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  "Title": "Shape Selection for Landsat Time Series of Forest Dynamics",
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  "Description": "Landsat satellites collect important data about global\nforest conditions. Documentation about Landsat's role in forest\ndisturbance estimation is available at the site\n<https://landsat.gsfc.nasa.gov/>. By constrained quadratic\nB-splines, this package delivers an optimal shape-restricted\ntrajectory to a time series of Landsat imagery for the purpose\nof modeling annual forest disturbance dynamics to behave in an\necologically sensible manner assuming one of seven possible\n\"shapes\", namely, flat, decreasing, one-jump (decreasing, jump\nup, decreasing), inverted vee (increasing then decreasing), vee\n(decreasing then increasing), linear increasing, and\ndouble-jump (decreasing, jump up, decreasing, jump up,\ndecreasing). The main routine selects the best shape according\nto the minimum Bayes information criterion (BIC) or the cone\ninformation criterion (CIC), which is defined as the log of the\nestimated predictive squared error. The package also provides\nparameters summarizing the temporal pattern including year(s)\nof inflection, magnitude of change, pre- and post-inflection\nrates of growth or recovery. In addition, it contains routines\nfor converting a flat map of disturbance agents to time-series\ndisturbance maps and a graphical routine displaying the fitted\ntrajectory of Landsat imagery.",
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  "Author": "Xiyue Liao [aut, cre]\n(<https://orcid.org/0000-0002-4508-9219>), Mary Meyer [aut],\nElizabeth Freeman [aut], Gretchen Moisen [aut]",
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