Other packages > Find by keyword >

ShapeSelectForest  

Shape Selection for Landsat Time Series of Forest Dynamics
View on CRAN: Click here


Download and install ShapeSelectForest package within the R console
Install from CRAN:
install.packages("ShapeSelectForest")

Install from Github:
library("remotes")
install_github("cran/ShapeSelectForest")

Install by package version:
library("remotes")
install_version("ShapeSelectForest", "1.7")



Attach the package and use:
library("ShapeSelectForest")
Maintained by
Xiyue Liao
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-06-01
Latest Update: 2023-08-19
Description:
Landsat satellites collect important data about global forest conditions. Documentation about Landsat's role in forest disturbance estimation is available at the site . By constrained quadratic B-splines, this package delivers an optimal shape-restricted trajectory to a time series of Landsat imagery for the purpose of modeling annual forest disturbance dynamics to behave in an ecologically sensible manner assuming one of seven possible "shapes", namely, flat, decreasing, one-jump (decreasing, jump up, decreasing), inverted vee (increasing then decreasing), vee (decreasing then increasing), linear increasing, and double-jump (decreasing, jump up, decreasing, jump up, decreasing). The main routine selects the best shape according to the minimum Bayes information criterion (BIC) or the cone information criterion (CIC), which is defined as the log of the estimated predictive squared error. The package also provides parameters summarizing the temporal pattern including year(s) of inflection, magnitude of change, pre- and post-inflection rates of growth or recovery. In addition, it contains routines for converting a flat map of disturbance agents to time-series disturbance maps and a graphical routine displaying the fitted trajectory of Landsat imagery.
How to cite:
Xiyue Liao (2015). ShapeSelectForest: Shape Selection for Landsat Time Series of Forest Dynamics. R package version 1.7, https://cran.r-project.org/web/packages/ShapeSelectForest. Accessed 07 Nov. 2024.
Previous versions and publish date:
1.0 (2015-06-01 01:06), 1.1 (2015-09-06 19:30), 1.2 (2015-12-26 00:41), 1.3 (2016-10-28 19:12), 1.4 (2020-03-27 23:00), 1.5 (2022-08-15 20:30), 1.6 (2023-08-08 09:30)
Other packages that cited ShapeSelectForest R package
View ShapeSelectForest citation profile
Other R packages that ShapeSelectForest depends, imports, suggests or enhances
Complete documentation for ShapeSelectForest
Functions, R codes and Examples using the ShapeSelectForest R package
Some associated functions: ShapeSelectForest-package . edf0s . f2a.map.jpeg . f2a.raster . f2p.raster . flat2annual . flat2parameter . getedf0 . plotshape . shape . shapeparams . ymat . 
Some associated R codes: shape.R .  Full ShapeSelectForest package functions and examples
Downloads during the last 30 days
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
bacondecomp  
Goodman-Bacon Decomposition
Decomposition for differences-in-differences with variation in treatment timing from Goodman-Bacon ...
Download / Learn more Package Citations See dependency  
con2aqi  
Calculate the AQI from Pollutant Concentration
To calculate the AQI (Air Quality Index) from pollutant concentration data. O3, PM2.5, PM10, CO, SO ...
Download / Learn more Package Citations See dependency  
robregcc  
Robust Regression with Compositional Covariates
We implement the algorithm estimating the parameters of the robust regression model with composition ...
Download / Learn more Package Citations See dependency  

23,092

R Packages

198,677

Dependencies

62,675

Author Associations

23,089

Publication Badges

© Copyright 2022 - present. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA