Bharath N. , Swathi K.K. , Dwarakish G.S. , Shivanna , Jagadeesha Pai B.
{"title":"基于DSAS的印度西南芒格洛尔海岸岸线变化探测与土地利用/覆被变化分析","authors":"Bharath N. , Swathi K.K. , Dwarakish G.S. , Shivanna , Jagadeesha Pai B.","doi":"10.1016/j.indic.2025.100906","DOIUrl":null,"url":null,"abstract":"<div><div>This study presents an integrated assessment combining Digital Shoreline Analysis System (DSAS) and multi-temporal Land Use/Land Cover (LU/LC) analysis to quantitatively link shoreline change and land use dynamics along the Mangalore coast, extending 26 km from Talapady in the south to Surathkal in the north. The objectives of the study were 1) to calculate the shoreline change rates for short and long periods along the study area with the help of the DSAS v5.1 tool in ArcGIS, and 2) to calculate LU/LC dynamics using remote sensing data from 1997 to 2022, including accuracy assessment of classifications. The shorelines were extracted by using conventional data (toposheet) and remote sensing data with multi-dated satellite images of Landsat 5, 7, 8 and 9 along with Resourcesat- LISS-Ⅲ. The shoreline change rates are detected through two statistical methods: Endpoint rate-EPR(m/yr) and Linear regression rate-LRR(m/yr). The change analysis reveals that the coastline is highly eroded about −3.24 m/yr (EPR) in the year 2000, and highly accreted about +3.99 m/yr (EPR) in 2009 compared to the 1970 shoreline. The long-term change analysis reveals that the coastline shows an average accretion rate of about 1.89 m/yr (LRR). Key limitations include potential errors in shoreline digitisation and spatial resolution constraints, which may impact rate precision. The study emphasises the urgent need for integrated coastal zone management to balance development pressures with environmental sustainability near the Ullal and Bengre regions, and highlights implications for achieving Sustainable Development Goal targets related to climate action and sustainable coastal ecosystems.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"28 ","pages":"Article 100906"},"PeriodicalIF":5.6000,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Shoreline change detection using DSAS and Land use/Land cover change analysis of Mangalore coast, southwest coast of India\",\"authors\":\"Bharath N. , Swathi K.K. , Dwarakish G.S. , Shivanna , Jagadeesha Pai B.\",\"doi\":\"10.1016/j.indic.2025.100906\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study presents an integrated assessment combining Digital Shoreline Analysis System (DSAS) and multi-temporal Land Use/Land Cover (LU/LC) analysis to quantitatively link shoreline change and land use dynamics along the Mangalore coast, extending 26 km from Talapady in the south to Surathkal in the north. The objectives of the study were 1) to calculate the shoreline change rates for short and long periods along the study area with the help of the DSAS v5.1 tool in ArcGIS, and 2) to calculate LU/LC dynamics using remote sensing data from 1997 to 2022, including accuracy assessment of classifications. The shorelines were extracted by using conventional data (toposheet) and remote sensing data with multi-dated satellite images of Landsat 5, 7, 8 and 9 along with Resourcesat- LISS-Ⅲ. The shoreline change rates are detected through two statistical methods: Endpoint rate-EPR(m/yr) and Linear regression rate-LRR(m/yr). The change analysis reveals that the coastline is highly eroded about −3.24 m/yr (EPR) in the year 2000, and highly accreted about +3.99 m/yr (EPR) in 2009 compared to the 1970 shoreline. The long-term change analysis reveals that the coastline shows an average accretion rate of about 1.89 m/yr (LRR). Key limitations include potential errors in shoreline digitisation and spatial resolution constraints, which may impact rate precision. The study emphasises the urgent need for integrated coastal zone management to balance development pressures with environmental sustainability near the Ullal and Bengre regions, and highlights implications for achieving Sustainable Development Goal targets related to climate action and sustainable coastal ecosystems.</div></div>\",\"PeriodicalId\":36171,\"journal\":{\"name\":\"Environmental and Sustainability Indicators\",\"volume\":\"28 \",\"pages\":\"Article 100906\"},\"PeriodicalIF\":5.6000,\"publicationDate\":\"2025-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental and Sustainability Indicators\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2665972725003277\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental and Sustainability Indicators","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2665972725003277","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Shoreline change detection using DSAS and Land use/Land cover change analysis of Mangalore coast, southwest coast of India
This study presents an integrated assessment combining Digital Shoreline Analysis System (DSAS) and multi-temporal Land Use/Land Cover (LU/LC) analysis to quantitatively link shoreline change and land use dynamics along the Mangalore coast, extending 26 km from Talapady in the south to Surathkal in the north. The objectives of the study were 1) to calculate the shoreline change rates for short and long periods along the study area with the help of the DSAS v5.1 tool in ArcGIS, and 2) to calculate LU/LC dynamics using remote sensing data from 1997 to 2022, including accuracy assessment of classifications. The shorelines were extracted by using conventional data (toposheet) and remote sensing data with multi-dated satellite images of Landsat 5, 7, 8 and 9 along with Resourcesat- LISS-Ⅲ. The shoreline change rates are detected through two statistical methods: Endpoint rate-EPR(m/yr) and Linear regression rate-LRR(m/yr). The change analysis reveals that the coastline is highly eroded about −3.24 m/yr (EPR) in the year 2000, and highly accreted about +3.99 m/yr (EPR) in 2009 compared to the 1970 shoreline. The long-term change analysis reveals that the coastline shows an average accretion rate of about 1.89 m/yr (LRR). Key limitations include potential errors in shoreline digitisation and spatial resolution constraints, which may impact rate precision. The study emphasises the urgent need for integrated coastal zone management to balance development pressures with environmental sustainability near the Ullal and Bengre regions, and highlights implications for achieving Sustainable Development Goal targets related to climate action and sustainable coastal ecosystems.