.sits_timeline_class_info

Description on the data being classified.

data

Samples used for training the classification model.

samples

Time series classification requires a series of steps:
(a) Provide labelled samples that will be used as training data.
(b) Provide information on how the classification will be performed,
 including data timeline,and start and end dates per interval.
(c) Clean the training data to ensure it meets the specifications
 of the classification info.
(d) Use the clean data to train a machine learning classifier.
(e) Classify non-labelled data sets.
In this set of steps, this function provides support for step (b).
It requires the user to provide a timeline, the classification interval,
and the start and end dates of the reference period. T
he results is a tibble with information that allows the user
to perform steps (c) to (e).

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_class_info function

Define the information required for classifying time series — .sits_timeline_class_info

Define the information required for classifying time series

.sits_timeline_class_info: Define the information required for classifying time series

Description

Usage

Arguments

Value