Linear Regression Rate Research Articles

Automatic shoreline extraction and change detection: A study on the southeast coast of Bangladesh

One of the multifaceted features of the Earth's surface is the shoreline, which is always changing and has enhanced economic and environmental values. This paper highlights the shoreline of Bangladesh's southeast coast from 1980 to 2020 with a 10-year interval to automatically extract the shoreline and the changes in coastline position due to accretion and erosion. Threshold, Sobel, Prewitt, Canny and Robert generic edge detection algorithms are used for automatic shoreline extraction, including canny's performance in accurately detecting the coastline. The Digital Shoreline Analysis System (DSAS) is carried out using Net Shoreline Movement (NSM), End Point Rate (EPR), and Linear Regression Rate (LRR) to statistically measure shoreline changes. The findings suggest that in terms of accretion and erosion, the shoreline is dynamic, but overall accretion is dominated rather than erosion. Because of both natural processes and anthropogenic interventions, the coastline in this area has changed increasingly. The result shows that maximum erosions reached between 2010 and 2020 are 2673.64 m for NSM and 284.49 m/yr for EPR, whereas the maximum accretions are 4689.4 m for NSM and 469.58 m/yr for EPR between 1980 and 1990. LRR tracks coastline variation over a 40-year period in which 162.91 m/yr and 45.91 m/yr, respectively, are the highest accretion and erosion observed. It is anticipated that the outcome of this study will help to understand the possible risks of future changes in the coastline that will require the country to establish planning and management strategies for its very significant southeast shoreline.

Coastal land use and shoreline evolution along the Nador lagoon Coast in Morocco

The coastal zone, a highly dynamic and complex environment, has important ecological and jurisdictional implications for governments and coastal managers. Based on the CORINE Land Cover classification system, this paper examined the effects of land use and land cover change (LULC) on the coastlines' dynamics along the ∼24 km barrier island of Nador lagoon on the Mediterranean coast of Morocco during a period of 62 years (1954–2016). The study utilized high-resolution orthoimages in the geographic information system (GIS) environment to characterize coastline evolution and LULC changes. The evolution of the coastline was assessed using a GIS tool, in particular the Digital Shoreline Analysis System (DSAS). The net rates of coastline change were calculated by using statistical methods: the End Point Rate (EPR) and the Linear Regression Rate (LRR). Results concerning the LULC changes showed that agricultural area and beach/dune classes decreased over the entire study period (62 years) by 11.14% and 28.45%, respectively. Urban fabric, shrub, forest, and saltmarsh/peat bog classes increased during the 62 years of evaluation by 2.69%, 19.92%, 16.77%, and 0.19%, respectively. Results regarding coastal analysis indicated that the accretion and erosion processes along the barrier island of the Nador lagoon (∼24km) were observed at 45% (10.6 km) and 55% (12.8 km) of the coastline, respectively. The beaches of Oulad Zehra and Oulad Aissa were characterized by erosion (−0.58 m/yr to −0.57 m/yr respectively), while accretion was observed on the beaches of Boukana and Kariat Arkmane at rates of +2.15 m/yr and +0.82 m/yr, respectively. This study highlighted that natural and anthropogenic processes have a strong influence on the erosion/accretion trends identified along the barrier island of Nador lagoon. The changes in LULC have affected the barrier island of the lagoon in two different forms: (1) a significant spatial conversion due to dune reforestation and (2) a fundamental spatial modification that affects the sea-lagoon connection (inlet) and the construction of new hard engineering structures.

