scholarly journals COASTLINE CHANGE ANALYSIS ON BALI ISLAND USING SENTINEL-1 SATELLITE IMAGERY

2021 ◽  
Vol 18 (1) ◽  
pp. 63
Author(s):  
Suhendra Suhendra ◽  
Christopher Ari Setiawan ◽  
Teja Arief Wibawa ◽  
Berta Berlian Borneo
Keyword(s):  
Satellite Imagery ◽  
Coastal Erosion ◽  
Human Factor ◽  
Change Analysis ◽  
Image Thresholding ◽  
Thresholding Method ◽  
Coastline Change ◽  
Tidal Correction

Bali is well-known as a popular tourism location for both local and foreign tourists. There are nine areas designated for tourism, eight of which are coastal. However, due to coastal erosion, the coastline of Bali is changing every year. The purpose of this study is to determine the changes that took place between 2015 and 2020 using Sentinel-1 satellite imagery. The study was conducted along the coastline of Bali Island at coordinates 08° 53' 35.5648" S, 114° 24' 41.8359" E and 08° 00' 46.7865" S, 115° 44' 17.5928" E. The coastlines were identified using the Otsu image thresholding method and linear tidal correction was performed. The coastline change analysis was made using the transect method. Ground truths were conducted in representative areas where major changes had occurred, either as a result of abrasion or accretion. According to the Sentinel-1 analysis, the coastline changes in Bali during the period 2015 – 2020 were mainly caused by abrasion, apart from at Buleleng, which were generally caused by accretion. Abrasion in Bali is dominantly affected by strong currents and high waves meanwhile accretion which having weak currents and low waves was more affected by human factor such as the construction in this study area.

scholarly journals Coastline change analysis and erosion prediction using satellite images

2018 ◽  
Vol 197 ◽  
pp. 13003 ◽  
Author(s):  
Putu Aryastana ◽  
I Made Ardantha ◽  
Kadek Windy Candrayana
Keyword(s):  
Spatial Resolution ◽  
Coastal Area ◽  
Coastal Erosion ◽  
Central Government ◽  
Morphological Changes ◽  
Average Rate ◽  
Change Analysis ◽  
Erosion Prediction ◽  
Coastline Change ◽  
Spot 5

The study of monitoring and analysis of coastline change and erosion prediction has been widely used satellite imagery. Satellite data that is often used in monitoring studies and analysis of coastline changes are Landsat, Quickbird, Allos, SPOT, IKONOS, etc. The aim of study is to determine an average of coastline change and average of coastal erosion in coastal area of Tabanan Regency, Bali Province, Indonesia by using two kind satellite are SPOT 5 in 2009 has a spatial resolution of 10 m (multispectral) and SPOT 6/7 in 2015 has a spatial resolution 1.5 m. This research contributes to local government and central government as a database in decision making for coastal area management. The result of analysis shows the average of coastline change in Tabanan regency is 13.96 m and the average rate of coastal erosion is 1.99 m/year. The coastline movement or erosion has caused the morphological changes.

scholarly journals Documenting a Century of Coastline Change along Central California and Associated Challenges: From the Qualitative to the Quantitative

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2648 ◽  
Author(s):  
Gary Griggs ◽  
Lida Davar ◽  
Borja G. Reguero
Keyword(s):  
Coastal Erosion ◽  
Shoreline Change ◽  
Initial Step ◽  
Sandy Beaches ◽  
Change Analysis ◽  
The West ◽  
Central California ◽  
Coastline Change ◽  
Coastal Cliffs ◽  
Cliff Retreat

