Shoreline morphology changes along the Eastern Coast of India, Andhra Pradesh by using geospatial technology
Abstract Shoreline changes on account of global climate change and sea level rise is one of the major problems along the coastlines in different continents of the world. This study was carried out along the coastlines of Andhra Pradesh state in India using multi-temporal satellite images from 1973 t...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Basheer Ahammed, K. K. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2018 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Nature B.V. 2018 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of coastal conservation - Dordrecht : Springer Netherlands, 1995, 23(2018), 2 vom: 25. Okt., Seite 331-353 |
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| Übergeordnetes Werk: |
volume:23 ; year:2018 ; number:2 ; day:25 ; month:10 ; pages:331-353 |
| Links: |
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| DOI / URN: |
10.1007/s11852-018-0662-5 |
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SPR022804021 |
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| 520 | |a Abstract Shoreline changes on account of global climate change and sea level rise is one of the major problems along the coastlines in different continents of the world. This study was carried out along the coastlines of Andhra Pradesh state in India using multi-temporal satellite images from 1973 to 2015 period. Long-term coastal erosion and accretion rate over a period of 42 years has calculated using Digital Shoreline Analysis System and prepared shoreline maps by using GIS-Software. End point rate (EPR) statistical method is applied to estimate the shoreline change rate. Various coastal parameters like sea level rise, geomorphology, elevation and coastal slope were used to find out the interactive relationship between the physical parameters and shoreline changes in the area. The study revealed that the coastal changes are more dominant in Krishna and Godavari Deltaic plain. The average erosion and accretion rate observed in the Krishna Godavari delta was 10.63 and 17.29 m per year respectively. The study indicated that, climatic changes and fluvial process are playing key role in changing shoreline positions. The study exhibited that elevation and slope are played intense role in the shoreline positional change. The present study demonstrates that combined use of satellite imagery and EPR statistical method as an accurate and reliable method for shoreline change analysis. | ||
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10.1007/s11852-018-0662-5 doi (DE-627)SPR022804021 (SPR)s11852-018-0662-5-e DE-627 ger DE-627 rakwb eng Basheer Ahammed, K. K. verfasserin aut Shoreline morphology changes along the Eastern Coast of India, Andhra Pradesh by using geospatial technology 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Nature B.V. 2018 Abstract Shoreline changes on account of global climate change and sea level rise is one of the major problems along the coastlines in different continents of the world. This study was carried out along the coastlines of Andhra Pradesh state in India using multi-temporal satellite images from 1973 to 2015 period. Long-term coastal erosion and accretion rate over a period of 42 years has calculated using Digital Shoreline Analysis System and prepared shoreline maps by using GIS-Software. End point rate (EPR) statistical method is applied to estimate the shoreline change rate. Various coastal parameters like sea level rise, geomorphology, elevation and coastal slope were used to find out the interactive relationship between the physical parameters and shoreline changes in the area. The study revealed that the coastal changes are more dominant in Krishna and Godavari Deltaic plain. The average erosion and accretion rate observed in the Krishna Godavari delta was 10.63 and 17.29 m per year respectively. The study indicated that, climatic changes and fluvial process are playing key role in changing shoreline positions. The study exhibited that elevation and slope are played intense role in the shoreline positional change. The present study demonstrates that combined use of satellite imagery and EPR statistical method as an accurate and reliable method for shoreline change analysis. Shoreline change (dpeaa)DE-He213 Digital shoreline analysis system (dpeaa)DE-He213 EPR (dpeaa)DE-He213 GIS (dpeaa)DE-He213 Pandey, Arvind Chandra aut Enthalten in Journal of coastal conservation Dordrecht : Springer Netherlands, 1995 23(2018), 2 vom: 25. Okt., Seite 331-353 (DE-627)332338533 (DE-600)2053395-0 1874-7841 nnns volume:23 year:2018 number:2 day:25 month:10 pages:331-353 https://dx.doi.org/10.1007/s11852-018-0662-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2939 GBV_ILN_2946 GBV_ILN_2949 GBV_ILN_2951 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4393 GBV_ILN_4700 AR 23 2018 2 25 10 331-353 |
