Predicting The Unseen: A Shoreline Shift Analysis And Prediction Along Mayo Bay, Davao Oriental
Fillmore D Masancay | Lea A. Jimenez
Discipline: environmental sciences
Abstract:
About 45%-60% of the world’s population resides in shoreline areas. Shoreline regions
are one of the most vulnerable areas to the effects of global warming. Positions of shorelines
are challenging to predict, but the trend of accretion and erosion can be determined using
statistical and geospatial techniques. Mati City is a major tourist destination for white sand
beaches and pristine waters. Shorelines along Mayo Bay are a source of income for the
local community. However, Mayo Bay has been subjected to shifts due to erosion. This
study aims to determine the trend of the shoreline shift in Mayo Bay from 2013 to 2023.
Landsat 8 OLI satellite images are used in this study. Results reveal that most shorelines
experienced erosion, with 97.26% erosion transects. The shoreline length has slightly
increased by 0.08% from 2013 to 2023 and is predicted to increase by 3.57% in 2063 and
11.51% by 2100. Barangay Lucatan shows the highest shoreline expansion, while Barangays
Bobon and Dahican exhibit the most erosion, with mean rates of -27.15 m/year and -23.60
m/year, respectively. With a classification accuracy of 89% and Root Mean Square Error (RMSE)
of 0.05, the study provides a reliable basis for Mayo Bay’s shoreline management. The findings
will inform erosion mitigation efforts and guide sustainable coastal management plans
for at-risk areas.
References:
- Ahmed, A., Drake, F., Nawaz, R., and Woulds, C. (2018). Where is the coast? Monitoring coastal land dynamics in Bangladesh: An integrated management approach using GIS and remote sensing techniques. Ocean and Coastal Management, 151, 10–24. https://doi.org/10.1016/j.ocecoaman.2017.10.030
- Alemayehu, F., Onwonga, R., Mwangi, J. K., and Wasonga, O. (2015). Assessment of shoreline changes in the period 1969–2010 in Watamu area, Kenya.
- Arjasakusuma, S., Kusuma, S. S., Saringatin, S., Wicaksono, P., Mutaqin, B. W., and Rafif, R. (2021). Shoreline dynamics in East Java Province, Indonesia, from 2000 to 2019 using multi-sensor remote sensing data. Land, 10(2), 100.
- Arkema, K. K., Guannel, G., Verutes, G., Wood, S. A., Guerry, A., Ruckelshaus, M., Kareiva, P., Lacayo, M., and Silver, J. M. (2013). Coastal habitats shield people and property from sea-level rise and storms. Nature Climate Change, 3(10), 913–918. http://dx.doi.org/10.1038/nclimate1944
- Bayram, B., Seker, D. Z., Acar, U., Yuksel, Y., Guner, H. A. A., and Cetin, I. (2013). An integrated approach to temporal monitoring of the shoreline and basin of Terkos Lake. Journal of Coastal Research, 29(6), 1427–1435.
- Bishop-Taylor, R., Nanson, R., Sagar, S., and Lymburner, L. (2021). Mapping Australia’s dynamic coastline at mean sea level using three decades of Landsat imagery. Remote Sensing of Environment, 267, 112734. DOI:10.1016/j.rse.2021.112734
- Boak, E. H., and Turner, I. L. (2005). Shoreline definition and detection: a review. Journal of Coastal Research, 21(4), 688–703. https://scispace.com/papers/shoreline-definition-and-detection-a-review-41qp0ofrkp
- Boye, C. B. (2015). Causes and trends in shoreline change in the Western Region of Ghana (Doctoral dissertation, University of Ghana, Ghana). http://197.255.68.203/handle/123456789/8444
- Chu, L., Oloo, F., Sudmanns, M., Tiede, D., Hölbling, D., Blaschke, T., and Teleoaca, I. (2020). Monitoring long-term shoreline dynamics and human activities in the Hangzhou Bay, China, combining daytime and nighttime EO data. Big Earth Data, 4(3), 242–264. DOI: 10.1080/20964471.2020.1740491, https://documentsdelivered.com/source/053/163/053163950.php
- Church, J. A., and White, N. J.(2011). Sea-level rise from the late 19th to the early 21st century. Surveys in Geophysics, 32, 585–602. https://doi.org/10.1007/s10712-011-9119-1
- Ciritci, D., and Türk, T. (2019). Automatic detection of shoreline change by geographical information system (GIS) and remote sensing in the Göksu Delta, Turkey. Journal of the Indian Society of Remote Sensing, 47, 233–243.
