{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T10:35:48Z","timestamp":1782124548692,"version":"3.54.5"},"reference-count":46,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T00:00:00Z","timestamp":1739923200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Faculty of Social Sciences, Srinakharinwirot University","award":["313\/2566"],"award-info":[{"award-number":["313\/2566"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Coastal erosion is a critical environmental challenge in the Upper Gulf of Thailand, driven by both natural processes and human activities. This study analyzes 35 years (1988\u20132023) of shoreline changes using geoinformatics, machine learning algorithms (Random Forest, Support Vector Machine, Maximum Likelihood, Minimum Distance), and the Digital Shoreline Analysis System (DSAS). The results show that the Random Forest algorithm, utilizing spectral bands and indices (NDVI, NDWI, MNDWI, SAVI), achieved the highest classification accuracy (98.17%) and a Kappa coefficient of 0.9432, enabling reliable delineation of land and water boundaries. The extracted annual shorelines were validated with high accuracy, yielding RMSE values of 13.59 m (2018) and 8.90 m (2023). The DSAS analysis identified significant spatial and temporal variations in shoreline erosion and accretion. Between 1988 and 2006, the most intense erosion occurred in regions 4 and 5, influenced by sea-level rise, strong monsoonal currents, and human activities. However, from 2006 to 2018, erosion rates declined significantly, attributed to coastal protection structures and mangrove restoration. The period 2018\u20132023 exhibited a combination of erosion and accretion, reflecting dynamic sediment transport processes and the impact of coastal management measures. Over time, erosion rates declined due to the implementation of protective structures (e.g., bamboo fences, rock revetments) and the natural expansion of mangrove forests. However, localized erosion remains persistent in low-lying, vulnerable areas, exacerbated by tidal forces, rising sea levels, and seasonal monsoons. Anthropogenic activities, including urban development, mangrove deforestation, and aquaculture expansion, continue to destabilize shorelines. The findings underscore the importance of sustainable coastal management strategies, such as mangrove restoration, soft engineering coastal protection, and integrated land-use planning. This study demonstrates the effectiveness of combining machine learning and geoinformatics for shoreline monitoring and provides valuable insights for coastal erosion mitigation and enhancing coastal resilience in the Upper Gulf of Thailand.<\/jats:p>","DOI":"10.3390\/ijgi14020094","type":"journal-article","created":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T11:49:27Z","timestamp":1739965767000},"page":"94","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Geoinformatics and Machine Learning for Shoreline Change Monitoring: A 35-Year Analysis of Coastal Erosion in the Upper Gulf of Thailand"],"prefix":"10.3390","volume":"14","author":[{"given":"Chakrit","family":"Chawalit","sequence":"first","affiliation":[{"name":"Department of Geography, Faculty of Social Sciences, Srinakharinwirot University, Bangkok 10110, Thailand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5267-9380","authenticated-orcid":false,"given":"Wuttichai","family":"Boonpook","sequence":"additional","affiliation":[{"name":"Department of Geography, Faculty of Social Sciences, Srinakharinwirot University, Bangkok 10110, Thailand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-0938-8023","authenticated-orcid":false,"given":"Asamaporn","family":"Sitthi","sequence":"additional","affiliation":[{"name":"Department of Geography, Faculty of Social Sciences, Srinakharinwirot University, Bangkok 10110, Thailand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2795-806X","authenticated-orcid":false,"given":"Kritanai","family":"Torsri","sequence":"additional","affiliation":[{"name":"Hydro-Informatics Institute, Ministry of Higher Education, Science, Research and Innovation, Bangkok 10900, Thailand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daroonwan","family":"Kamthonkiat","sequence":"additional","affiliation":[{"name":"Department of Geography, Faculty of Liberal Arts, Thammasat University, Rangsit Campus, Khlong Nueng 12120, Thailand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0447-8223","authenticated-orcid":false,"given":"Yumin","family":"Tan","sequence":"additional","affiliation":[{"name":"School of Transportation Science and Engineering, Beihang University, Beijing 100191, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Apised","family":"Suwansaard","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, Faculty of Engineering, Rajamangala University of Technology Rattanakosin, Salaya, Nakhon Pathom 73170, Thailand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9452-4387","authenticated-orcid":false,"given":"Attawut","family":"Nardkulpat","sequence":"additional","affiliation":[{"name":"Department of Geography, Faculty of Social Sciences, Srinakharinwirot University, Bangkok 10110, Thailand"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,2,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Li, K., Zhang, L., Chen, B., Zuo, J., Yang, F., and Li, L. 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