Evolution of southern Mexican Pacific coastline: Responses to meteo-oceanographic and physiographic conditions

The coast of Oaxaca, along the southern Mexican Pacific coastline, is home to diverse ecosystems, which undergoes significant erosion and accretion due to natural and anthropogenic influences. This study aims in analysing the historical shoreline variations and predicting the future changes for better coastal management plans. In order to study the long-term variations in shoreline, Landsat time-series satellite imageries between 1973 and 2020 were evaluated. Overall, the results indicate that the coast is highly dominated by accretion (74%) process, with the most significant changes occurring at the estuarine areas and beaches. Linear Regression Rate (LRR) and Weighted Linear Regression (WLR) methods showed mean variations at rates of 1.2±2.5 and 0.4±2.5 m/yr for the long-term period. The analysis of seven short-term periods (for every 5 years between 1986–2020) identified the maximum mean erosion of −20.6 m during 2005–2010 and accretion of 18.7 m during 2000–2005. However, the forecasted rate of change for the period 2030 and 2040 using End Point Rate (EPR) statistics revealed that the northern region would continue to move seaward at a rate of +0.26 m/yr and the coastline of southern region would move landward at a possible rate of −0.45 m/yr. The natural factors such as rainfall, river discharge, hurricane, and wave dynamics are the main drivers of shoreline changes along the estuarine and wetland areas. Contrarily, the anthropogenic factors such as breakwaters and urbanization are responsible for coastline dynamics along the beaches and ports. Henceforth, the estuarine region, lagoon openings, and tourist beaches require utmost attention as the sediment flow in these regions are not monitored constantly.

Geomorphologic Impact of Construction of Breakwaters at Ponnani Fishery Harbour in Kerala

Coast belonging to one particular stretch happens to be versatile because of its dynamicity. This dynamicity is attributed to both natural and anthropogenic activities. Hence, it is important to monitor any fragile coastal stretch’s dynamicity in a temporal basis. In the present study, an attempt is made to analyse the shoreline changes using Digital Shoreline Analysis System (DSAS), by calculating Linear Regression Rate (LRR), in response to the construction of two breakwaters at Ponnani which is a major fish landing centre in Malappuram district of Kerala state in India. Shorelines were extracted from field data, satellite imageries, LANDSAT (1979-2002) and Google earth (2010-2016). From the detailed analyses, before the construction of breakwaters, it is inferred that erosion at the rate of 1.5m/yr and 5.3m/yr was observed on north and south sides of Ponnani estuary respectively. But after construction, an accretion at the rate of 3m/yr on either side of estuary is observed.

Coastal system evolution along the southeastern Caspian Sea coast using satellite image analysis: response to the sea level fall during 1994–2015

The southeastern segment of the Caspian Sea (CS) along the Iranian coast, which has a very gentle inner shelf slope, underwent rapid beach evolution in response to water level changes. Based on satellite altimetry data, the CS basin has experienced an accelerated water level fall drop in recent years, leading to an increase in the rate of shoreline changes. The shoreline dynamics and morphodynamics of the Amirabad coastal zone, Gorgan Bay, Miankaleh Spit, and Gomishan Lagoon are evaluated here to determine morphological changes of the study area. Landsat-TM/ETM+/OLI moderate spatial resolution products were acquired at unequal intervals between 1994 and 2015 to monitor the coastal changes using Geographic Information System (GIS) tools. The Digital Shoreline Analysis System (DSAS), a GIS software extension, has been used for estimation of the shoreline rate of change through several approaches, including End Point Rate (EPR), Linear Regression Rate (LRR), and Weighted Linear Regression (WLR). The results show that both Gorgan Bay and Gomishan Lagoon have significantly decreased in size during recent years, mainly due to the fall of the CS water level. Results also show that water level drop of the CS, along with net eastward littoral transport, resulted in the growing of the Miankaleh Spit. Further analysis based on the wave climate in the southeast CS and net estimated longshore sediment transport indicates that the littoral drift contributed to ~ 6% of the total annual elongation of the Miankaleh Spit during the study period.