- Crowell, M., Leatherman, S. P., and Buckley, M. K. (1991). Historical shoreline change: error analysis and mapping accuracy. Journal of Coastal Research, 839–852. https://www.researchgate.net/publication/279557852_Historical_shoreline_change_error_analysis_and_mapping_accuracy
- Davidson, M. A., Lewis, R. P., and Turner, I. L. (2010). Forecasting seasonal to multi-year shoreline change. Coastal Engineering, 57(6), 620–629. https://doi.org/10.1016/j.coastaleng.2010.02.001
- Dellepiane, S., De Laurentiis, R., and Giordano, F. (2004). Coastline extraction from SAR images and a method for the evaluation of the coastline precision. Pattern Recognition Letters, 25(13), 1461–1470.
- Elnabwy, M. T., Elbeltagi, E., el Banna, M. M., Elshikh, M. M. Y., Motawa, I., and Kaloop, M. R. (2020). An approach based on Landsat images for shoreline monitoring to support integrated coastal management - A case study, Ezbet Elborg, Nile Delta, Egypt. ISPRS International Journal of Geo-Information, 9(4). https://doi.org/10.3390/ijgi9040199
- Fenster, M. S., Dolan, R., and Morton, R. A. (2001). Coastal storms and shoreline change: signal or noise? Journal of Coastal Research, 17, 714–720.
- Goksel, C., Senel, G., and Dogru, A. O. (2020). Determination of shoreline change along the Black Sea coast of Istanbul using remote sensing and GIS technology. Desalination and Water Treatment, 177, 1. https://doi.org/10.5004/dwt.2020.25847
- Jimenez, L., and Inabiogan, M. K. (2019a). A survey of cetaceans found in Mayo Bay, Davao Oriental, Philippines. Davao Research Journal, 12(2), 30–39.
- Jimenez, L. A., and Inabiogan, M. K. D. (2019b). A survey of marine turtles found in Davao Oriental, Philippines. Davao Research Journal, 12(2), 1–11.
- Jenness, J., and Wynne, J. J. (2007). Kappa analysis (kappa_stats.avx) extension for ArcView 3.x. Jenness Enterprises.
- Johnston, A., Slovinsky, P., and Yates, K. L. (2014). Assessing the vulnerability of coastal infrastructure to sea level rise using multi-criteria analysis in Scarborough, Maine (USA). Ocean & Coastal Management, 95, 176–188.
- Kale, S., and Acarli, D. (2019). Shoreline change monitoring in Atikhisar Reservoir by using remote sensing and geographic information system (GIS). Fresenius Environmental Bulletin, 28(5), 4329–4339.
- Kankara, R. S., Selvan, S. C., Markose, V. J., Rajan, B., and Arockiaraj, S. (2015). Estimation of long and short term shoreline changes along Andhra Pradesh coast using remote sensing and GIS techniques. Procedia Engineering, 116, 855–862.