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10.1007/s11852-018-0662-5 doi (DE-627)SPR022804021 (SPR)s11852-018-0662-5-e DE-627 ger DE-627 rakwb eng Basheer Ahammed, K. K. verfasserin aut Shoreline morphology changes along the Eastern Coast of India, Andhra Pradesh by using geospatial technology 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Nature B.V. 2018 Abstract Shoreline changes on account of global climate change and sea level rise is one of the major problems along the coastlines in different continents of the world. This study was carried out along the coastlines of Andhra Pradesh state in India using multi-temporal satellite images from 1973 to 2015 period. Long-term coastal erosion and accretion rate over a period of 42 years has calculated using Digital Shoreline Analysis System and prepared shoreline maps by using GIS-Software. End point rate (EPR) statistical method is applied to estimate the shoreline change rate. Various coastal parameters like sea level rise, geomorphology, elevation and coastal slope were used to find out the interactive relationship between the physical parameters and shoreline changes in the area. The study revealed that the coastal changes are more dominant in Krishna and Godavari Deltaic plain. The average erosion and accretion rate observed in the Krishna Godavari delta was 10.63 and 17.29 m per year respectively. The study indicated that, climatic changes and fluvial process are playing key role in changing shoreline positions. The study exhibited that elevation and slope are played intense role in the shoreline positional change. The present study demonstrates that combined use of satellite imagery and EPR statistical method as an accurate and reliable method for shoreline change analysis. Shoreline change (dpeaa)DE-He213 Digital shoreline analysis system (dpeaa)DE-He213 EPR (dpeaa)DE-He213 GIS (dpeaa)DE-He213 Pandey, Arvind Chandra aut Enthalten in Journal of coastal conservation Dordrecht : Springer Netherlands, 1995 23(2018), 2 vom: 25. Okt., Seite 331-353 (DE-627)332338533 (DE-600)2053395-0 1874-7841 nnns volume:23 year:2018 number:2 day:25 month:10 pages:331-353 https://dx.doi.org/10.1007/s11852-018-0662-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2939 GBV_ILN_2946 GBV_ILN_2949 GBV_ILN_2951 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4393 GBV_ILN_4700 AR 23 2018 2 25 10 331-353 |
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10.1007/s11852-018-0662-5 doi (DE-627)SPR022804021 (SPR)s11852-018-0662-5-e DE-627 ger DE-627 rakwb eng Basheer Ahammed, K. K. verfasserin aut Shoreline morphology changes along the Eastern Coast of India, Andhra Pradesh by using geospatial technology 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Nature B.V. 2018 Abstract Shoreline changes on account of global climate change and sea level rise is one of the major problems along the coastlines in different continents of the world. This study was carried out along the coastlines of Andhra Pradesh state in India using multi-temporal satellite images from 1973 to 2015 period. Long-term coastal erosion and accretion rate over a period of 42 years has calculated using Digital Shoreline Analysis System and prepared shoreline maps by using GIS-Software. End point rate (EPR) statistical method is applied to estimate the shoreline change rate. Various coastal parameters like sea level rise, geomorphology, elevation and coastal slope were used to find out the interactive relationship between the physical parameters and shoreline changes in the area. The study revealed that the coastal changes are more dominant in Krishna and Godavari Deltaic plain. The average erosion and accretion rate observed in the Krishna Godavari delta was 10.63 and 17.29 m per year respectively. The study indicated that, climatic changes and fluvial process are playing key role in changing shoreline positions. The study exhibited that elevation and slope are played intense role in the shoreline positional change. The present study demonstrates that combined use of satellite imagery and EPR statistical method as an accurate and reliable method for shoreline change analysis. Shoreline change (dpeaa)DE-He213 Digital shoreline analysis system (dpeaa)DE-He213 EPR (dpeaa)DE-He213 GIS (dpeaa)DE-He213 Pandey, Arvind Chandra aut Enthalten in Journal of coastal conservation Dordrecht : Springer Netherlands, 1995 23(2018), 2 vom: 25. Okt., Seite 331-353 (DE-627)332338533 (DE-600)2053395-0 1874-7841 nnns volume:23 year:2018 number:2 day:25 month:10 pages:331-353 https://dx.doi.org/10.1007/s11852-018-0662-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2939 GBV_ILN_2946 GBV_ILN_2949 GBV_ILN_2951 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4393 GBV_ILN_4700 AR 23 2018 2 25 10 331-353 |
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| author |
Basheer Ahammed, K. K. |
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Basheer Ahammed, K. K. misc Shoreline change misc Digital shoreline analysis system misc EPR misc GIS Shoreline morphology changes along the Eastern Coast of India, Andhra Pradesh by using geospatial technology |
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Shoreline morphology changes along the Eastern Coast of India, Andhra Pradesh by using geospatial technology Shoreline change (dpeaa)DE-He213 Digital shoreline analysis system (dpeaa)DE-He213 EPR (dpeaa)DE-He213 GIS (dpeaa)DE-He213 |
