GIS Based Integrated Vulnerability Assessment of Konkan Coastal Stretch between Bankot and Dabhol Creeks, Maharashtra

Binh Thuan coastal zone, nearly 192,9 km shoreline, is well known for residential, recreational areas and minor industries. Shoreline is vulnerable to accelerated sea level rise (SLR) due to its low topography and its high ecological. The present study has been carried out with a view to assess the coastal vulnerability of SLR. Coastal vulnerability map has been built to the calculating results of the place vulnerability index (PVI). The PVI is derived by summing the CVI (coastal vulnerability index) and CSoVl (coastal social vulnerability index) scores. CVI is calculated from nine variables: Geology, geomorphology, coastal slope(%), shoreline change rate (m/yr), mean elevation (m), shoreline direction, mean tidal range (m), wave height (m) and SLR (mm/yr). We use two socioeconomic variables for CSoVI which are socioeconomic variable and relative distance to coast. Results of the vulnerable areas analysis indicate that 120,73 km2 is at very high vulnerable, 84,96 km2 high, 109,23 km2 moderate, 113,99 km2 low and 232,20 km2 very low. The method in this study which combine CVI, CSoVI and PVI together is new protocol of coastal vulnerability assessment for Vietnam coastal zone due to future SLR.

Physical assessment of coastal vulnerability under enhanced land subsidence in Semarang, Indonesia, using multi-sensor satellite data

Coastal vulnerability assessment of India's Purba Medinipur-Balasore coastal stretch: A comparative study using empirical models

The coastal area supports millions of population in terms of livelihood, settlement and social activities across the world and India. The increasing rate of socioeconomic activities made the coasts susceptible to various hazards. Therefore, this study is aimed to examine the coastal vulnerability of Vishakhapatnam Coastal district using remote sensing and geographic information system. To fulfill this objective, six physical indicators, i.e., geomorphology, land use/land cover, coastal slope, shoreline change rate, etc., were prepared using the multi-temporal datasets of 1991, 2001, 2011 and 2018 and mean tidal height has been considered to calculate the coastal vulnerability index (CVI). The indicators selected for the analysis of coastal vulnerability have been integrated using the rank and weighted methods. The shoreline change has been detected using the digital shoreline analysis system (DSAS). Analytical hierarchy process (AHP) has been used for calculating weights of various indices. The CVI values obtained using different indicators are 2.6 (min) and 14.39 (max). Based on the CVI values, the coast is classified as five classes of vulnerability, i.e., very low (0—4.9) covering 42.5 km, low (4.9—7.3) which covers 29.49 km, moderate (7.3—9.6) covering 23.46 km, high (9.6—12.0) which covers 34.61 km, and very high (12.0–14.39) covering 7.5 km. This integrated study is found useful for exploring the accretion and erosion processes and also for vulnerability mapping in the coastal tract of Vishakhapatnam district.

The Sultanate of Oman overlooks three water bodies: The Arabian Sea, the Sea of Oman and the Arabian Gulf with a coastal face of more than 3000 km. Due to the recent global climate change, storm intensity has increased and inundation of coastal areas is inevitable. The pattern of coastal flooding depends on the geomorphologic and oceanographic characteristics of the coastal zone. The current research aims to delineate the susceptibility of Omani coast to the sudden sea level rise from cyclones and tsunamis using the coastal vulnerability index (CVI). Five physical parameters were implemented to perform the CVI, namely: The coastal geomorphology, elevation, slope, tidal range and bathymetry of the nearshore zone. Data were extracted from remotely sensed images and government resources assisted by field surveying. Geospatial analysis using geographical information system (GIS) was performed to manipulate and process the CVI from the collected data. Results showed that high vulnerable coastal regions to sea level rise account for 805 km of the coast, mostly along Al-Batinah plain in the north and along some scattered sectors at the eastern coast of the country. Major settlements and infrastructures are located at high CVI category. Moderate vulnerable coasts total 695 km mostly at the headlands along the Arabian Sea, whereas the low vulnerability coasts include the remaining shores along Musandam Peninsula and the eastern coast. This study provides a national map of the coastal vulnerability to the sea level rise, which is important for urban planning and decision supports for a sustainable management of Omani coastal zone.

