{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T17:40:29Z","timestamp":1760118029805,"version":"build-2065373602"},"reference-count":32,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2024,12,23]],"date-time":"2024-12-23T00:00:00Z","timestamp":1734912000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Japan International Cooperation Agency"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This study evaluates the effectiveness of an enhanced satellite-based method for estimating the construction years of Cambodian road bridges. By leveraging Landsat satellite imagery and the Normalized Difference Water Index 2 (NDWI_2), in combination with the sequential t-test analysis of regime shifts (STARS) method, this research identifies significant shifts in NDWI_2 values indicative of bridge construction activities. A total of 423 road bridges were analyzed, with the accuracy of the method assessed using the Mean Absolute Error (MAE). The improved method demonstrated considerable accuracy, with 64.3% of bridges classified as high-accuracy (MAE of 0\u20135), 20.8% as moderate-accuracy (MAE of 6\u201310), and 14.9% as low-accuracy (MAE of 11\u201330). Factors such as the bridge length and data quality were found to influence accuracy. A regression analysis comparing the actual bridge age to damage ratings closely aligned with the model using the estimated bridge age to damage ratings, suggesting that the the estimated bridge age obtained from the estimated construction years, in conjunction with damage ratings, provide a reliable basis for evaluating the damage trends of road bridges. The findings underscore the method\u2019s potential for broader applications in regions with limited infrastructure data. Although effective for medium to large bridges, challenges remain for smaller bridges due to spatial resolution limitations. Recommendations for further enhancement include refining data preprocessing, segmenting bridges by size, and incorporating auxiliary datasets. This research highlights the critical role of accurate construction year estimation in effective bridge infrastructure monitoring and maintenance planning.<\/jats:p>","DOI":"10.3390\/rs16244796","type":"journal-article","created":{"date-parts":[[2024,12,23]],"date-time":"2024-12-23T09:13:38Z","timestamp":1734945218000},"page":"4796","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Assessing the Effectiveness of Estimating the Construction Years of Cambodia Road Bridges Using an Improved Satellite-Based Method"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7199-4741","authenticated-orcid":false,"given":"Bennie","family":"Hamunzala","sequence":"first","affiliation":[{"name":"Division of Engineering and Policy for Sustainable Environment, Graduate School of Engineering, Hokkaido University, Sapporo 060-8628, Hokkaido, Japan"}]},{"given":"Hiroto","family":"Goto","sequence":"additional","affiliation":[{"name":"Division of Engineering and Policy for Sustainable Environment, Graduate School of Engineering, Hokkaido University, Sapporo 060-8628, Hokkaido, Japan"}]},{"given":"Koji","family":"Matsumoto","sequence":"additional","affiliation":[{"name":"Division of Civil Engineering, Faculty of Engineering, Hokkaido University, Sapporo 060-8628, Hokkaido, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Sastrawiria, R.P., and Seigo, N. 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