Using Landsat Phenology Curves to Characterize Fire Impacted Forests in South Carolina, USA

Authors: Miranda Rose*, University of Tennessee, Nicholas N. Nagle, University of Tennessee at Knoxville
Topics: Land Use and Land Cover Change, Remote Sensing
Keywords: Landsat phenology, forest disturbance, land cover change
Session Type: Paper
Day: 4/6/2019
Start / End Time: 1:10 PM / 2:50 PM
Room: Balcony B, Marriott, Mezzanine Level
Presentation File: No File Uploaded


Quantifying forest change following a disturbance is a key but challenging aspect of ecological monitoring. Forests respond to disturbances in different ways, depending on forest and disturbance type as well as disturbance severity. Landsat data are frequently used to assess these responses over large geographic areas and through time. Intra-annual vegetation patterns derived from Landsat data provide valuable information related to the timing of various vegetation events, or phenology, throughout a year, including length of growing season, onset of greenness, and timing of senescence. Using all available cloudless pixels from Landsat 5, 7, and 8, we will construct annual vegetation phenology curves in fire-impacted forests in southeastern South Carolina, USA. We will compare phenology signals in pre-fire, post-fire, and unburned forest sites for the two dominant forest species groups in the study region: loblolly-shortleaf pine and oak-gum-cypress. We will also discuss some of the challenges associated with deriving phenology curves from Landsat data and some potential modeling techniques to address those challenges.

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