Shoreline change monitoring using the Digital Shoreline Analysis System along the coast of Gujarat, India

Year 2025, Volume: 12 Issue: 1, 15 - 27, 31.03.2025

Foram Jadeja , Kauresh Vachhrajani

Abstract

The shoreline is a multifaceted feature of the Earth’s surface and is highly susceptible to both natural and anthropogenic influences. Hence, accurate and frequent shoreline change monitoring is essential for determining the dynamic nature of coastal areas. This paper highlights the shoreline changes in the Gujarat coast from 1993 to 2023 with 10-year interval multitemporal Landsat satellite datasets. The modified normalized difference water index was used to extract the shoreline by differentiating the land-water boundary. The shoreline change rates were calculated by applying statistical techniques, such as the end point rate, linear regression rate, net shoreline movement, and weighted linear regression, using a digital shoreline analysis system. In this study, a total of 8782 transects were employed on the considered coastline stretch at an equal distance of 100 meters. Almost half of the transects (49.7%) showed an accretion trend, while erosion was observed in 23.6% of the transects. The remaining 26.7% of transects were in stable condition. This study was performed on a regional scale with significant detailed information that can help further research on sustainable coastal zone management and planning.

Keywords

Coastal erosion and accretion, Shoreline change, DSAS, Remote sensing and GIS, Gujarat coast

