.gc_regularize

Creates cubes with regular time intervals
 using the gdalcubes package.

internal

An end-to-end toolkit for land use and land cover classification
using big Earth observation data, based on machine learning methods
applied to satellite image data cubes, as described in Simoes et al (2021) <doi:10.3390/rs13132428>.
Builds regular data cubes from collections in AWS, Microsoft Planetary Computer,
Brazil Data Cube, and Digital Earth Africa using the STAC protocol <https://stacspec.org/>
and the 'gdalcubes' R package <doi:10.3390/data4030092>.
Supports visualization methods for images and time series and
smoothing filters for dealing with noisy time series.
Includes functions for quality assessment of training samples using self-organized maps
as presented by Santos et al (2021) <doi:10.1016/j.isprsjprs.2021.04.014>.
Provides machine learning methods including support vector machines,
random forests, extreme gradient boosting, multi-layer perceptrons,
temporal convolutional neural networks <doi:10.3390/rs11050523>,
residual networks <arxiv:1809.04356>, and temporal attention encoders
<arXiv:2007.00586>.
Performs efficient classification of big Earth observation data cubes and includes
functions for post-classification smoothing based on Bayesian inference, and
methods for uncertainty assessment. Enables best
practices for estimating area and assessing accuracy of land change as
recommended by Olofsson et al(2014) <doi:10.1016/j.rse.2014.02.015>.
Minimum recommended requirements: 16 GB RAM and 4 CPU dual-core.

Gilberto Camara

sits

Satellite Image Time Series Analysis for Earth Observation Data
Cubes

Rolf Simoes

Felipe Souza

Lorena Santos

Pedro Andrade

Karine Ferreira

Alber Sanchez

Gilberto Queiroz

.gc_regularize function

<dl><dt>cube</dt>
<dd>Data cube whose spacing of observation
times is not constant and will be regularized
by the <code>gdalcubes</code> package.</dd>
<dt>period</dt>
<dd>ISO8601 time period for regular data cubes
with number and unit, e.g., "P16D" for 16 days.
Use "D", "M" and "Y" for days, month and year.</dd>
<dt>res</dt>
<dd>Spatial resolution of the regularized images.</dd>
<dt>roi</dt>
<dd>A named <code>numeric</code> vector with a region of interest.</dd>
<dt>output_dir</dt>
<dd>Valid directory where the
regularized images will be written.</dd>
<dt>multicores</dt>
<dd>Number of cores used for regularization.</dd>
<dt>progress</dt>
<dd>Show progress bar?</dd></dl>

Arguments

Build a regular data cube from an irregular one — .gc_regularize

<dl>

<dt>cube</dt>
<dd>Data cube whose spacing of observation
times is not constant and will be regularized
by the <code>gdalcubes</code> package.</dd>


<dt>period</dt>
<dd>ISO8601 time period for regular data cubes
with number and unit, e.g., "P16D" for 16 days.
Use "D", "M" and "Y" for days, month and year.</dd>


<dt>res</dt>
<dd>Spatial resolution of the regularized images.</dd>


<dt>roi</dt>
<dd>A named <code>numeric</code> vector with a region of interest.</dd>


<dt>output_dir</dt>
<dd>Valid directory where the
regularized images will be written.</dd>


<dt>multicores</dt>
<dd>Number of cores used for regularization.</dd>


<dt>progress</dt>
<dd>Show progress bar?</dd>

</dl>

Build a regular data cube from an irregular one

.gc_regularize: Build a regular data cube from an irregular one

Description

Usage

Value

Arguments

References