.sits_coverage_raster_classified

Tibble with metadata about the input RasterBrick objects.

raster.tb

Samples used for training the classification model.

samples.tb

Generic name of the files that will contain the RasterLayers.

file

interval

Takes a tibble containing metadata about a set of RasterBrick objects
containing time series (each Brick has information for one band) and creates a
set of RasterLayers to store the classification result. Each RasterLayer corresponds
to one time step. The time steps are specified in a list of dates.

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.

Pedro Andrade

sits

Satellite Image Time Series Analysis

Rolf Simoes

Gilberto Camara

Victor Maus

Alexandre Carvalho

Lorena Santos

Gilberto Queiroz

Alber Sanchez

Luiz Assis

Adeline Marinho

.sits_coverage_raster_classified function

Create a set of RasterLayer objects to store time series classification results — .sits_coverage_raster_classified

Create a set of RasterLayer objects to store time series classification results

.sits_coverage_raster_classified: Create a set of RasterLayer objects to store time series classification results

Description

Usage

Arguments

Value