e-sensing/sits: Satellite Image Time Series Analysis

A set of tools for working with satellite image time series. Supports data retrieval from a WTSS (web time series service) and other data sets. Provides different visualisation methods for image time series. Provides smoothing methods for noisy time series. Enables different clustering methods, including dendrograms and SOM. Matches noiseless patterns with noisy time series using the TWDTW method for shape recognition. Provide machine learning methods for time series classification, including SVM, LDA, QDA, GLM, Lasso, Random Forests and Deep Learning.

Getting started

Package details

MaintainerPedro Andrade <[email protected]>
LicenseGPL-2 | file LICENSE
Version1.12.6
URL https://github.com/e-sensing/sits/
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("e-sensing/sits")
e-sensing/sits documentation built on July 18, 2019, 3:51 p.m.