Evaluation of shoreline change using multitemporal satellite images

Coastal areas are vulnerable to change because, in this region, many human activities and natural influences change. These activities can result in changes in the existing coastline. Moreover, the city of Surabaya has a reasonably long coastline. This study calculated the speed of shoreline change using remote sensing technology of SPOT 6 and SPOT 7 high- resolution satellite imagery from 2015 to 2019. Calculation of shoreline change speed is assisted by the application of the Digital Shoreline Analysis System (DSAS) using several methods, namely Shoreline Change Envelope (SCE), Net Shoreline Movement (NSM), End Point Rate (EPR), and Linear Regression Rate (LRR). Based on data processing and analysis, the longest coastline of Surabaya City was found in 2015 with a length of 69.605 km, and the shortest coastline was in 2019 with a length of 65.759 km. The maximum speed of Surabaya shoreline changes can be identified by using the SCE method (956.590 m), the NSM method (+584.722 m), the EPR (+148.725 m per year), and the LRR (+154.386 m per year). Also, an analysis of land area changes during the 20152019 period resulted in the Kalisari Village experiencing the most significant accretion of 358073.62 m2, while in Keputih Village abrasion of 30189.72 m2.

Remote Sensing of Narrowing Barrier Islands along the Coast of Pakistan over Past 30 Years

Barrier islands (BIs) are the first line of defense against the sea/wave actions in coastal areas, and assessing their stability is crucial in the context of effective coastal planning. Therefore, this study evaluates the spatial–temporal shoreline changes of the BIs in Pakistan over the past three decades (1989–2018). Satellite data from Landsat missions are used to delineate the shorelines of 19 BIs in Pakistan. After delineating the shorelines from satellite observations, two well-known statistical methods (i.e., end point rate (EPR) and linear regression rate (LRR)) are used to capture the localized changes in the BIs. The results ascertain that nearly all of the BIs have experienced noteworthy erosion during the past three decades. While the mean erosion over all the BIs during the study period is estimated to be >6 m/y, significant spatial heterogeneities among the individual BIs exist. The interdecadal comparison indicates that the highest mean erosion of the BIs occurred during the period 1989–1999 (13.03 ± 0.62 m/y), which gradually reduced over the preceding decades (i.e., 7.76 ± 0.62 m/y during the period 1999–2009 and 3.8 ± 0.7 m/y during the period 2009–2018). Nevertheless, ~65% of the total BIs experienced high erosion (>2 m/y), ~15% experienced moderate (<2 m/y), and ~20% experienced low erosion (<1 m/y) during the period 1989-2018. This situation implies that while ~65% of these BIs need immediate interventions from the concerned authorities, the 15% BIs with moderate erosion might experience high erosion in the wake of rising sea levels and decreasing sediment influx in the near future without proper measures. This depletion of the BIs might not only affect Pakistan but also have regional consequences due to their various services.

The analysis of shoreline change dynamics and future predictions using automated spatial techniques: Case of El-Omayed on the Mediterranean coast of Egypt

The study area belongs to the coast of El-Omayed Biosphere Reserve on the western Mediterranean coast of Egypt. This work represents one of the limited studies analyzing historical change rates of its shoreline and predicting future changes to identify the parts requiring management interventions. The shorelines of five dates covering a period of 34 years between 1984 and 2018 were extracted from five Level-2 Landsat images. The Water Index (WI2015) provided the best extraction results of three common water indices when compared with a reference shoreline digitized from high resolution Google Earth imagery. End Point Rate (EPR) and Linear Regression Rate (LRR) were automatically calculated to determine shoreline change rates. The two methods provided very similar results (R2 exceeding 0.98). EPR was used for evaluating historical changes (1984–2018) and predicting future shoreline positions (2030 and 2050). The results showed that the shoreline exhibited alternation between erosion and accretion with varied rates. The average erosion rate is −1.67 m/year and highest accretion is 1.88 m/year. These changes result basically from longshore sediment transport generated by the waves and currents approaching mostly from NW quadrant. The western parts are also affected by the protective structures supporting the intensive touristic activities characterizing the study area. The future trends of predicted shorelines showed that urgent and long-term protective measures are required to avoid the partial and complete loss of the several parts of its beaches jeopardizing the sustainability of the tourism activities in the study area.