Wave erosion has moved coastal cliffs and bluffs landward over the centuries. Now climate change-induced sea-level rise (SLR) and the changes in wave action are accelerating coastline retreat around the world. Documenting the erosion of cliffed coasts and projecting the rate of coastline retreat under future SLR scenarios are more challenging than historical and future shoreline change studies along low-lying sandy beaches. The objective of this research was to study coastal erosion of the West Cliff Drive area in Santa Cruz along the Central California Coast and identify the challenges in coastline change analysis. We investigated the geological history, geomorphic differences, and documented cliff retreat to assess coastal erosion qualitatively. We also conducted a quantitative assessment of cliff retreat through extracting and analyzing the coastline position at three different times (1953, 1975, and 2018). The results showed that the total retreat of the West Cliff Drive coastline over 65 years ranges from 0.3 to 32 m, and the maximum cliff retreat rate was 0.5 m/year. Geometric errors, the complex profiles of coastal cliffs, and irregularities in the processes of coastal erosion, including the undercutting of the base of the cliff and formation of caves, were some of the identified challenges in documenting historical coastline retreat. These can each increase the uncertainty of calculated retreat rates. Reducing the uncertainties in retreat rates is an essential initial step in projecting cliff and bluff retreat under future SLR more accurately and in developing a practical adaptive management plan to cope with the impacts of coastline change along this highly populated edge.

Image thresholding method based on Fourier spectrum and moment-preserving principle

2010 ◽  
Vol 30 (8) ◽  
pp. 2094-2097 ◽  
Author(s):  
Xin-ming ZHANG ◽  
Shuang LI ◽  
Yan-bin ZHENG ◽  
Hui-yun ZHANG
Keyword(s):  
Fourier Spectrum ◽  
Image Thresholding ◽  
Thresholding Method

Change Detection Within Pipeline ROWs: Environmental Change Analysis Using High Resolution Satellite Imagery

2015 ◽  
Author(s):  
Otto Huisman ◽  
Arash Gharibi
Keyword(s):  
Decision Making ◽  
High Resolution ◽  
Environmental Change ◽  
Satellite Imagery ◽  
Vegetation Index ◽  
Low Cost ◽  
Comparison Method ◽  
Large Area ◽  
Change Analysis ◽  
High Resolution Satellite Images

One of the major concerns for pipeline operators is to efficiently monitor the events happening over the pipeline corridor, or right-of-way (ROW). Monitoring of the ROW is an important part of ensuring the safe and efficient transportation of oil and gas. Events occurring within this zone require rapid assessment and, if necessary, mitigation. These events could be physical intrusions such as encroachment from growing settlements, impact of vegetation, pipeline leakage or geo-environmental hazards. Analysis of satellite imagery can provide an efficient and low cost solution to access and quantify change across the ROW. Examining these events over a periodic interval requires implementation of specific methods that can support the on-going monitoring and decision making practices. In this context, satellite remote sensing images can provide a low cost and efficient solution for monitoring the physical and environmental impacts over the ROW of pipeline system. This paper reports on the development of a methodological approach for environmental change analysis using high resolution satellite images that can help decision making in pipeline systems. Analysis results and maps produced during this work provide an insight into landcover change over the study area and expected to support in on-going pipeline management practices. Two methods, Vegetation index differencing and post classification comparison have been implemented to identify change areas in the Taranaki region of the North Island of New Zealand. Vegetation index differencing with NDVI shows increase or decrease of overall vegetation within the study area. Special focus was given on large area increase and decrease with area threshold value above 0.2 hectare. Detailed analysis of change was conducted with post classification comparison method that uses land cover classification results of year 2010 and 2013. An overall change of 10% has been observed throughout the study area with large area change of approximately 5%. Results obtained from post classification comparison method were further analyzed with 6 focus areas and compared with the existing soil data and rainfall data. The methods adopted during this study are expected to provide a base for environmental change analysis in similar pipeline corridors to support decision making.

A novel statistical image thresholding method

2010 ◽  
Vol 64 (12) ◽  
pp. 1137-1147 ◽  
Author(s):  
Zuoyong Li ◽  
Chuancai Liu ◽  
Guanghai Liu ◽  
Yong Cheng ◽  
Xibei Yang ◽  
...  
Keyword(s):  
Image Thresholding ◽  
Thresholding Method
Sign in / Sign up

Export Citation Format

Share Document