.sits_timeline_match_indexes

Timeline of input observations (vector).

timeline

List of breaks to be applied to the input data set.

ref_dates

For correct classification, the time series of the input data
 should be aligned to that of the reference data set
 (usually a set of patterns).
 This function aligns these data sets so that shape
 matching works correctly

internal

A set of tools for working with satellite image time series, both as individual data or as part of data cubes.
Builds data cubes from collections in AWS, Brazil Data Cube, and Digital Earth Africa.
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

Lorena Santos

Alexandre Carvalho

Pedro Andrade

Karine Ferreira

Alber Sanchez

Gilberto Queiroz

.sits_timeline_match_indexes function

Find indexes in a timeline that match the reference dates — .sits_timeline_match_indexes

Find indexes in a timeline that match the reference dates

.sits_timeline_match_indexes: Find indexes in a timeline that match the reference dates

Description

Usage

Arguments

Value