Assessing the multi-decadal shoreline dynamics along the Purba Medinipur Balasore coastal stretch, India by integrating remote sensing and statistical methods SK

Hossain, Ariful; Mondal, Ismail; Thakur, Sandeep; Linh, Nguyen Thi Thuy; Anh, Duong Tran

doi:10.1007/s11600-022-00797-5

Artykuł - szczegóły

Tytuł artykułu

Assessing the multi-decadal shoreline dynamics along the Purba Medinipur Balasore coastal stretch, India by integrating remote sensing and statistical methods SK

Autorzy

Hossain Ariful , Mondal Ismail , Thakur Sandeep , Linh Nguyen Thi Thuy , Anh Duong Tran

Wybrane pełne teksty z tego czasopisma

https://www.springer.com/journal/11600

Identyfikatory

DOI

10.1007/s11600-022-00797-5

Warianty tytułu

Języki publikacji

Abstrakty

Monitoring decadal shoreline change is essential to understand the influence of coastal processes on the coastline. The shoreline is constantly shaped by natural and anthropogenic factors, and so, it is critical to understand decadal trends. The prediction of future shoreline positions is a must for effective long-term coastal zone management. This study was conducted along a 90-km-stretch of the coastline from the mouth of the Haldi River (Purba Medinipur) in the Northeast to the Subarnarekha estuary (Balasore) in the Southwest. The primary objectives of the study were to analyze the decadal shoreline migration using the End Point Rate (EPR) method and then predict future shoreline change prediction using the Kalman Filter method. Shoreline positions were digitized after extracting the shorelines using Principal Component Analysis (PCA) from Multi-temporal (1990, 2000, 2010, and 2020) and Multisensor (Landsat TM, ETM+, and OLI) satellite data. A total of 887 transects were cast to compute change statistics of the time series shoreline. It was observed that the average shoreline change rate was −8.41 m/year in the periods of 1990–2000 and 2000–2010, and −8.80 m/year from 2010 to 2020. Accretion along this coastal stretch is caused by the growth of morphological features such as sand bars, beaches, and dunes. We also found that erosion occurred from 1990 to 2000 along the coastline of Bhograi, Ramnagar-I, Ramnagar-II, a few parts of Contai-I, Khejuri-I, and the Nandigram-I coastal block. Accretion mostly occurred due to Land reclamation in the Northern portion of Bhograi, Contai-1 blocks and Nandigram- I block from 2000 to 2010 and 2010 to2020. Root mean square error (RMSE) and Regression Coefficient values were computed for the future shoreline prediction of 2031 and 2041. The calculated RMSE value of±4.7 m and value of 0.97 shows a good relationship between the actual and predicted coastline of 2020. This study concludes that the coastline of Purba Medinipur-Balasore experienced severe erosion and needs management action and also proves the efficiency of the Digital Shoreline Analysis System (DSAS) tool for decadal analysis and prediction of shoreline change. The findings of this study may help the coastal planners, environmentalists, and coastal managers in preparing both short-term and long-term coastal zone management plans.

Słowa kluczowe

shoreline change digital shoreline analysis system linear regression rate Kalman filter end point rate

zmiana linii brzegowej cyfrowy system analizy linii brzegowej współczynnik regresji liniowej filtr Kalmana

Wydawca

Instytut Geofizyki PAN
Springer

Czasopismo

Acta Geophysica

Rocznik

2022

Tom

Vol. 70, no 4

Strony

1701--1715

Opis fizyczny

Bibliogr. 48 poz.

Twórcy

autor

Hossain Ariful

School of Oceanographic Studies, Jadavpur University, Kolkata 700032, India

autor

Mondal Ismail

School of Oceanographic Studies, Jadavpur University, Kolkata 700032, India
Department of Marine Science, University of Calcutta, Kolkata, West Bengal, India

autor

Thakur Sandeep

Department of Marine Science, University of Calcutta, Kolkata, West Bengal, India

autor

Linh Nguyen Thi Thuy

Institute of Applied Technology, Thu Dau Mot University, Binh Duong Province, Vietnam

autor

Anh Duong Tran

ta.duong@hutech.edu.vn

HUTECH University, 475A, Dien Bien Phu, Ward 25, Binh Thanh District, Ho Chi Minh City, Vietnam

