The change processes and trends of shoreline and tidal flat forced by human activities are essential issues for the sustainability of coastal area,which is also of great significance for understanding coastal ecologic...The change processes and trends of shoreline and tidal flat forced by human activities are essential issues for the sustainability of coastal area,which is also of great significance for understanding coastal ecological environment changes and even global changes.Based on field measurements,combined with Linear Regression(LR)model and Inverse Distance Weighing(IDW)method,this paper presents detailed analysis on the change history and trend of the shoreline and tidal flat in Bohai Bay.The shoreline faces a high erosion chance under the action of natural factors,while the tidal flat faces a different erosion and deposition patterns in Bohai Bay due to the impact of human activities.The implication of change rule for ecological protection and recovery is also discussed.Measures should be taken to protect the coastal ecological environment.The models used in this paper show a high correlation coefficient between observed and modeling data,which means that this method can be used to predict the changing trend of shoreline and tidal flat.The research results of present study can provide scientific supports for future coastal protection and management.展开更多
The present study aims to analyze the shift in shoreline due to coastal processes and formulate available for best estimate of future shoreline positions based on precedent shorelines. Information on rates and trends ...The present study aims to analyze the shift in shoreline due to coastal processes and formulate available for best estimate of future shoreline positions based on precedent shorelines. Information on rates and trends of shoreline change can be used to improve the understanding of the underlying causes and potential effects of coastal erosion which can support informed coastal management decisions. In this paper, researchers go over the changes in the recent positions of the shoreline of the Balasore coast for the 38 years from 1975 through 2013. The study area includes the Balasore coastal region from Rasalpur to Udaypur together with Chandipur, Choumukh, Chandrabali as well as Bichitrapur. Transects wise shoreline data base were developed for approximately 67 kilometers of shoreline and erosional/accretional scenario has also been analysed by delineating the shoreline from Landsat imageries of 1975, 1980, 1990, 1995, 2000, 2005, 2010 and 2013. A simple Linear Regression Model and End Point Rate (EPR) have been adopted to take out the rate of change of shoreline and its future positions, based on empirical observations at 67 transects along the Balasore coast. It is found that the north eastern part of Balasore coast in the vicinity of Subarnarekha estuary and Chandrabali beach undergo high rates of shore line shift. The shoreline data were integrated for long- (about 17 years) and short-term (about 7 years) shift rates analysis to comprehend the shoreline change and prediction. For the prediction of future shoreline, the model has been validated with the present shoreline position (2013). The rate of shoreline movement calculated from the fixed base line to shoreline position of 1975, 1980, 1990, 1995, 2000, 2005 and 2010 and based on this, the estimated shoreline of 2013 was calculated. The estimated shoreline was compared with the actual shoreline delineated from satellite imagery of 2013. The model error or positional shift at each sample point is observed. The positional error varies from??4.82 m to 212.41 m展开更多
The prediction of shoreline erosion is vital for coastal management. This study aims to utilize geo-informatics technology to increase accuracy of a shoreline prediction model along two study sites in Samutprakarn pro...The prediction of shoreline erosion is vital for coastal management. This study aims to utilize geo-informatics technology to increase accuracy of a shoreline prediction model along two study sites in Samutprakarn province and in Prachuabkirikhan province. Predicting coastline change using remote sensing together with GIS （geographic information system） is a spat^o-temporal technology, which can continuously provide perspectives of coastal areas. Due to a long term of operational period of LANDSAT satellite, it is useful to enhance accuracy of prediction model. LANDSAT-5 TM images acquired during 1999-2009 were used to produce historical shoreline vectors. Physical data were modified to be input data of digital shoreline analysis system. The model was validated. Linear regressions were applied in order to derive equations of erosion magnitude. The result presents that averaged erosion and accretion rate along Samutprakarn province was 22.30 meters/year and 2.94 meters/year, respectively. On the other hand, the average rate of coastal erosion along Prachuabkirikhan province was much lower, being 2.48 meters/year while the accretion rate was approximately 4.11 meters/year. The predicted shoreline change at Samutprakarn province in 2019 is about -132.69 ~ 0.758 meters while at Prachuabkirikhan is 40.58 ~ 0.0012 meters. In conclusion, this prediction model focused the changing of shoreline in long term and accuracy of the model could be improved by increasing number of shorelines vectors, transect intervals and resolution of satellite images. Clearly, the model is flexible and can be applied in other particular areas for coastal zone management in Thailand.展开更多
This study explains the multi-decadal shoreline changes along the coast of Kanyakumari from 1980 to2020.The shorelines are extracted from the Landsat images to estimate the shoreline dynamics and future predictions us...This study explains the multi-decadal shoreline changes along the coast of Kanyakumari from 1980 to2020.The shorelines are extracted from the Landsat images to estimate the shoreline dynamics and future predictions using Digital Shoreline Analysis System(DSAS).By the estimation of End Point Rate(EPR)and Linear Regression Rate(LRR),it is quantified that the maximum erosion is 5.01 m/yr(EPR)and 6.13 m/yr(LRR)consistently with the maximum accretion of 3.77 m/yr(EPR)and 3.11 m/yr(LRR)along the entire coastal stretch of 77 km.The future shoreline predicted using the Kalman filter forecasted that Inayam,Periyakattuthurai and Kodimunai are highly prone to erosion with a shift of 170 m,157 m and 145 m by 2030 and 194 m,182 m and 165 m by 2040 towards the land.Also,the western coast is highly prone to erosion and it is predicted that certain villages are prone to loss of economy and livelihood.The outcome of this study may guide the coastal researchers to understand the evolution and decisionmakers to evolve with alternative sustainable management plans in the future.展开更多
基金supported by the National Natural Science Foundation of China (41602205, 42293261)the China Geological Survey Program (DD20189506, DD20211301)+2 种基金the Special Investigation Project on Science and Technology Basic Resources of the Ministry of Science and Technology (2021FY101003)the Central Guidance for Local Scientific and Technological Development Fund of 2023the Project of Hebei University of Environmental Engineering (GCY202301)
文摘The change processes and trends of shoreline and tidal flat forced by human activities are essential issues for the sustainability of coastal area,which is also of great significance for understanding coastal ecological environment changes and even global changes.Based on field measurements,combined with Linear Regression(LR)model and Inverse Distance Weighing(IDW)method,this paper presents detailed analysis on the change history and trend of the shoreline and tidal flat in Bohai Bay.The shoreline faces a high erosion chance under the action of natural factors,while the tidal flat faces a different erosion and deposition patterns in Bohai Bay due to the impact of human activities.The implication of change rule for ecological protection and recovery is also discussed.Measures should be taken to protect the coastal ecological environment.The models used in this paper show a high correlation coefficient between observed and modeling data,which means that this method can be used to predict the changing trend of shoreline and tidal flat.The research results of present study can provide scientific supports for future coastal protection and management.
