior to the reform. It seems that the new fabric purposefully maintained the old temples at the centers of the blocks. However, the old alleys, which still remain within these blocks, have been significantly overloaded with services and have become auxiliary utility spaces for the in-block residences. With regard to the part of the fabric that was truncated or reoriented by new streets, the modification could also be easily found on the second skin. A physical model analysis used a UAV 3D cloud model and QGIS® to verify the axes, hierarchies, entrances, open spaces, and corners in the commission store block and temple blocks. We found that the 3D point model and historical maps presented a convincing explanation of the evolved fabric from the past to the present. The stepwise segmentation visualizes the enclosed block inside a block on the historical maps and according to the present sections. We found that new roles for old alleys have evolved behind the new fabric.

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Section: Related Studiesmentioning

confidence: 99%

Nested Fabric Adaptation to New Urban Heritage Development

Shih

Qiu

2023

Remote Sensing

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“…For instance, Gonçalves (2019) utilized a digital surface model derived from airborne LiDAR and low-cost unmanned aerial systems (UAS) to track shoreline changes on Furadouro Beach in Portugal from 2011 to 2015 [15]. The study by Shenbagaraj et al (2021) utilized unmanned aerial vehicles (UAVs) for remote sensing to monitor shoreline changes in Cuddalore District, Tamil Nadu, India, from 1989 to 2017 [23]. Amodio utilized digital elevation model (DEM) data from unmanned aerial vehicles (UAVs) to assess changes in the terrain morphology during the summer of 2019 and 2020 for the coastal system along the Central Adriatic coastline [3].…”

Section: Introductionmentioning

confidence: 99%

Evaluating and predicting coastal shoreline changes in the Doi Duong - Phan Thiet beach area by remote sensing and GIS technology

Thi My,

Thi,

Thuy

et al. 2024

IOP Conf. Ser.: Earth Environ. Sci.

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Assessing the shoreline variability is paramount in understanding the erosion and coastal accretion processes. The potential impact of erosion on coastal communities, particularly in coastal regions, amplifies the vulnerability to coastal disasters. In this study, Landsat satellite imagery captured from 1990 to 2022 was utilized, in conjunction with Geographic Information System (GIS), to scrutinize alterations in the shoreline of Doi Duong Beach - Phan Thiet. The satellite images were independently processed using aspect-ratio methods and thresholding techniques to determine the prevailing condition of the coastline. The rate of shoreline change was quantified using the DSAS tool. The investigation’s findings reveal a dynamic interplay between erosion and accretion, with accretion dominance explicitly evident within the areas surrounding the Ca Ty - Phu Hai river mouth. The average annual shoreline change rate is 27.1 m/yr for the Ca Ty River mouth and 16.5 m/yr for the Phu Hai River mouth. The most significant disparity between the recorded coastline in 1990 and 2022 measures 868 m. Additionally, the projections for the coastline until 2032 indicate that accretion remains the dominant process. This research shows that combining geospatial techniques and numerical models is a reliable way to study shoreline change trends.

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“…Gonçalves et al (2019) [60] used digital surface models (DSM) resulting from airborne LiDAR and low cost UAS (unmanned aerial systems) to monitor shoreline changes from 2011 to 2015 on Furadouro beach in the northern part of Portugal. Shenbagaraj et al (2021) [61] used an unmanned aerial vehicle (UAV) remote sensing to monitor shoreline changes between 1989 and 2017 for the Cuddalore District, Tamil Nadu, India. Amodio et al (2022) [62] established a method for using DEMs based on UAV-derived data for assessing the short-term morphologicaltopographic changes of a coastal system along a stretch of beach affected by erosion, located along the Central Adriatic coast during the summers of 2019 and 2020.…”

Section: Introductionmentioning

confidence: 99%

Historical Trend Analysis and Forecasting of Shoreline Change at the Nile Delta Using RS Data and GIS with the DSAS Tool

et al. 2023

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Coastal areas are increasingly endangered by climate change and associated sea level rise, which could have serious consequences, such as shoreline erosion and coastal city submergence. The current study aims to conduct a historical trend analysis (HTA) and predict the shoreline changes of the Nile Delta coasts. The Digital Shoreline Analysis System (DSAS) software, with the GIS environment, is used for monitoring the shoreline changes using a number of statistical methods (SCE, NSM, EPR, WLR and LRR). Satellite images from 1974 to 2022 were collected and geometrically corrected using supervised classification to detect the shoreline change of the Nile Delta. The GIS was used for detecting and monitoring changes in the shoreline, as well as forecasting future changes in the shoreline for the next 10 and 20 years (2033–2043). The critical sections of the Nile Delta were identified, and a time series analysis of shoreline changes was conducted. For each section, linear equations were established to predict probable changes in the shoreline. Between 1974 and 2022, the shoreline of the Nile Delta moved inland in different directions due to coastal erosion, and predictions indicate that this erosion will continue until both 2033 and 2043, particularly affecting the Rosetta and Damietta sections. The erosion rate ranged between 30–60 and 10–25 m/year at Rosetta and Damietta, respectively, but at Manzala, it ranged between 8–15 m/year. Continued erosion of the Nile Delta shoreline could have severe consequences that could affect the inhabitants, economy, buildings, roads, railways, and ports. These areas need an integrated coastal management strategy which incorporates increasing consciousness, urban development, and the implementation of rules and adaptation plans. The results of the current study and forecasting the shoreline change could help in protecting such areas.

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Mapping and Electronic Publishing of Shoreline Changes using UAV Remote Sensing and GIS

Cited by 12 publications

References 13 publications

Nested Fabric Adaptation to New Urban Heritage Development

Nested Fabric Adaptation to New Urban Heritage Development

Evaluating and predicting coastal shoreline changes in the Doi Duong - Phan Thiet beach area by remote sensing and GIS technology

Historical Trend Analysis and Forecasting of Shoreline Change at the Nile Delta Using RS Data and GIS with the DSAS Tool

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