Bibliografia

1. Barman NK, Chatterjee S, Khan A (2015) Trends of shoreline position: an approach to future prediction for Balasore Shoreline, Odisha, India. Open J of Mari Sci 5:13–25
2. Bhattacharya A, Sarkar S K, Bhattacharya A (2003) An assessment of coastal modification in the low lying tropical coast of north east India and role of natural and artificial forcings. In: International conference on estuaries and coasts, 2003, November pp. 9–11, Hangzhou, China
3. Chand P, Acharya P (2010) Shoreline change and sea level rise along coast of Bhitarkanika wildlife sanctuary, Orissa: an analytical approach of remote sensing and statistical techniques. Int J Geomat Geosci 1:436–454
4. Chen AJ, Chen CF, Chen KS (1995) Investigation of shoreline change and migration along Wai-San-Ding-Zou barrier Island, central western Taiwan. Geosci Remote Sens Symp 3:2097–2099
5. Ciritci D, Türk T (2020) Assessment of the Kalman filter-based future shoreline prediction method. Int J Environ Sci Technol 17:3801–3816. https://doi.org/10.1007/s13762-020-02733-w
6. Cooper JA, Jackson D, Nava F, Mckenna J, Malvarez G (2004) Storm impacts on an embayed high energy coastline, Western Ireland. Mar Geol 210:261–280
7. Crowell M, Leatherman SP, Buckley MK (1991) Historical shoreline change: error analysis and mapping accuracy. J Coast Res 7:839–852
8. Crowell M, Douglas BC, Leatherman SP (1997) On forecasting future US shoreline positions: a test of algorithms. J Coast Res 13(4):1245–1255
9. Cui B, Li X (2011) Coastline change of Yellow River estuary and its response to the sediment and runoff (1976–2005). Geomorphology 127:32–40
10. Deepika B, Avinash K, Jayappa KS (2014) Shoreline change rate estimation and its forecast: remote sensing, geographical information system and statistics-based approach. Int J Environ Sci Technol 11(2):395–416
11. Dey S, Ghosh P, Nayak A (2005) The influences of natural environment upon the evolution of sand dunes in tropical environment along Midnapur coastal area. India Indones J Geogr 37(1):51–68
12. Dolan R, Fenster MS, Holme SJ (1991) Temporal analysis of shoreline recession and accretion. J Coast Res 7:723–744
13. Fenster MS, Dolan R, Elder JF (1993) A new method for predicting shoreline positions from historical data. J Coast Res 9:147–171
14. Fenster MS, Dolan R, Morton RA (2001) Coastal storms and shoreline change: signal or noise? J Coast Res 17:714–720
15. Forbes D, Parkers G, Manson G, Ketch K (2004) Storms and shoreline retreat in the southern Gulf of St. Lawrence Mar Geol 210:169–204
16. Gopinath G (2010) Critical coastal issues of Sagar Island, east coast of India. Environ Monit Assess 160:555–561
17. Himmelstoss EA, Farris AS, Henderson RE, Kratzmann MG, Ergul A, Zhang O, Zichichi JL, Thieler ER (2018) Digital shoreline analysis system (version 5.0): U.S. Geological Survey software. Https: //code.usgs.gov/cch/dsas/
18. IMD- Cyclone e-Atlas (2011) Tracks of cyclones and depressions over North Indian Ocean (from 1891 onwards). Cyclone Warning and Research Centre, India Meteorological Department, Regional Meteorological Centre Chennai, Version 2, 48p
19. Jana A, Maiti S, Biswas A (2016) Analysis of short-term shoreline oscillations along Midnapur-Balasore Coast, Bay of Bengal, India: a study based on geospatial technology. Model Earth Syst Environ 2(2):64
20. Jayappa KS, Mitra D, Mishra AK (2006) Coastal geomorphological and land-use and land-cover study of Sagar Island, Bay of Bengal (India) using remotely sensed data. Int J Remote Sens 27:3671–3682
21. Kuleli T (2010) Quantitative analysis of shoreline changes at the mediterranean coast in turkey. Environ Monit Assess 167:387–397
22. Li R, Liu JK, Felus Y (2001) Spatial modelling and analysis for shoreline change detection and coastal erosion monitoring. Mar Geod 24:1–12
23. Long JW, Plant NG (2012) Extended Kalman Filter framework for forecasting shoreline evolution. Geophys Res Lett 39(1–6):L13603. https://doi.org/10.1029/2012GL052180
24. Long M, Leatherman SP, Buckley MK (1991) Historical shoreline change error analysis. J Coastal Res 7:839–852
25. Maiti S, Bhattacharya AK (2009) Shoreline change analysis and its application to prediction: a remote sensing and statistics based approach. Mar Geol 257:11–23
26. Mahapatra M, Ratheesh R, Rajawat AS (2014) Shoreline Change Analysis along the Coast of South Gujarat, India, Using Digital Shoreline Analysis System. J Indian Soc Remote Sens 42:869–876. https://doi.org/10.1007/s12524-013-0334-8
27. Mills JP, Buckley SJ, Mitchell HL, Clarke PJ, Edwards SJ (2005) A geomatics data integration technique for coastal change monitoring. Earth Surf Process Landf 30:651–664
