README.md

In pvts-approach/PVts: photosynthetic vegetation time series manipulation in R.

PVts-β

The PVts-β approach is implemented in R with the 'PVts' package. This algorithm will allow to detect disturbances in the forests using all the available Landsat set. In fact, it can also be run with sensors such as MODIS (Moderate Resolution Imaging Spectroradiometer). In essence, the PVts-β approach is an algorithm that does not model the seasonal component in time series, instead it only requires calculating the mean and standard deviation of the time series itself to detect disturbances. Therefore, the PVts-β approach is a method: i) simple and intelligent that does not model seasonality, ii) has only one calibration parameter and iii) can be easily implemented by any standard user.

For any work you will submit, credits from this algorithm must be given to:

Tarazona, Y., Mantas, V.M., Pereira, A.J.S.C. (2018). Improving tropical deforestation detection through using photosynthetic vegetation time series – (PVts-β). Ecological Indicators, 94, 367–379.

Please note that the 'PVts' project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

Installation

You can install the released version of PVts from CRAN with:

install.packages("PVts")

Example

This is a basic example which shows you how to solve a common problem:

library(PVts)
## basic example code

pvts-approach/PVts documentation built on July 1, 2019, 4:59 p.m.