- Landis, J. R., and Koch, G. G. (1977). A one-way components of variance model for categorical data. Biometrics, 33, 671–679. https://doi.org/10.2307/2529465
- Li, R., Liu, J. K., and Felus, Y. (2001). Spatial modelling and analysis for shoreline change detection and coastal erosion monitoring. Marine Geodesy, 24, 1–12. DOI:10.1080/01490410151079891
- Li, R., Di, K., and Ma, R. (2003). 3-D shoreline extraction from IKONOS satellite imagery. Marine Geodesy, 26(1–2), 107–115. https://doi.org/10.1080/01490410306699
- Louati, M., Saïdi, H., and Zargouni, F. (2015). Shoreline change assessment using remote sensing and GIS techniques: A case study of the Medjerda delta coast, Tunisia. Arabian Journal of Geosciences, 8, 4239-4255. https://doi.org/10.1007/s12517-014-1472-1
- Lu, D., and Weng, Q. (2007). A survey of image classification methods and techniques for improving classification performance. International Journal of Remote Sensing, 28(5), 823-870. https://doi.org/10.1080/01431160600746456
- Maiti, S., and Bhattacharya, A. K. (2009). Shoreline change analysis and its application to prediction: A remote sensing and statistics-based approach. Marine Geology, 257(1-4), 11-23. https://doi.org/10.1016/j.margeo.2008.10.006
- Masancay, F. D., Comendador, Y. J. F., Dizon, J. A. L., and Jallores, L. P. L. (2024). Geographic information system-based prioritization mapping for urban search and rescue in Poblacion, Davao City. Davao Research Journal, 15(3), 111-121. https://doi.org/10.59120/drj.v15i3.254
- 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. https://doi.org/10.1080/01431169608948714
- Mills, J. P., Buckley, S. J., Mitchell, H. L., Clarke, P. J., and Edwards, S. J. (2005). A geomatics data integration technique for coastal change monitoring. Earth Surface Processes and Landforms, 30(6), 651-664. https://doi.org/10.1002/esp.1165
- Mondal, I., Bandyopadhyay, J., and Dhara, S. (2017). Detecting shoreline changing trends using principal component analysis in Sagar Island, West Bengal, India. Spatial Information Research, 25, 67-73.
- 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.
- Mutaqin, B. W. (2017). Shoreline changes analysis in Kuwaru coastal area, Yogyakarta, Indonesia: An application of the digital shoreline analysis system (DSAS). International Journal of Sustainable Development and Planning, 12(7), 1203-1214. https://www.witpress.com/elibrary/sdp-volumes/12/7/1701
- NAMRIA. (2015). Philippine Rivers. National Mapping and Resource Information Authority, OCHA.
- Nandi, S., Ghosh, M., Kundu, A., Dutta, D., and Baksi, M. (2016). Shoreline shifting and its prediction using remote sensing and GIS techniques: A case study of Sagar Island, West Bengal (India). Journal of Coastal Conservation, 20, 61-80.
- Natih, N. M. N., Pasaribu, R. A., Sangadji, M. S., and Kusumaningrum, E. E. (2020). Study on shoreline changes using Landsat imagery in Sangsit Region, Bali Province. In IOP Conference Series: Earth and Environmental Science, 429(1), 012059. IOP Publishing. DOI 10.1088/1755-1315/429/1/012059 https://iopscience.iop.org/article/10.1088/1755-1315/429/1/012059
- Nayak, S. (2002). Use of satellite data in coastal mapping. Indian Cartographer, 22(147-157), 1. https://www.researchgate.net/publication/284414724_Use_of_satellite_data_in_coastal_mapping
- Oke, E. O., Adeyi, O., Okolo, B. I., Adeyi, J. A., Ayanyemi, J., Osoh, K. A., and Adegoke, T. S. (2020). Phenolic compound extraction from Nigerian Azadirachta indica leaves: Response surface and neuro-fuzzy modelling performance evaluation with Cuckoo search multi-objective optimization. Results in Engineering, 8, 100160. https://doi.org/10.1016/j.rineng.2020.100160
- Olmanson, L. G., Kloiber, S. M., Bauer, M. E., and Brezonik, P. L. (2001). Image processing protocol for regional assessments of lake water quality. Water Resources Center Technical Report, 14.