Effect of disturbed river sediment supply on shoreline configuration: A case study

ABSTRACT The magnitude of river sediment supply and its distribution play a significant role in coastal sediment dynamics, especially in erosion and deposition. Due to the construction of the dam, obstruction in the natural flow of water occurs, and part of the sediment is trapped. In the present study, the Kali river catchment and its river-mouth at Karwar, Devbagh, and Ravindranath Tagore beaches are considered as the study area, to assess the impact of dams on coastal processes. Landsat data for 42 years, from 1975 to 2017, were collected and analyzed using DSAS, an ArcGIS extension. The sediment yield estimated at the Kali river basin outlet, without the dam is 4.19 t/ha/yr and with the dam, it is estimated to be 1.42 t/ha/yr. Similarly, for the Aghanashini river basin outlet, the sediment yield was found to be 4.58 t/hr/yr. From the results of shoreline analysis, it is found that after the construction of the dam, Devbagh beach is under erosion at the rate of −0.93 m/yr End Point Rate (EPR) and −0.47 m/yr Linear Regression Rate (LRR). Ravindranath Tagore beach also has undergone erosion, which is −0.75 m/yr (EPR) and −0.97 m/yr (LRR). Further, both the beaches have been changed to the erosion zone.

Dynamic change and spatial analysis of Great Lakes in China based on Hydroweb and Landsat data

Lakes are crucial elements of the Earth’s hydrological cycle and play an important role in the regulation of the Earth’s material exchange and energy transfer. The expansion or contraction of lakes has an important influence on water use in agricultural and biogeochemical activities. It is of great significance to establish a long time series dataset of changes in the lake area, water level, and lake volume. Based on Landsat data and Hydroweb data, this study firstly established a long time series dataset of the lake area, water level, and lake volume change of China’s great lakes from 1978 to 2018. Then combined with DSAS, net shoreline movement (NSM), and linear regression rate (LRR) of the growth type lakes and the reduction type lakes were calculated, and quantitatively described the lake area change and spatial variation of lake shoreline. Finally, meteorological factors such as precipitation, evaporation, and temperature, as well as the influence of land use factors on lake area change, were analyzed. The results showed that Namtso, Selinco, Zhari Namco, Qinghai Lake, Xingkai Lake, and Taihu Lake belong to the growth type lakesl Hongze Lake, Poyang Lake, and Dongting Lake belong to the non-obvious change type lakes; and Bosten Lake and Hulun Lake belong to the reduction type lakes. Hongze Lake and Poyang Lake were greatly affected by precipitation; Xingkai Lake, Selinco, and Zhari Namco were greatly affected by evaporation and temperature. The impact of land use on lakes was mainly reflected in the following aspects: fishery breeding activities along the lakes, agricultural production activities of cultivated land around the lakes, human activities of construction land, and industrial activities of industrial land. Hydroweb/Landsat Data combined with DSAS can effectively conduct spatial analysis of changes in the lake area and provide valuable information for environmental protection of lakes in China.

Analysis of long- and short-term shoreline change dynamics: A study case of João Pessoa city in Brazil

