Shape selection in Landsat time series: A tool for monitoring forest dynamicsAuthor(s): Gretchen G. Moisen; Mary C. Meyer; Todd A. Schroeder; Xiyue Liao; Karen G. Schleeweis; Elizabeth A. Freeman; Chris Toney
Source: Global Change Biology. doi: 10.1111/gcb.13358.
Publication Series: Scientific Journal (JRNL)
Station: Rocky Mountain Research Station
View PDF (2.0 MB)
Related Research Highlights
Shape Selection in Landsat Time Series
We present a new methodology for fitting nonparametric shape-restricted regression splines to time series of Landsat imagery for the purpose of modeling, mapping, and monitoring annual forest disturbance dynamics over nearly three decades. For each pixel and spectral band or index of choice in temporal Landsat data, our method delivers a smoothed rendition of the trajectory constrained to behave in an ecologically sensible manner, reflecting one of seven possible ‘shapes’. It also provides parameters summarizing the patterns of each change including year of onset, duration, magnitude, and pre- and postchange rates of growth or recovery. Through a case study featuring fire, harvest, and bark beetle outbreak, we illustrate how resultant fitted values and parameters can be fed into empirical models to map disturbance causal agent and tree canopy cover changes coincident with disturbance events through time. We provide our code in the R package ShapeSelectForest on the Comprehensive R Archival Network and describe our computational approaches for running the method over large geographic areas. We also discuss how this methodology is currently being used for forest disturbance and attribute mapping across the conterminous United States.
- You may send email to email@example.com to request a hard copy of this publication.
- (Please specify exactly which publication you are requesting and your mailing address.)
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
Moisen, Gretchen G.; Meyer, Mary C.; Schroeder, Todd A.; Liao, Xiyue; Schleeweis, Karen G.; Freeman, Elizabeth A.; Toney, Chris. 2016. Shape selection in Landsat time series: A tool for monitoring forest dynamics. Global Change Biology. doi: 10.1111/gcb.13358.
Keywordsattribution, canopy change activities, change agents, forest disturbance, landcover change, R package, regression splines, tree canopy cover
- ShapeSelectForest: a new r package for modeling landsat time series
- Use of Landsat-based monitoring of forest change to sample and assess the role of disturbance and regrowth in the carbon cycle at continental scales
- Mapping timing, extent, type and magnitude of disturbances across the national forest system, 1990–2011
XML: View XML