28. Mondal I, Bandyopadhyay J (2014) Coastal zone mapping through geospatial technology for resource management of Indian Sundarban. West Bengal, India, Int J Remote Sens Appl 4(2):103–112. https://doi.org/10.14355/ijrsa.2014.0402.04
29. Mondal I, Thakur S (2020) Bandyopadhyay J (2019) Delineating lateral channel migration and risk zones of Ichamati River. West Bengal, India, J Clean Prod Elsevier 244:118740
30. Mondal I, Bandyopadhyay J, Dhara S (2016) Detecting shoreline changing trends using principle component analysis in Sagar Island, West Bengal, India, Journal of Spatial Information Research. Springer Nature 25(1):67–73. https://doi.org/10.1007/s41324-016-0076-0
31. Mondal I, Thakur S, Juliev M, Bandyopadhyay JD, TK. (2020) Spatio-temporal modelling of shoreline migration in Sagar Island. West Bengal, India, J Coast Conserv Springer 24(50):1–20. https://doi.org/10.1007/s11852-020-00768-2
32. Mondal I, Thakur SG, De PB, T.K. (2021a) Assessing the impacts of global sea level rise (SLRR) on the mangrove forests of indian sundarbans using geospatial technology. Geograp Inform Sci Land Resour Manag Wiley 11:209–228. https://doi.org/10.1002/9781119786375.ch11
33. Mondal I, Thakur S, De A, Bandyopadhyay J, De TK (2021b) Estimating water quality of sundarban coastal zone area using landsat series satellite data. River Health and Ecol South Asia (springer). https://doi.org/10.1007/978-3-030-83553-8_8.pp.155-172
34. Mukhopadhyay A, Mukherjee S, Mukherjee S, Ghosh S, Hazra S, Mitra D (2012) Automatic shoreline detection and future prediction: a case study on Puri coast, Bay of Bengal, India. Europe J Remote Sens 45:201–213
35. Mukhopadhyay A, Ghosh P, Chanda A, Ghosh A, Ghosh S, Das S, Ghosh T, Hazra S (2018) Threats to coastal communities of mahanadi delta due to imminent consequences of erosion – Present and near Future. Sci of the Tot Environ 637–638:717–729
36. Murali Krishna G, Mitra D, Mishra AK, Oyuntuya, Sh, Nageswra Rao K (2005) Evaluation of semi-automated image processing techniques for the identification and delineation of coastal edge using IRS, LISS-III Image – A Case Study on Sagar Island, East Coast of India. International Journal of Geoinformatics, Vol.1, No. 2
37. Nandi S, Ghosh M, Kundu A, Dutta D, Baks M (2016) Shoreline shifting and its prediction using remote sensing and GIS techniques: a case study of Sagar Island, West Bengal(India). J Coast Conserv 20:61–80. https://doi.org/10.1007/s11852-015-0418-4
38. Orford JD, Forbes DL, Jennings SC (2002) Organizational controls, typologies and time scales of paraglacial gravel-dominated coastal systems. Geomorphology 48:51–85
39. Pajak MJ, Leatherman S (2002) The high water line as shoreline indicator. J Coast Res 18:329–337
40. Paul AK (2002) Coastal geomorphology and environment: Sundarban Coastal Plain, Kanthi Coastal Plain. ACB Publication, Kolkata, Subarnarekha Delta plain
41. Purkait B (2009) Coastal erosion in response to wave dynamics operative in Sagar Island, Sundarban delta, India. Front Earth Sci Chin 3:21–33
42. Reshma KN, Murali RM (2018) Current status and decadal growth analysis of krishna - godavari delta regions using remote sensing. J Coastal Res 85:1416–1420
43. Santra A, Mitra D, Mitra S (2011) Spatial modeling using high resolution image for future shoreline prediction along Junput Coast, West Bengal, India. Geo Spatial Info Sci 14:157–163
44. Scott DB (2005) Coastal changes, rapid. In: Schwartz MI (ed) Encyclopedia of coastal sciences. Springer, the Netherlands, pp 253–255
45. Srivastava A, Niu X, Di K, Li R (2005) Shoreline modeling and erosion prediction, ASPRS 2005 Annual Conference B Geospatial Goes Global: From Your Neighborhood to the Whole Planet^ March 7– 11, 2005, Baltimore, Maryland
46. Thakur S, Maity D, Mondal I, Basumatary GG, De PB, T.K. (2020a) Assessment of changes in land use, land cover, and land surface temperature in the mangrove forest of Sundarbans, northeast coast of India. Environ Dev Sustain 22(3):1–29. https://doi.org/10.1007/s10668-020-00656-7
47. Thakur S, Mondal I, Bar I, Nandi S, Ghosh PB, Das P, De TK (2020b) Shoreline changes and its impact on the mangrove ecosystems of some islands of Indian Sundarbans, North-East coast of India. J Clean Prod ISSN 124764:0959–6526. https://doi.org/10.1016/j.jclepro.2020.124764
48. Wilson G, Özkan-Haller H, Holman R (2010) Data assimilation and bathymetric inversion in a 2dh surf zone model. J Geophys Res 115:C12057. https://doi.org/10.1029/2010JC006286

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-8e60c46c-4c90-47a0-b702-39c2bab0cde9