The coastal area of João Pessoa city, Paraíba, Brazil, is densely populated and has a large flow of trade and services. More recently, this region has been suffering from the advance of the sea, which has caused changes in the shoreline and caused a decrease in the beach area and damage to various urban facilities. Thus, the spatiotemporal changes of the short- and long-term characteristics of the shoreline of João Pessoa city over the past 34 years (1985–2019) were calculated and the forcing mechanisms responsible for the shoreline changes were analyzed. Remote sensing data (Landsat 5-TM and 8-OLI) and statistical techniques, such as endpoint rate (EPR), linear regression rate (LRR) and weighted linear regression (WLR), using Digital Shoreline Analysis System (DSAS), were used. In this study, 351 transects ranging from ~1.1 km to ~6 km were analyzed within four zones (Zones I to IV), and the main controlling factors that influence the shoreline changes in these zones, such as sea level, tidal range, wave height, beach morphology and ocean currents, were discussed. The long-term change from 1985 to 2019 showed primarily accretion on the shoreline of João Pessoa city, with the rate of 0.55 m/year (WLR method); 282 transects showed accretion. The results showed that Zone-I, which was located in the south of the study area, was the only zone that primarily recorded erosion from 1985 to 2019, with a mean rate of −0.23 m/year according to the WLR method. According to the short-term shoreline change analysis, a cyclical pattern of erosion was observed in the 1985–1990, 1993–1999, 2005–2011 and 2014–2019 periods, and accretion was observed in the 1990–1993, 1999–2005 and 2011–2014 periods. It was inferred that the patterns of all analyzed zones were similar, i.e., when majority accretion was detected within a zone, the other zones also recorded accretion, except for during the period from 2014 to 2019, when Zone-I showed different behavior. Finally, the long- and short-term analyses showed that the coastal area of João Pessoa city is influenced by various forcing mechanism responsible for the shoreline changes.

Shoreline Change and its Impact on Land use Pattern and Vice Versa – A Critical Analysis in and Around Digha Area between 2000 and 2018 using Geospatial Techniques

The shoreline is a very unpredictable, uncertain, and forever changing landscape for any coastal process. Due to erosional and accretional activities, the shoreline has continuously fluctuated with the continual process of waves and tides. Shore boundaries are determined by the shoreline at its furthest towards the sea (low tide) and extreme towards land (high tide). The present research aimed to identify the temporal alterations of shoreline and changes in land-cover between the areas of Rasulpur to Subarnarekha estuary, east coast of India with 70.04 km length of shoreline. An area amounting to 143sq.km had been selected for showing the land-cover changing and this area had witnessed the rapid growth of population and increasing industrial activities causing an unsurpassable impact on the environment. The present study used three multi dated imageries for land use/ land cover (LULC) map and seven multi-resolution satellite images were applied to estimate the long-term shoreline change rate by dividing the coastal area into three “littoral zones” (LZ). The Digital shoreline analysis system (DSAS) was applied to identify the shoreline change rate of the year 2000 to 2018. Several statistical methods, linear regression rate (LRR), net shoreline movement (NSM), End Point Rate (EPR) were used to find out the erosion and accretion rate. The result showed that maximum erosion had been found in LZ III, rate of -2.22 m/year. Maximum accretion had been identified in LZ I, at the rate of 35.5 m/year. The LULC showed that maximum vegetation area had been decreased in the year of 2010 (14.21sq.km) but 38.96sq.km vegetation area had increased in 2018. The prominent increase had been identified in built up and shallow water. Built up had been expanded from 25.59sq.km (2000) to 41.26sq.km (2018). Shallow water was increased from 5.53sq.km (2000) to 18.90sq.km (2018). Sand and soil showed a decreasing pattern from 2000 – 2018. The outcome acquired from the present study will play a significant role to estimate the shoreline migration rate and will be helpful for sustainable land use management. The shoreline change rate will be also useful for coastal planners to adopt mitigation measures.

A DSAS-based study of central shoreline change in Jiangsu over 45 years

A large-scale sand ridge group is distributed in the central Jiangsu coastal area, and a deposition muddy sea bank was developed in the nearshore area. Quantitative monitoring of coastline changes is of great significance for tidal beach development and protection. The shorelines of the central coast of Jiangsu within six periods (1973–2018) were extracted in this study, and their length changes over the years were analyzed. The Digital Shoreline Analysis System (DSAS) was employed to generate a cross section perpendicular to the baseline and calculate the linear regression rate (LRR) of the shoreline, changes in end point rate (EPR), and net shoreline movement (NSM), based on which the shoreline change features were analyzed. The DSAS results indicated that the shorelines in the study area maintained fluctuating growth and presented a continuous advancing trend towards the sea. From the changes in shoreline evolution distance during 1973–2018, the advancing shorelines in the study area accounted for over 50% of the total shorelines and presented first rising and then declining trends with the period of 2003–2013 taken as the time boundary. The average shoreline change rate was 207 m/year, and the periods with the highest change degrees were 1983–1993 and 1993–2013. The shoreline change tended to be stable during 2013–2018, and only a few estuaries and ports underwent obvious erosion and sedimentation.

