timeline_2013_2014

<p>The timeline for the time series used in the examples
   that use data for one year classification.
   There are 23 instances from 2013-09-14 until 2014-08-29.</p>

datasets

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

timeline_2013_2014 function

<p>A vector with 23 dates in YYYY-MM-DD format.</p>

Format

The timeline for the sequence of images one year (2013 to 2014) — timeline_2013_2014

The timeline for the sequence of images one year (2013 to 2014)

timeline_2013_2014: The timeline for the sequence of images one year (2013 to 2014)

Description

Usage

Arguments

Format