Evaluating shoreline prediction accuracy with the Kalman filter model: A case study of Nijhum Dwip, Bay of Bengal

IF 3.8 Q2 ENVIRONMENTAL SCIENCES Remote Sensing Applications-Society and Environment Pub Date : 2025-01-01 DOI:10.1016/j.rsase.2025.101469

Anamika Das Kona , Md Enamul Hoque , Md Atiqur Rahman

{"title":"Evaluating shoreline prediction accuracy with the Kalman filter model: A case study of Nijhum Dwip, Bay of Bengal","authors":"Anamika Das Kona , Md Enamul Hoque , Md Atiqur Rahman","doi":"10.1016/j.rsase.2025.101469","DOIUrl":null,"url":null,"abstract":"<div><div>Shoreline dynamics play a critical role in coastal zone management and environmental conservation. This study investigates shoreline changes and predictions for Nijhum Dwip, located in the Meghna estuary, over the period from 1980 to 2020, with a forecast for 2030. Utilizing multi-temporal Landsat imagery, Digital Shoreline Analysis System (DSAS), and the Kalman Filter Model, the study analyzes spatial and temporal shoreline variations. Results indicate a significant accretion trend, particularly in Segment B, which exhibits a net shoreline movement of 1322.85 m and an average rate of 31.96 m/yr. Segment A shows moderate accretion, with an average rate of 7.79 m/yr. The Kalman Filter Model predicts a mean accretion of 1601.23 m by 2030, aligning with historical accretion patterns. Model validation through Root Mean Square Error (RMSE) analysis yields a value of 95 m, highlighting discrepancies between predicted and observed shoreline positions. This comprehensive study underscores the utility of advanced geospatial and statistical methods in coastal change monitoring and provides actionable insights for sustainable coastal management.</div></div>","PeriodicalId":53227,"journal":{"name":"Remote Sensing Applications-Society and Environment","volume":"37 ","pages":"Article 101469"},"PeriodicalIF":3.8000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing Applications-Society and Environment","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352938525000229","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}

引用次数: 0

Abstract

Shoreline dynamics play a critical role in coastal zone management and environmental conservation. This study investigates shoreline changes and predictions for Nijhum Dwip, located in the Meghna estuary, over the period from 1980 to 2020, with a forecast for 2030. Utilizing multi-temporal Landsat imagery, Digital Shoreline Analysis System (DSAS), and the Kalman Filter Model, the study analyzes spatial and temporal shoreline variations. Results indicate a significant accretion trend, particularly in Segment B, which exhibits a net shoreline movement of 1322.85 m and an average rate of 31.96 m/yr. Segment A shows moderate accretion, with an average rate of 7.79 m/yr. The Kalman Filter Model predicts a mean accretion of 1601.23 m by 2030, aligning with historical accretion patterns. Model validation through Root Mean Square Error (RMSE) analysis yields a value of 95 m, highlighting discrepancies between predicted and observed shoreline positions. This comprehensive study underscores the utility of advanced geospatial and statistical methods in coastal change monitoring and provides actionable insights for sustainable coastal management.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

求助全文

约1分钟内获得全文去求助

来源期刊

Remote Sensing Applications-Society and Environment Multiple-

CiteScore

8.00

自引率

8.50%

发文量

204

审稿时长

65 days

期刊介绍： The journal ''Remote Sensing Applications: Society and Environment'' (RSASE) focuses on remote sensing studies that address specific topics with an emphasis on environmental and societal issues - regional / local studies with global significance. Subjects are encouraged to have an interdisciplinary approach and include, but are not limited by: " -Global and climate change studies addressing the impact of increasing concentrations of greenhouse gases, CO2 emission, carbon balance and carbon mitigation, energy system on social and environmental systems -Ecological and environmental issues including biodiversity, ecosystem dynamics, land degradation, atmospheric and water pollution, urban footprint, ecosystem management and natural hazards (e.g. earthquakes, typhoons, floods, landslides) -Natural resource studies including land-use in general, biomass estimation, forests, agricultural land, plantation, soils, coral reefs, wetland and water resources -Agriculture, food production systems and food security outcomes -Socio-economic issues including urban systems, urban growth, public health, epidemics, land-use transition and land use conflicts -Oceanography and coastal zone studies, including sea level rise projections, coastlines changes and the ocean-land interface -Regional challenges for remote sensing application techniques, monitoring and analysis, such as cloud screening and atmospheric correction for tropical regions -Interdisciplinary studies combining remote sensing, household survey data, field measurements and models to address environmental, societal and sustainability issues -Quantitative and qualitative analysis that documents the impact of using remote sensing studies in social, political, environmental or economic systems