References

• Addo, K. A., Jayson-Quashigah, P. N., and Kufogbe, K. S. 2011. Quantitative analysis of shoreline change using medium resolution satellite imagery in Keta, Ghana. Marine Science, 1(1), 1-9.
• Alesheikh, A. A., Ghorbanali, A., and Nouri, N. 2007. Coastline change detection using remote sensing. International Journal of Environmental Science & Technology, 4, 61-66.
• Basheer Ahammed, K. K., Mahendra, R. S., and Pandey, A. C. 2016. Coastal vulnerability assessment for Eastern Coast of India, Andhra Pradesh by using geo-spatial technique. Geoinformatics & Geostatistics: An Overview, 4(3).
• Beluru Jana, A., and Hegde, A. V. 2016. GIS based approach for vulnerability assessment of the Karnataka coast, India. Advances in Civil Engineering, 2016.
• Braud, D. H., and Feng, W. 1998. Semi-automated construction of the Louisiana coastline digital land/water boundary using Landsat Thematic Mapper satellite imagery. Louisiana Applied Oil Spill Research and Development Program, OS2 RAPD Technical Report Series, 97(002).
• Burak, S., Dogan, E., & Gazioglu, C. (2004). Impact of urbanization and tourism on coastal environment. Ocean & Coastal Management, 47(9-10), 515-527.
• Çelik, O. İ., & Gazioğlu, C. (2020). Coastline difference measurement (CDM) method. International Journal of Environment and Geoinformatics, 7(1), 1-5.
• CERC. 1973. Shore protection manual (Vol. 1). US Army Coastal Engineering Research Center.
• Chen, C., Bu, J., Zhang, Y., Zhuang, Y., Chu, Y., Hu, J., and Guo, B. 2019. The application of the tasseled cap transformation and feature knowledge for the extraction of coastline information from remote sensing images. Advances in Space Research, 64(9), 1780-1791.
• Coco, G., Senechal, N., Rejas, A., Bryan, K. R., Capo, S., Parisot, J. P., Brown, J.A. and MacMahan, J. H., 2014. Beach response to a sequence of extreme storms. Geomorphology, 204, pp.493-501.
• Dey, M., Shanmuga Priyaa, S. and Jena, B. K. 2021. A Shoreline Change Detection (2012-2021) and forecasting Using Digital Shoreline Analysis System (DSAS) Tool: A Case Study of Dahej Coast, Gulf of Khambhat, Gujarat, India. Indonesian Journal of Geography, 53(2).
• El-Asmar, H. M., and Hereher, M. E. 2011. Change detection of the coastal zone east of the Nile Delta using remote sensing. Environmental Earth Sciences, 62, 769-777.
• El-Sharnouby, B. A., El-Alfy, K. S., Rageh, O. S., and El-Sharabasy, M. M. 2015. Coastal changes along Gamasa beach, Egypt. J Coast Zone Manag, 17, 393.
• Feyisa, G. L., Meilby, H., Fensholt, R., and Proud, S. R. 2014. Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery. Remote sensing of environment, 140, 23-35.
• Frazier, P. S., and Page, K. J. 2000. Water body detection and delineation with Landsat TM data. Photogrammetric engineering and remote sensing, 66(12), 1461-1468.
• Gazioğlu, C. (2018). Biodiversity, coastal protection, promotion and applicability investigation of the ocean health index for Turkish seas. International Journal of Environment and Geoinformatics, 5(3), 353-367.
• Giardino, C., Bresciani, M., Villa, P., and Martinelli, A. 2010. Application of remote sensing in water resource management: the case study of Lake Trasimeno, Italy. Water resources management, 24, 3885-3899.
• Guariglia, A., Buonamassa, A., Losurdo, A., Saladino, R., Trivigno, M. L., Zaccagnino, A., and Colangelo, A. 2006. A multisource approach for coastline mapping and identification of shoreline changes.
• Gupta, M. 2014. Monitoring shoreline changes in the Gulf of Khambhat, India during 1966–2004 using RESOURCESAT-1 LISS-III. Open Journal of Remote Sensing and Positioning, 1(1), 27-37.
• Himmelstoss, E., Henderson, R. E., Kratzmann, M. G., and Farris, A. S. 2018. Digital shoreline analysis system (DSAS) version 5.0 user guide (No. 2018-1179). US Geological Survey.
• Hossain, M. S., Yasir, M., Wang, P., Ullah, S., Jahan, M., Hui, S., and Zhao, Z. 2021. Automatic shoreline extraction and change detection: A study on the southeast coast of Bangladesh. Marine geology, 441, 106628.
• Jayanthi, M., Thirumurthy, S., Samynathan, M., Duraisamy, M., Muralidhar, M., Ashokkumar, J., and Vijayan, K. K. 2018. Shoreline change and potential sea level rise impacts in a climate hazardous location in southeast coast of India. Environmental monitoring and assessment, 190, 1-14.
• Kabuth, A. K., Kroon, A., and Pedersen, J. B. 2014. Multidecadal shoreline changes in Denmark. Journal of Coastal Research, 30(4), 714-728.
• Kankara, R. S., Murthy, M. R., and Rajeevan, M. 2018. National Assessment of Shoreline changes along Indian Coast: Status report for 26 years (1990–2016). NCCR Publication.
• Kumar, T. S., Mahendra, R. S., Nayak, S., Radhakrishnan, K., and Sahu, K. C. 2010. Coastal vulnerability assessment for Orissa State, east coast of India. Journal of Coastal research, 26(3), 523-534.
• Li, R. D., and Ma, R. 2001. The 4th International Symposium on Computer mapping and GIS for Coastal Zones Management–A comparative study of shoreline Mapping techniques. Halifax, Nova Scotia, Canada. McFeeters, S. K. 1996. The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. International journal of remote sensing, 17(7), 1425-1432.
• Misra, A., and Balaji, R. 2015. Decadal changes in the land use/land cover and shoreline along the coastal districts of southern Gujarat, India. Environmental Monitoring and Assessment, 187, 1-13.
• Mohan, G. S., and Jairaj, P. G. 2014. Coastal vulnerability assessment along Kerala coast using remote sensing and GIS. International Journal of Scientific & Engineering Research, 5(7), 228-234.
• Mujabar, P. S., and Chandrasekar, N. 2013. Shoreline change analysis along the coast between Kanyakumari and Tuticorin of India using remote sensing and GIS. Arabian Journal of Geosciences, 6, 647-664.
• Nassar, K., Mahmod, W. E., Fath, H., Masria, A., Nadaoka, K., & Negm, A. 2019. Shoreline change detection using DSAS technique: Case of North Sinai coast, Egypt. Marine Georesources & Geotechnology, 37(1), 81-95.
• Pajak, M. J., and Leatherman, S. 2002. The high water line as shoreline indicator. Journal of coastal research, 329-337.
• Pilkey, O. H., and Hume, T. M. 2001. The shoreline erosion problem: lessons from the past. Water and Atmosphere, 9(2), 22-23.
• Ratheesh, R., Rajput, P., Bhatti, H., Rajawat, A. S., and Rajak, D. R. 2023. Quantification of shoreline changes along the entire Indian coast using Indian Remote Sensing satellite images of 2004-06 and 2014-16. Current Science (00113891), 124(5).
• Roy, S., Mahapatra, M., and Chakraborty, A. 2018. Shoreline change detection along the coast of Odisha, India using digital shoreline analysis system. Spatial Information Research, 26, 563-571.
• Santos, C. A. G., do Nascimento, T. V. M., Mishra, M., and da Silva, R. M. 2021. Analysis of long-and short-term shoreline change dynamics: A study case of João Pessoa city in Brazil. Science of the Total Environment, 769, 144889.
• Shen, L., and Li, C. 2010. Water body extraction from Landsat ETM+ imagery using adaboost algorithm. In 2010 18th International Conference on Geoinformatics (pp. 1-4). IEEE.
• Splinter, K. D., Turner, I. L., Davidson, M. A., Barnard, P., Castelle, B., and Oltman‐Shay, J. 2014. A generalized equilibrium model for predicting daily to interannual shoreline response. Journal of Geophysical Research: Earth Surface, 119(9), 1936-1958.
• Sutariya, S., Hirapara, A., Meherbanali, M., Tiwari, M. K., Sıngh, V., & Kalubarme, M. (2021). Soil moisture estimation using Sentinel-1 SAR data and land surface temperature in Panchmahal district, Gujarat State. International Journal of Environment and Geoinformatics, 8(1), 65-77.
• Thieler, E. R., Himmelstoss, E. A., Zichichi, J. L., and Ergul, A. 2009. The Digital Shoreline Analysis System (DSAS) version 4.0-an ArcGIS extension for calculating shoreline change (No. 2008-1278). US Geological Survey.
• Tran Thi, V., Tien Thi Xuan, A., Phan Nguyen, H., Dahdouh-Guebas, F., and Koedam, N. 2014. Application of remote sensing and GIS for detection of long-term mangrove shoreline changes in Mui Ca Mau, Vietnam. Biogeosciences, 11(14), 3781-3795.
• Ustun, B., Ekercin, S., and Musaoglu, N. 2004. A performance analysis of the classification and manual digiting methods for the detection of coast line by using satelllite image data. Remote sensing in transition, 143-148.
• Vitousek, S., Barnard, P. L., Limber, P., Erikson, L., and Cole, B. 2017. A model integrating longshore and cross‐shore processes for predicting long‐term shoreline response to climate change. Journal of Geophysical Research: Earth Surface, 122(4), 782-806.
• Xu, H. 2006. Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. International journal of remote sensing, 27(14), 3025-3033.
• Yan, D., Yao, X., Li, J., Qi, L., and Luan, Z. 2021. Shoreline change detection and forecast along the Yancheng coast using a digital shoreline analysis system. Wetlands, 41, 1-16.