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dc.contributor.authorKingfield, Darrel M.
dc.contributor.authorde Beurs, Kirsten M.
dc.date.accessioned2017-06-09T16:51:35Z
dc.date.available2017-06-09T16:51:35Z
dc.date.copyright2017/04/01
dc.date.issued2017
dc.identifier.issn1558-8424
dc.identifier.otherams-75414.pdf
dc.identifier.urihttp://onlinelibrary.yabesh.ir/handle/yetl/4217748
dc.description.abstractultispectral satellite imagery provides a spaceborne perspective on tornado damage identification; however, few studies have explored how tornadoes alter the spectral signature of different land-cover types. In part 1 of this study, Landsat surface reflectance is used to explore how 17 tornadoes modify the spectral signature, NDVI, and ?Tassled Cap? parameters inside forest (N = 16), grassland (N = 10), and urban (N = 17) land cover. Land cover influences the magnitude of change observed, particularly in spring/summer imagery, with most tornado-damaged surfaces exhibiting a higher median reflectance in the visible and shortwave infrared, and a lower median reflectance in the near-infrared spectral ranges. These changes result in a higher median Tasseled Cap brightness, lower Tasseled Cap greenness and wetness, and lower NDVI relative to unaffected areas. Other factors affecting the magnitude of change in reflectance include season, vegetation condition, land-cover heterogeneity, and tornado strength. While vegetation indices like NDVI provide a quick way to identify damage, they have limited utility when monitoring recovery because of the cyclical seasonal vegetation cycle. Since tornado damage provides an analogous spectral signal to that of forest clearing, NDVI is compared with a forest disturbance index (DI) across a 5-yr Landsat climatology surrounding the 27 April 2011 tornado outbreak in part 2 of this study. Preoutbreak DI values remain relatively stable across seasons. In the five tornado-damaged areas evaluated, DI values peak within 6 months followed by a decline coincident with ongoing recovery. DI-like metrics provide a seasonally independent mechanism to fill the gap in identifying damage and monitoring recovery.
dc.publisherAmerican Meteorological Society
dc.titleLandsat Identification of Tornado Damage by Land Cover and an Evaluation of Damage Recovery in Forests
dc.typeJournal Paper
dc.journal.volume56
dc.journal.issue4
dc.journal.titleJournal of Applied Meteorology and Climatology
dc.identifier.doi10.1175/JAMC-D-16-0228.1
dc.journal.fristpage965
dc.journal.lastpage987
dc.treeJournal of Applied Meteorology and Climatology:;2017:;volume( 056 ):;issue: 004
dc.contenttypeFulltext


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