{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T12:48:43Z","timestamp":1773751723233,"version":"3.50.1"},"reference-count":21,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2013,3,18]],"date-time":"2013-03-18T00:00:00Z","timestamp":1363564800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Climate change has increased the occurrence of heavy storms that cause damage to forests. After a storm, it is necessary to obtain knowledge about the injured trees quickly in order to detect and aid in collecting the fallen trees and estimate the total damage. The objective in this study was to develop an automatic method for storm damage detection based on comparisons of digital surface models (DSMs), where the after-storm DSM was derived by automatic image matching using high-altitude photogrammetric imagery. This DSM was compared to a before-storm DSM, which was computed using national airborne laser scanning (ALS) data. The developed method was tested using imagery collected in extreme illumination conditions after winter storms on 8 January 2012 in Finland. The image matching yielded a high-quality surface model of the forest areas, which were mainly coniferous and mixed forests. The entire set of major damage forest test areas was correctly classified using the method. Our results showed that airborne, high-altitude photogrammetry is a promising tool for automating the detection of forest storm damage. With modern photogrammetric cameras, large areas can be collected efficiently, and the imagery also provides visual, stereoscopic support for various forest storm damage management tasks. Developing methods that work in different seasons are becoming more important, due to the increase in the number of natural disasters.<\/jats:p>","DOI":"10.3390\/rs5031405","type":"journal-article","created":{"date-parts":[[2013,3,18]],"date-time":"2013-03-18T13:58:38Z","timestamp":1363615118000},"page":"1405-1424","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":46,"title":["Automatic Storm Damage Detection in Forests Using High\u2011Altitude Photogrammetric Imagery"],"prefix":"10.3390","volume":"5","author":[{"given":"Eija","family":"Honkavaara","sequence":"first","affiliation":[{"name":"Finnish Geodetic Institute, Geodeetinrinne 2, 02430 Masala, Finland"}]},{"given":"Paula","family":"Litkey","sequence":"additional","affiliation":[{"name":"Finnish Geodetic Institute, Geodeetinrinne 2, 02430 Masala, Finland"}]},{"given":"Kimmo","family":"Nurminen","sequence":"additional","affiliation":[{"name":"Finnish Geodetic Institute, Geodeetinrinne 2, 02430 Masala, Finland"}]}],"member":"1968","published-online":{"date-parts":[[2013,3,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"G00E02","DOI":"10.1029\/2008JG000911","article-title":"Forest disturbance and recovery: A general review in the context of spaceborne remote sensing of impacts on aboveground biomass and canopy structure","volume":"114","author":"Frolking","year":"2009","journal-title":"J. Geophys. Res."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1080\/07038992.2000.10855271","article-title":"Modelling deciduous forest ice storm damage using aerial CIR imagery and hemispheric photography","volume":"26","author":"Pellikka","year":"2000","journal-title":"Can. J. Remote Sens"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1190","DOI":"10.3390\/rs4051190","article-title":"Advances in forest inventory using airborne laser scanning","volume":"4","author":"Yu","year":"2012","journal-title":"Remote Sens"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2919","DOI":"10.3390\/rs4102919","article-title":"Laser scanning in forests","volume":"4","author":"Holopainen","year":"2012","journal-title":"Remote Sens"},{"key":"ref_5","unstructured":"Rahman, M. (2011, January 10\u201315). Integration of Remote Sensing and GIS for Tree Damage Estimation from Natural Disasters. 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No 59."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/5\/3\/1405\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:45:37Z","timestamp":1760219137000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/5\/3\/1405"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,3,18]]},"references-count":21,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2013,3]]}},"alternative-id":["rs5031405"],"URL":"https:\/\/doi.org\/10.3390\/rs5031405","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,3,18]]}}}