{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T22:59:17Z","timestamp":1771023557157,"version":"3.50.1"},"reference-count":135,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,2,11]],"date-time":"2023-02-11T00:00:00Z","timestamp":1676073600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Union","award":["BSB 963 \u201cProtect-Streams-4-Sea\u201d"],"award-info":[{"award-number":["BSB 963 \u201cProtect-Streams-4-Sea\u201d"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The alleviation of landslide impacts is a priority since they have the potential to cause significant economic damage as well as the loss of human life. Mitigation can be achieved effectively by using warning systems and preventive measures. The development of improved methodologies for the analysis and understanding of landslides is at the forefront of this scientific field. Identifying effective monitoring techniques (accurate, fast, and low cost) is the pursued objective. Geographic Information Systems (GISs) and remote sensing techniques are utilized in order to achieve this goal. In this study, four methodological approaches (manual landslide delineation, a segmentation process, and two mapping models, specifically object-based image analysis and pixel-based image analysis (OBIA and PBIA)) were proposed and tested with the use of Unmanned Aerial Vehicles (UAVs) and data analysis methods to showcase the state and evolution of landslides. The digital surface model (DSM)-based classification approach was also used to support the aforementioned approaches. This study focused on streamside landslides at research sites in three different countries: Greece, Romania, and Turkey. The results highlight that the areas of the OBIA-based classifications were the most similar (98%) to our control (manual) classifications for all three sites. The landslides\u2019 perimeters at the Lefkothea and Chirlesti sites showed similar results to the OBIA-based classification (93%), as opposed to the Sirtoba site, where the perimeters of the landslides from OBIA-based classification were not well corroborated by the perimeters in the manual classification. Deposition areas that extend beyond the trees were revealed by the DSM-based classification. The results are encouraging because the methodology can be used to monitor landslide evolution with accuracy and high performance in different regions. Specifically, terrains that are difficult to access can be surveyed by UAVs because of their ability to take aerial images. The obtained results provide a framework for the unitary analysis of landslides using modern techniques and tools.<\/jats:p>","DOI":"10.3390\/rs15041006","type":"journal-article","created":{"date-parts":[[2023,2,13]],"date-time":"2023-02-13T01:48:56Z","timestamp":1676252936000},"page":"1006","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Identification of Streamside Landslides with the Use of Unmanned Aerial Vehicles (UAVs) in Greece, Romania, and Turkey"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1481-2849","authenticated-orcid":false,"given":"Mehmet","family":"Yavuz","sequence":"first","affiliation":[{"name":"Department of Forest Engineering, Faculty of Forestry, Artvin Coruh University, 08100 Artvin, Turkey"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6430-719X","authenticated-orcid":false,"given":"Paschalis","family":"Koutalakis","sequence":"additional","affiliation":[{"name":"Geomorphology, Edaphology and Riparian Areas Laboratory (GERi Lab), Department of Forestry and Natural Environment Sciences, International Hellenic University, 66100 Drama, Greece"}]},{"given":"Daniel Constantin","family":"Diaconu","sequence":"additional","affiliation":[{"name":"Ministry of Investments and European Projects, 013681 Bucharest, Romania"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6118-2256","authenticated-orcid":false,"given":"Georgios","family":"Gkiatas","sequence":"additional","affiliation":[{"name":"Geomorphology, Edaphology and Riparian Areas Laboratory (GERi Lab), Department of Forestry and Natural Environment Sciences, International Hellenic University, 66100 Drama, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9358-3326","authenticated-orcid":false,"given":"George N.","family":"Zaimes","sequence":"additional","affiliation":[{"name":"Geomorphology, Edaphology and Riparian Areas Laboratory (GERi Lab), Department of Forestry and Natural Environment Sciences, International Hellenic University, 66100 Drama, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3350-2897","authenticated-orcid":false,"given":"Mustafa","family":"Tufekcioglu","sequence":"additional","affiliation":[{"name":"Department of Forest Engineering, Faculty of Forestry, Artvin Coruh University, 08100 Artvin, Turkey"}]},{"given":"Maria","family":"Marinescu","sequence":"additional","affiliation":[{"name":"Buzau Ialomita Water Administration, 120208 Buzau, Romania"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"647","DOI":"10.1007\/s41324-018-0209-8","article-title":"A review of landform classification methods","volume":"26","author":"Mokarram","year":"2018","journal-title":"Spat. 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