文摘The present study aims to analyze the shift in shoreline due to coastal processes and formulate available for best estimate of future shoreline positions based on precedent shorelines. Information on rates and trends of shoreline change can be used to improve the understanding of the underlying causes and potential effects of coastal erosion which can support informed coastal management decisions. In this paper, researchers go over the changes in the recent positions of the shoreline of the Balasore coast for the 38 years from 1975 through 2013. The study area includes the Balasore coastal region from Rasalpur to Udaypur together with Chandipur, Choumukh, Chandrabali as well as Bichitrapur. Transects wise shoreline data base were developed for approximately 67 kilometers of shoreline and erosional/accretional scenario has also been analysed by delineating the shoreline from Landsat imageries of 1975, 1980, 1990, 1995, 2000, 2005, 2010 and 2013. A simple Linear Regression Model and End Point Rate (EPR) have been adopted to take out the rate of change of shoreline and its future positions, based on empirical observations at 67 transects along the Balasore coast. It is found that the north eastern part of Balasore coast in the vicinity of Subarnarekha estuary and Chandrabali beach undergo high rates of shore line shift. The shoreline data were integrated for long- (about 17 years) and short-term (about 7 years) shift rates analysis to comprehend the shoreline change and prediction. For the prediction of future shoreline, the model has been validated with the present shoreline position (2013). The rate of shoreline movement calculated from the fixed base line to shoreline position of 1975, 1980, 1990, 1995, 2000, 2005 and 2010 and based on this, the estimated shoreline of 2013 was calculated. The estimated shoreline was compared with the actual shoreline delineated from satellite imagery of 2013. The model error or positional shift at each sample point is observed. The positional error varies from??4.82 m to 212.41 m
文摘The prediction of shoreline erosion is vital for coastal management. This study aims to utilize geo-informatics technology to increase accuracy of a shoreline prediction model along two study sites in Samutprakarn province and in Prachuabkirikhan province. Predicting coastline change using remote sensing together with GIS （geographic information system） is a spat^o-temporal technology, which can continuously provide perspectives of coastal areas. Due to a long term of operational period of LANDSAT satellite, it is useful to enhance accuracy of prediction model. LANDSAT-5 TM images acquired during 1999-2009 were used to produce historical shoreline vectors. Physical data were modified to be input data of digital shoreline analysis system. The model was validated. Linear regressions were applied in order to derive equations of erosion magnitude. The result presents that averaged erosion and accretion rate along Samutprakarn province was 22.30 meters/year and 2.94 meters/year, respectively. On the other hand, the average rate of coastal erosion along Prachuabkirikhan province was much lower, being 2.48 meters/year while the accretion rate was approximately 4.11 meters/year. The predicted shoreline change at Samutprakarn province in 2019 is about -132.69 ~ 0.758 meters while at Prachuabkirikhan is 40.58 ~ 0.0012 meters. In conclusion, this prediction model focused the changing of shoreline in long term and accuracy of the model could be improved by increasing number of shorelines vectors, transect intervals and resolution of satellite images. Clearly, the model is flexible and can be applied in other particular areas for coastal zone management in Thailand.
文摘This study explains the multi-decadal shoreline changes along the coast of Kanyakumari from 1980 to2020.The shorelines are extracted from the Landsat images to estimate the shoreline dynamics and future predictions using Digital Shoreline Analysis System(DSAS).By the estimation of End Point Rate(EPR)and Linear Regression Rate(LRR),it is quantified that the maximum erosion is 5.01 m/yr(EPR)and 6.13 m/yr(LRR)consistently with the maximum accretion of 3.77 m/yr(EPR)and 3.11 m/yr(LRR)along the entire coastal stretch of 77 km.The future shoreline predicted using the Kalman filter forecasted that Inayam,Periyakattuthurai and Kodimunai are highly prone to erosion with a shift of 170 m,157 m and 145 m by 2030 and 194 m,182 m and 165 m by 2040 towards the land.Also,the western coast is highly prone to erosion and it is predicted that certain villages are prone to loss of economy and livelihood.The outcome of this study may guide the coastal researchers to understand the evolution and decisionmakers to evolve with alternative sustainable management plans in the future.