- Pajak, M. J., and Leatherman, S. (2002). The high-water line as shoreline indicator. Journal of Coastal Research, 329-337. https://www.jstor.org/stable/4299078
- Qiao, G., Mi, H., Wang, W., Tong, X., Li, Z., Li, T., and Hong, Y. (2018). 55-year (1960–2015) spatiotemporal shoreline change analysis using historical DISP and Landsat time series data in Shanghai. International Journal of Applied Earth Observation and Geoinformation, 68, 238-251. DOI:10.1016/j.jag.2018.02.009
- Rahman, A. F., Dragoni, D., and El-Masri, B. (2011). Response of the Sundarbans coastline to sea level rise and decreased sediment flow: A remote sensing assessment. Remote Sensing of Environment, 115(12), 3121-3128. DOI:10.1016/j.rse.2011.06.019
- Rasuly, A., Naghdifar, R., and Rasoli, M. (2010). Monitoring of Caspian Sea coastline changes using object-oriented techniques. Procedia Environmental Sciences, 2, 416-426. DOI:10.1016/j.proenv.2010.10.046
- Ruiz, L. A., Pardo, J. E., Almonacid, J., and Rodríguez, B. (2007, July). Coastline automated detection and multi-resolution evaluation using satellite images. In Proceedings of the Coastal Zone (Vol. 7, pp. 22-26). https://www.researchgate.net/publication/229042922_COASTLINE_AUTOMATED_DETECTION_AND_MULTI-RESOLUTION_EVALUATION_USING_SATELLITE_IMAGES
- Rwanga, S. S., and Ndambuki, J. M. (2017). Accuracy assessment of land use/land cover classification using remote sensing and GIS. International Journal of Geosciences, 8(04), 611.
- Schönau, M. C., Rudnick, D. L., Cerovecki, I., Gopalakrishnan, G., Cornuelle, B. D., McClean, J. L., and Qiu, B. (2015). The Mindanao Current: Mean structure and connectivity. Oceanography, 28(4), 34-45.
- Srivastava, A., Niu, X., Di, K., and Li, R. (2005, March). Shoreline modeling and erosion prediction. In Proceedings of the ASPRS Annual Conference (pp. 7-11).
- Sryberko, A. (2023). Analysis of the application of the Normalized Difference Water Index (NDWI) in the Odesa Bay Area of the Black Sea. Materials of the MCND Conferences, (03.11.2023; Sumy, Ukraine), 190-192.
- SunStar Davao. (2020). 3 bays in Mati among most beautiful bays in the world. SunStar. https://www.sunstar.com.ph/davao/local-news/3-bays-in-mati-among-most-beautiful-bays-in-the-world
- Szmytkiewicz, M., Biegowski, J., Kaczmarek, L. M., Okroj, T., Ostrowski, R., Pruszak, Z., and Skaja, M. (2000). Coastline changes nearby harbour structures: Comparative analysis of one-line models versus field data. Coastal Engineering, 40(2), 119-139.
- Thakur, S., Dey, D., Das, P., Ghosh, P., and De, T. (2017). Shoreline change detection using remote sensing in the Bakkhali Coastal Region, West Bengal, India. Indian Journal of Geosciences, 71, 611-626.
- 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.
- USGS. (2024). Landsat 8. https://www.usgs.gov/landsat-missions/landsat-8
- Xu, N. (2018). Detecting coastline change with all available Landsat data over 1986–2015: A case study for the state of Texas, USA. Atmosphere, 9(3), 107.
- Yadav, A., Dodamani, B. M., and Dwarakish, G. S. (2021). Shoreline analysis using Landsat-8 satellite image. ISH Journal of Hydraulic Engineering, 27(3), 347-355.
- Yadav, A., Dodamani, B., and Dwarakish, G. S. (2017). Shoreline Change: A Review.
- Zhang, K., Douglas, B. C., and Leatherman, S. P. (2004). Global warming and coastal erosion. Climatic Change, 64, 41-58.
- Zuzek, P. J., Nairn, R. B., and Thieme, S. J. (2003). Spatial and temporal considerations for calculating shoreline change rates in the Great Lakes Basin. Journal of Coastal Research, 125-146.
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