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shoreline morphology changes along the eastern coast of india, andhra pradesh by using geospatial technology |
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Shoreline morphology changes along the Eastern Coast of India, Andhra Pradesh by using geospatial technology |
| abstract |
Abstract Shoreline changes on account of global climate change and sea level rise is one of the major problems along the coastlines in different continents of the world. This study was carried out along the coastlines of Andhra Pradesh state in India using multi-temporal satellite images from 1973 to 2015 period. Long-term coastal erosion and accretion rate over a period of 42 years has calculated using Digital Shoreline Analysis System and prepared shoreline maps by using GIS-Software. End point rate (EPR) statistical method is applied to estimate the shoreline change rate. Various coastal parameters like sea level rise, geomorphology, elevation and coastal slope were used to find out the interactive relationship between the physical parameters and shoreline changes in the area. The study revealed that the coastal changes are more dominant in Krishna and Godavari Deltaic plain. The average erosion and accretion rate observed in the Krishna Godavari delta was 10.63 and 17.29 m per year respectively. The study indicated that, climatic changes and fluvial process are playing key role in changing shoreline positions. The study exhibited that elevation and slope are played intense role in the shoreline positional change. The present study demonstrates that combined use of satellite imagery and EPR statistical method as an accurate and reliable method for shoreline change analysis. © Springer Nature B.V. 2018 |
| abstractGer |
Abstract Shoreline changes on account of global climate change and sea level rise is one of the major problems along the coastlines in different continents of the world. This study was carried out along the coastlines of Andhra Pradesh state in India using multi-temporal satellite images from 1973 to 2015 period. Long-term coastal erosion and accretion rate over a period of 42 years has calculated using Digital Shoreline Analysis System and prepared shoreline maps by using GIS-Software. End point rate (EPR) statistical method is applied to estimate the shoreline change rate. Various coastal parameters like sea level rise, geomorphology, elevation and coastal slope were used to find out the interactive relationship between the physical parameters and shoreline changes in the area. The study revealed that the coastal changes are more dominant in Krishna and Godavari Deltaic plain. The average erosion and accretion rate observed in the Krishna Godavari delta was 10.63 and 17.29 m per year respectively. The study indicated that, climatic changes and fluvial process are playing key role in changing shoreline positions. The study exhibited that elevation and slope are played intense role in the shoreline positional change. The present study demonstrates that combined use of satellite imagery and EPR statistical method as an accurate and reliable method for shoreline change analysis. © Springer Nature B.V. 2018 |
| abstract_unstemmed |
Abstract Shoreline changes on account of global climate change and sea level rise is one of the major problems along the coastlines in different continents of the world. This study was carried out along the coastlines of Andhra Pradesh state in India using multi-temporal satellite images from 1973 to 2015 period. Long-term coastal erosion and accretion rate over a period of 42 years has calculated using Digital Shoreline Analysis System and prepared shoreline maps by using GIS-Software. End point rate (EPR) statistical method is applied to estimate the shoreline change rate. Various coastal parameters like sea level rise, geomorphology, elevation and coastal slope were used to find out the interactive relationship between the physical parameters and shoreline changes in the area. The study revealed that the coastal changes are more dominant in Krishna and Godavari Deltaic plain. The average erosion and accretion rate observed in the Krishna Godavari delta was 10.63 and 17.29 m per year respectively. The study indicated that, climatic changes and fluvial process are playing key role in changing shoreline positions. The study exhibited that elevation and slope are played intense role in the shoreline positional change. The present study demonstrates that combined use of satellite imagery and EPR statistical method as an accurate and reliable method for shoreline change analysis. © Springer Nature B.V. 2018 |
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2 |
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Shoreline morphology changes along the Eastern Coast of India, Andhra Pradesh by using geospatial technology |
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https://dx.doi.org/10.1007/s11852-018-0662-5 |
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Pandey, Arvind Chandra |
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10.1007/s11852-018-0662-5 |
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2024-07-03T14:58:50.302Z |
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| score |
7.402439 |