Assessment of Coringa Mangrove shoreline migration using geospatial techniques

ABSTRACT Coringa Mangroves in the Kakinada Bay have evolved as the second-largest mangroves in the East Coast of India over the last century. The Coringa Mangrove shoreline has accreted considerably in the past decades as observed from the satellite imageries, adding value to the natural biodiversity of flora and fauna. This study is focused on quantifying the long term changes of Coringa mangrove shoreline using the Landsat imageries for years 1977, 1988, 2000, and 2013 using the Digital Shoreline Analysis System. For a mangrove shoreline length of 20.5 km, 41 transects were cast at an interval of 500 m for calculating the change and their migration distance using three statistical methods, namely End Point Rate (EPR), Net Shoreline Movement (NSM) and Linear Regression Rate (LRR). Results showed that there was considerable growth of mangroves in the bay leading to the seaward migration of the mangrove shoreline from the year 1977–2013. The study observed the difference in the mangrove shoreline migration dynamics in the South-eastern (near the bottom of the spit) and the western part of the Kakinada Bay. The calculated average degradation rate due to erosion is −5.19 m.yr−1 and the average accretion rate leading to their growth is 14.83 m.yr−1 for all transects of the 20.5 km mangrove shoreline stretch during this period. The results hold importance as they help in identifying the regions prone to mangrove degradation and enable management planning for the protection of the eroding stretch of the mangrove shoreline.

Shoreline changes and its impact on the mangrove ecosystems of some islands of Indian Sundarbans, North-East coast of India

This study aims to analyse the shoreline oscillations of three estuarine Islands in Sundarban delta and its impact on mangrove forests around the Islands. Six multi-temporal Landsat images spanning 42 years (1975–2017) have been used in the study. Band ratio was computed to discriminate the water line from the land, which was later digitized. Digital shoreline analysis system (DSAS) was employed for estimation and analysis of the shorelines changes by End point rate (EPR) model and Linear regression rate (LRR) model after laying transects offshore of the baseline. Sea level and topography of the islands have also been analyzed. To assess the mangrove health, time series Normalized Differential Vegetation Index (NDVI) analysis has been performed using the Mann Kendall Tau statistics and Sen’s slope. Mangrove degradation maps were produced from the data and combined with evidences collected from field works. The results point to a very dynamic shoreline ensuing in erosion of mangrove forests while some areas do show encouraging trends due to sustained accretion especially in the southern and eastern parts. Overall erosion is higher than accretion in the Islands. Results show that NDVI has been decreasing along patches that are near to erosion hotspots irrespective of climatic trends. Thus it can be concluded that mangrove forests are under severe stress due to shoreline ingression and sea level rise and not climatic alterations. Going forward this work could provide significant information on the nature of shoreline changes and could assist in sustainable development for Sundarban biodiversity niche management.

