.sits_timeline_raster_indexes

cube

<p>Tibble with samples used for classification.</p>

samples

<p>Given a list of time indexes that indicate the start and end
             of the values to be extracted to classify each band,
             obtain a list of indexes that will be used to extract values
             from a combined distance tibble
             (which has all the bands put together).</p>

internal

A set of tools for working with satellite image time series, both as individual data or as part of data cubes.
Supports data retrieval from a web time series service (WTSS), raster bricks and cubes from the Brazilan Data Cube.
Provides different visualisation methods for image time series.
Provides smoothing methods for noisy time series.
Includes functions for smoothing based on Bayesian inference.
Enables different clustering methods, including dendrograms and self-organized maps (SOM).
Matches noiseless patterns with noisy time series using the time-weighted dynamic time warping (TWDTW) method for shape recognition.
Provides machine learning methods for time series classification, including support vector machines (SVM), random forests and deep learning.
Minimum recommended requirements: 8 GB RAM and 1 CPU dual-core.

Gilberto Camara

sits

Satellite Image Time Series Analysis for Remote Sensing Data Cubes

Rolf Simoes

Felipe Souza

Pedro Andrade

Lorena Santos

Alexandre Carvalho

Gilberto Queiroz

Karine Ferreira

Alber Sanchez

Victor Maus

.sits_timeline_raster_indexes function

Provide a list of indexes to extract data from a raster-derived
       data table for classification — .sits_timeline_raster_indexes

Provide a list of indexes to extract data from a raster-derived
       data table for classification

.sits_timeline_raster_indexes: Provide a list of indexes to extract data from a raster-derived data table for classification

Description

Usage

Arguments

Value