Rising sea levels and the increasing intensity of storm surges and tropical cyclones due to climate change and the resulting dynamic shifts in shoreline positions have dramatically increased the exposure risk and vulnerability of local communities inhabiting the ecologically sensitive deltaic tracts of the Sunderbans in India. The impacts arising from such hazard events on this fragile ecosystem need to be gauged to ameliorate the lives and livelihoods of these residents. This article examines the spatial distribution of vulnerability to coastal hazards within the Sundarban Biosphere Reserve (SBR) in India. For this, we have utilized several structural and process variables, which were integrated to construct a coastal vulnerability index (CVI), using the square root equation. The coastlines of the islands located within the SBR were overlain by 543 grids, each of 2 × 2 km dimension, to assign the risk rank for each considered variable. This revealed that of the total shoreline length (754 km), nearly one-fourth was very highly vulnerable, followed by highly vulnerable (27.8%), moderately vulnerable (27.9%) and low vulnerability (18.8%). Of the total islands located in these grids (27), the coastline of eleven islands was found to have very high vulnerability, five experienced high vulnerability, eight recorded moderate vulnerability while only three had low vulnerability status. The ambient geomorphological characteristics, coastal area slope, the rate of shoreline change and sea level rise were significant variables that accorded high and very high vulnerability to the islands. The CVI helped in identifying islands that require immediate attention for lessening the impact of climate change induced hazards in the SBR and also aided the assessment of the physical and coastal vulnerability conditions of these islands. This approach can be effectively utilized for assessing coastal vulnerability and for creating a holistic approach towards coastal conservation and management.

The study mainly deals with the physical vulnerability of eastern coast India, Andhra Pradesh. It is one of the Indian states which have a very vast coastal line. Andhra Pradesh is very important to the whole economy, Vishakhapatnam is a major port situated in the eastern coast of India. Andhra Pradesh coastal line about 972 Km long, is affected by Storm surge, Cyclone, Sea Level Rise and Tsunami, etc. The method adopted for identifying the coastal vulnerability mapping was Coastal Vulnerability Index (CVI). Seven parameters were used for identifying Costal Vulnerability mapping which are Historical Shoreline changes, Mean Sea Level Rice, Significance of Wave Height, Mean Tide Range, Coastal Regional Elevation, Coastal Slope and Geomorphology. The final results of this study are in the form of a coastal vulnerability map which shows the environmentally vulnerable areas. This map will give general idea about the probability of an area to undergo coastal hazards due to coastal erosion or sea level rise. According to this study about 16% area of the coast of Andhra Pradesh is identified to have high vulnerability which can harm the environment. The map prepared of the Andhra coast under this study can be used by the state and district administration involved in the disaster mitigation and management plan.

The coastal zone is a vulnerable habitat that needs extra caution to protect ecosystems. Coastal systems are increasingly threatened by possible climate change consequences, as evidenced by the Intergovernmental Panel on Climate Change’s consecutive assessments. Increased tropical storm occurrences in recent years, in addition to the devastation caused by the tsunami in December 2004, have highlighted the necessity of analyzing the coast’s susceptibility to flooding-induced hazards to get a better knowledge of the factors that generate various hazards and, as a result, reduce the after-effects of future occurrences. The Ratnagiri coast in Maharashtra is prone to erosional hazards, periodic land rehabilitation, and sudden rises in sea level. The main objective is to calculate the CVI (Coastal Vulnerability Index) for the Ratnagiri coast. To analyze the vulnerability of the coastal region, eight risk parameters were used, viz. shoreline change rate, coastal elevation, sea level change rate, coastal slope, tide range, significant wave height, coastal geomorphology, and tsunami arrival height. The coastal vulnerability map was created by categorizing the numerous coastal portions into three vulnerability groups: high, medium, and low, which will aid coastal residents in risk mitigation in the future.

Comprehensive coastal vulnerability assessment and adaptation for Cherating-Pekan coast, Pahang, Malaysia

Kerentanan pantai merupakan kondisi dimana terdapat peningkatan proses kerusakan di wilayah pantai yang diakibatkan oleh berbagai faktor seperti aktivitas manusia dan faktor alami seperti pengaruh kenaikan muka laut, gelombang laut serta arus menyusur pantai yang mengakibatkan terjadinya proses abrasi maupun sedimentasi yang merupakan salah satu indikator adanya tekanan terhadap suatu kawasan pantai walaupun bukan berarti sebagai degradasi kondisi kawasan pantai. Analisis kerentanan pantai sangat penting untuk dilakukan, dengan melakukan kajian kondisi suatu kawasan pantai khususnya kajian mengenai kerentanan suatu kawasan pantai akan memudahkan dalam menyoroti bagian-bagian mana saja dari suatu pantai yang dinilai memiliki tingkat kerentanan yang tinggi dan faktor-faktor apa saja yang mengakibatkan kerentanan kawasan pantai tersebut. Penelitian mengenai kerentanan pantai timur Pulau Bintan dilaksanakan pada Bulan September-Oktober 2015 dengan mengamati variabel fisik dan variabel oseanografi yang terdiri dari geomorfologi pantai, kemiringan pantai, perubahan garis pantai dan rata-rata tinggi gelombang laut serta rata-rata kisaran pasang surut per tahun. Analisis kerentanan pantai menggunakan metode coastal vulnerability index (CVI) dengan memberikan skor terhadap masing-masing variabel yang digunakan sesuai dengan kategori yang telah ditetapkan oleh United States Geological Survey (USGS). Hasil analisis kerentanan pantai menunjukan geomorfologi pantai dan kemiringan pantai merupakan variabel tingkat kerentanan tinggi hingga sangat tinggi dengan skor kerentanan masing-masing variabel adalah 4.75 dan 5 (rentang skala skor berkisar antara 1-5). Indeks kerentanan pantai timur Pulau Bintan berkisar antara 3.16-3.54 dengan rata-rata 3.33 yang menunjukan bahwa tingkat kerentanan pantai timur Pulau Bintan berada dalam kategori rendah.