Analysis of shoreline changes in Vishakhapatnam coastal tract of Andhra Pradesh, India: an application of digital shoreline analysis system (DSAS)

ABSTRACT Coastline or Shoreline calculation is one of the important factors in the finding of coastal accretion and erosion and the study of coastal morphodynamic. Coastal erosion is a tentative hazard for communities especially in coastal areas as it is extremely susceptible to increasing coastal disasters. The study has been conducted along the coast of Vishakhapatnam district, Andhra Pradesh, India with the help of multi-temporal satellite images of 1991 2001, 2011 and 2018. The continuing coastal erosion and accretion rates have been calculated using the Digital Shoreline Analysis System (DSAS). Linear regression rate (LRR), End Point Rate (EPR) and Weighted Linear Regression (WLR) are used for calculating shoreline change rate. Based on calculations the district shoreline has been classified into five categories as high and low erosion, no change and high and low accretion. Out of 135 km, high erosion occupied 5.8 km of coast followed by moderate or low erosion 46.2 km. Almost 34.7 km coastal length showed little or no change. Moderate accretion is found along 30.5 km whereas high accretion trend found around 17.8 km. The outcome of shows that erosion is prevailing in Vishakhapatnam taluk, Ankapalli taluk, Yellamanchili taluk whereas most of the Bhemunipatnam coast is accreting. Natural and manmade activities and phenomena influence the coastal areas in terms of erosion and accretion. The study could be used for further planning and development and also for disaster management authority in the decision-making process in the study area.

Using landsat satellite images for assessing riverbank changes in the Mekong and Bassac rivers in the An Giang province

An Giang Province is one of the key economic regions of Mekong Delta and of Vietnam. With the development of urbanization and industrialization, An Giang has been suffering a burden from natural disasters, including salinity intrusion, drought, and riverbank erosion, due to natural and anthropological drivers. Amongst them, riverbank erosion is a key problem of the An Giang province, caused by changes in hydrological and sediment characteristics because of hydropower development and sand exploitation in the upstream part. In this study, we investigated the riverbank changes by using the water extraction index based on the Landsat imagery data. Amongst three extraction indices, such as Normalized Difference Water Index (NDWI), Modified Normalized Water Index (MNDWI), and Automated Water Extraction Index (AWEI), AWEI was identified the suitable index for the study area replied on the assessment of the index performance in extracting the riverbank in the four test sites in An Giang province (An Phu District, Vinh Hoa District, Cho Moi District, and Vam Nao River). Based on that, AWEI was then used for riverbank extraction for the study area in the period 1989-2015. After using the AWEI riverbank extracting method, Linear Regression Rate (LRR) had been applied to estimate the rate of the riverbank changes in the study area. The results stated that the rate of riverbank erosion was high in meandering river segments and upper part of islets, such as Tan Chau (-33m/year), Cho Moi (-36m/year) and Vam Nao (-3.07m/year). Besides analyzing the rate of erosion, this research also discusses some potential reasons as well as protection method to mitigate this problem. This study reveals that it is crucial to take sustainable measures to mitigate erosion in An Giang province.

Assessment of shoreline changes for setback zone establishment from Son Tra (Da Nang city) to Cua Dai (Hoi An city), Vietnam

The most important function of the coastal setback is to minimize damage due to coastal erosion, climate change response, and sea-level rise. There are many directions and methods of researching and assessing coastal changes and coastal erosion. This study presents the results of the shoreline changes in the area from Son Tra (Da Nang City) to Cua Dai (Hoi An City), Central Vietnam based on remote sensing data from 1965 to 2019. Three methods are used to include End Point Ratio (EPR), Linear Regression Rate (LRR), and Weighted Linear Regression (WLR). The results show that the EPR method is effective when calculating the rate of shoreline changes only at two different times. For more objective and reliable calculation, it is necessary to assess the shoreline changes over time. Meanwhile, the LRR method was shown to be superior because all shoreline data were taken into account during the construction of the regression line. However, when there is much shoreline data with different reliability, the WLR method proved more superior because of limited objective errors. The results show that from 1965 to 2019, the coast of the Son Tra - Cua Dai area had quite complicated fluctuations, of which the northern area (Son Tra) tended to accretion, the central area tends to be alternate between accretion and erosion, while the south area (Cua Dai) is strong to very strong erosion. The coast with sudden changes is the Cua Dai area with the shoreline change envelope (SCE) reaching 512m. The results also allow us to divide the coast of the Son Tra - Cua Dai area into 30 segments. They are clustered into 8 groups with different levels of erosion and accretion. This is an important basis for the setback zone establishment in the study area.

