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This paper presents the comprehensive dataset of satellite data, shoreline detection methodology, and shoreline changes in the coast of Haiphong province from 1987 to 2018. Landsat satellite images from 1987 to 2018 were gathered. With this dataset, based on the metadata of images, only the images with the similar water level (~1.8 m) and high quality were selected for detecting the shoreline using modification of normalized difference index (MNDWI). These generations of shoreline will be processed using GIS technique for retrieving the detail shoreline changes in the tidal dominated estuarine region as Haiphong coast. It should be noted that in the study area, the change of shoreline mostly comes from the human activities as reclaimation or aquaculture. However, the landward movement of Hoang Chau warp proved that the sea forcings are dominant compared to them from rivers in the Haiphong bay.
 M. A. Marfai, H. Almohammad, S. Dey, B. Susanto, L. King, Coastal Dynamic and Shoreline Mapping: Multi-Sources Spatial Data Analysis in Semarang Indonesia, Environmental Monitoring and Assessment, Vol. 142, Issue 1-3, 2008, pp. 297-308, https://doi.org/10.1007/s10661-007-9929-2.
 E. Tamassoki, H. Amiri, Z. Soleymani, Monitoring of Shoreline Changes Using Remote Sensing (Case Study: Coastal City of Bandar Abbas), 7th IGRSM International Remote Sensing & GIS Conference and Exhibition, IOP Conf. Series: Earth and Enviromental Science, No. 20, 2014, pp. 012-023.
 B. Shin, K. Kim, Estimation of Shoreline Change Using High Resolution Images, 8th International Conference on Asian and Pacific Coasts, Procedia Engineering, No. 116, 2015, pp. 994-1001.
 T. A. Tu, T. D. Thanh, Several Results of Erosion and Deposition in the Haiphong Coast, Proceedings of 5-Year Establishment of Faculty of Coastal Engineering, Thuyloi University (2008) 143-150 (in Vietnamese).
 K. C. Nguyen, M. Umeyama, V. U. Dinh, Long-term Morphological Changes and Hydrodynamics of Tidal Dominant Coastal Zone in the Hai Phong Estuary, Viet Nam, Journal of Janpan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol. 68, No. 4, 2012, pp. I_85-I_90, http://dx.doi.org/10.2208/jscejhe.68.I_85.
 T. T. Van, T. T. Binh, Application of Remote Sensing for Shoreline Change Detection in Cuu Long Estuary, VNU Journal of Science: Earth and Environmental Sciences, Vol. 25, 2009, pp. 217-222, https://js.vnu.edu.vn/EES/article/view/1879.
 S. K. McFeeters, The Use of the Normalized Difference Water Index (NDWI) in the Delineation of Open Water Features, Remote Sensing Letters, Vol. 17, 1996, pp. 1425-1432, https://doi.org/10.1080/01431169608948714.
 H. Xu, Modification of Normalized Difference Water Index (NDWI) to Enhance Open Water Features in Remotely Sensed Imagery, International Journal of Remote Sensing, Vol. 27, No. 14, 2006, pp. 3025-3033, https://doi.org/10.1080/01431160600589179.
 N. Xu, Detecting Coastline Change with All Available Landsat Data over 1986 – 2015: A Case Study for the State of Texas, USA, Atmosphere, Vol. 9, No. 107, 2018, pp. 1-20, https://doi.org/10.3390/atmos9030107.
 Q. Guo, R. Pu, J. Li, and J. Cheng, A Weighted Normalized Difference Water Index for Water Extraction Using Landsat Imagery, International Journal of Remote Sensing, Vol. 38, No. 19, 2017, pp. 5430-5445, https://doi.org/10.1080/01431161.2017.1341667.
 C. Lin, C. C. Wu, K. Tsogt, Y. C. Ouyang, C. I. Chang, Effects of Atmospheric Correction and Pansharpening on LULC Classification Accuracy Using Worldview-2 Imagery, Information Processing in Agriculture, Vol. 2, No. 1, 2015, pp. 25-36, https://doi.org/10.1016/j.inpa.2015.01.003.
 C. Song, C. E. Woodcock, K. C. Seto, M. P. Lenney, S. A. Macomber, Classification and Change Detection Using Landsat TM Data: When and How to Correct Atmospheric Effects? Remote Sensing of Environment, Vol. 75, No. 2, 2001, pp. 230-244, https://doi.org/10.1016/S0034-4257(00)00169-3.