Coastal areas in Arctic and sub-Arctic regions are getting increasingly vulnerable to climate change, particularly due to sea-level rise and changing wave dynamics. This study assesses the coastal vulnerability of Sweden using the Coastal Vulnerability Index (CVI), based on a GIS-based, semi-quantitative approach integrating Earth Observation (EO) and geoinformatics. Six physical parameters were used: coastal geomorphology, coastal slope, shoreline change rate, relative sea-level change, mean tidal range, and significant wave height. CVI scores were derived from openly available national and international datasets, including satellite imagery and historical records. Mean tidal range and relative sea-level change were the most influential variables. The results indicate significant spatial variability: 36.5% of the coastline is classified as having “High” or “Very High” vulnerability, mainly in the south, while over 41% is “Low” or “Very Low,” especially in the Gulf of Bothnia. This assessment offers a harmonized spatial baseline to support sustainable coastal planning and adaptation efforts in Sweden and provides a comparative framework for coastal vulnerability studies across northern Europe.

Evaluation of coastal vulnerability for the District of Buenaventura, Colombia: A geospatial approach

Climate change interacts in a different way with varieties of human activities and other drivers of change along coastlines. Sea level rise (SLR) is one of the major impacts of global warming. Changes in climate extremes and SLR may impact the critical infrastructures such as coastal road, jetty and chalets as well as the local community. The population and assets exposed to coastal risks will increase significantly due to population growth, economic development and urbanization in the future. As most of the cities in Malaysia are situated near the coast, immediate actions are needed to minimize the undesired outcome due to the SLR. The main objective of this study is to identify physical variables that may have impacts on the coastal area, thus develop a coastal vulnerability index (CVI) for the East Coast of Peninsular Malaysia. Seven (7) physical variables have been identified to assess the CVI that consists of geomorphology, coastal slope, shoreline change rate, mean significant wave height, mean tidal range, relative sea level rate and land use. A comprehensive CVI was obtained by integrating the differential weighted rank values of the variables. The outcome of this study is useful as a tool for coastal disaster management.

Assessing the preparedness of the coastal region to the anticipated sea level rise is a major task among the coastal management authority, where identification of relative vulnerable of coast is a prime concern. The present research work has utilized Remote Sensing and GIS techniques for assessing vulnerability of the Gujarat coast due to predicted sea level rise. Synergetic use of satellite remote sensing, numerical simulations and filed observations has been done to generate coastal thematic information followed by validation. Coastal vulnerability assessment of the entire Gujarat coast on 1:50,000 scale were carried out considering five physical parameters. They are; coastal geomorphology, coastal slope, shoreline change rate, mean spring tidal range, and significant wave height. The rank values of all the five physical variables are integrated through additive method to compute a Coastal Vulnerability Index (CVI) where the relative ranking is assigned to various coastal segments based on the vulnerability level. The CVI values categorize Gujarat coast into four risk level classes. The results show that 785 km (45.67 %) of the Gujarat coast is under high to very high risk category and 934 km (54.33 %) of the Gujarat coast is under Moderate to Low risk category due to an anticipated rise in sea level. The coastal regions under very high risk category are along northwestern parts of the Gulf of Khambhat, the northernmost parts of the Gulf of Kachchh and western parts of the Kachchh coast. The southern parts of the Saurashtra coast and southwestern parts of the Kachchh coast is under the low risk category along with isolated segments along the eastern parts of the Gulf of Khambhat. The approach developed for assessing vulnerability of the coast to predicted sea level rise using remote sensing and GIS techniques can be used effectively by coastal management authorities and decision makers to devise better coastal zone management plans as well as to ensure efficient mitigation measures to minimize the losses due to possible impact of predicted sea level rise through which appropriate measures to protect life, property and environment can be timely planned.

The diversity function of coastal areas requires the increasing need for land and infrastructure that will lead to new problems such as changes in coastal morphology, the occurrence of erosion and accretion, which is supported by the population growth caused the increasing of coastal vulnerable towards hazards. This paper aims to explain the parameters affect Simeulue Island’s coastal vulnerability - beach slope, geomorphology, geology, shoreline change, mean tidal range and mean wave height - and its mapping. The data used were the bathymetry, tide, and currents, the topography of coastal morphology, LANDSAT imagery of 2000 and 2015. To determine the coastal vulnerability level, we implemented CVI (Coastal Vulnerability Index) method of 6 parameters. Finally, we found that CVI from these physical parameters ranges between 1.291to 5.00, which were classified into five classes; 1.291 – 1.826 (very low), 1.826 – 2.449 (low), 2.449 – 2.887 (moderate), 2.887 – 3.651(high), and 3.651 – 5.00 (very high).