Assessment of shoreline changes for setback zone establishment from Son Tra (Da Nang city) to Cua Dai (Hoi An city), Vietnam

The most important function of the coastal setback is to minimize damage due to coastal erosion, climate change response, and sea-level rise. There are many directions and methods of researching and assessing coastal changes and coastal erosion. This study presents the results of the shoreline changes in the area from Son Tra (Da Nang City) to Cua Dai (Hoi An City), Central Vietnam based on remote sensing data from 1965 to 2019. Three methods are used to include End Point Ratio (EPR), Linear Regression Rate (LRR), and Weighted Linear Regression (WLR). The results show that the EPR method is effective when calculating the rate of shoreline changes only at two different times. For more objective and reliable calculation, it is necessary to assess the shoreline changes over time. Meanwhile, the LRR method was shown to be superior because all shoreline data were taken into account during the construction of the regression line. However, when there is much shoreline data with different reliability, the WLR method proved more superior because of limited objective errors. The results show that from 1965 to 2019, the coast of the Son Tra - Cua Dai area had quite complicated fluctuations, of which the northern area (Son Tra) tended to accretion, the central area tends to be alternate between accretion and erosion, while the south area (Cua Dai) is strong to very strong erosion. The coast with sudden changes is the Cua Dai area with the shoreline change envelope (SCE) reaching 512m. The results also allow us to divide the coast of the Son Tra - Cua Dai area into 30 segments. They are clustered into 8 groups with different levels of erosion and accretion. This is an important basis for the setback zone establishment in the study area.

Multi-decadal shoreline change analysis in coast of Thiruchendur Taluk, Thoothukudi district, Tamil Nadu, India, using remote sensing and DSAS techniques

Shoreline position has been forwarding or retrograding due to many factors, among them climate change and human interferences play a major role. The shoreline changes can be analyzed by various methods. In the present study, Linear Regression Rate (LRR) method is applied for the demarcation of rate of shoreline changes along the coast of Thiruchendur Taluk, Thoothukudi district, by using Digital Shoreline Analysis System (DSAS). It is an extension tool in ArcGIS. The length of the coast is 45 km. The coastal zone is further divided into three coastal zones based on their administrative division (panchayat union). The zones are Alwarthirunagiri coast, Thiruchendur coast, and Udankudi coast. These zone divisions are done for detailed mapping. Multi-date of remotely sensed data was used for mapping the details. These data are georeferenced with the UTM projection of WGS1984 and digitized the shorelines with the FCC color image. Transect lines were generated using DSAS tool. The transect lines starting from 752 to 1210 were used for present study to assess the shoreline changes. The tool had generated the LRR Statistic reports on each transect lines for all shorelines. The statistic report has been classified into five classes, viz., high erosion, low erosion, stable, low accretion, and high accretion. Finally, the shoreline has classified with LRR reports. The overall result shows that, low accretion has notied at 36 km (79%), high accretion perceived at 8.7 km (8.7%), and stable has observed in 8.3 km (8.3%), along the coast. Whereas, low erosion was noticed around 1.4 km (3.1%), and no high erosion was noticed along the study area. Thiruchendur and Udankudi coastal zones are mostly perceived low rate of shoreline changes with the rate from 1.02 to 3.96 m/year, happen in 18.9 km and 16.5 km, respectively. But, Alwarthirunagiri coast zone, low rate of erosion is noticed along the 1.4-km length of the shore. The study has concluded that, most of the Thiruchendur Taluk coastal areas are under the low-rate accretion, and the same area is observed as erosion along the coast due to both natural and human activities. Thiruchendur Taluk has major coastal cities, and a large number of people live around the coast. There are numerous natural resources and tourist places around the coast. Therefore, this coastal area shoreline changes studies should be examined.