sits_debug_log

.sits_debug_log

.sits_debug

.sits_debug_log: (internal) logs to a CSV file the following values:<ul>
<li>date_time: event date and time</li>
<li>pid: process identifier</li>
<li>event: event name</li>
<li>elapsed_time: duration (in seconds) from the last log call</li>
<li>mem_used: session used memory (in MB)</li>
<li>max_mem_used: maximum memory used (in MB) from first log call</li>
<li>tag: any character string to be registered</li>
</ul>Each event will be logged in one row in the log file.
The log file name will be the same as the base name of the current
session's temporary directory.
.sits_debug: When called without parameters retrieves the
current debug flag value. The sits write log files when the debug
flag is TRUE

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

sits_debug_log function

<dl><dt>output_dir</dt>
<dd>Output directory to write log file</dd>
<dt>event</dt>
<dd>The name of the event to be logged</dd>
<dt>key</dt>
<dd>A key describing the value.</dd>
<dt>value</dt>
<dd>Any value to be logged. The value will be converted
to string and escaped.</dd>
<dt>flag</dt>
<dd>A logical value to set the debug flag</dd></dl>

Arguments

Rolf Simoes, <a href="/link/rolf.simoes%40inpe.br?package=sits&version=1.1.0" data-mini-rdoc="sits::rolf.simoes@inpe.br">rolf.simoes@inpe.br</a>

Author

sits log functions — sits_debug_log

<dl>

<dt>output_dir</dt>
<dd>Output directory to write log file</dd>


<dt>event</dt>
<dd>The name of the event to be logged</dd>


<dt>key</dt>
<dd>A key describing the value.</dd>


<dt>value</dt>
<dd>Any value to be logged. The value will be converted
to string and escaped.</dd>


<dt>flag</dt>
<dd>A logical value to set the debug flag</dd>

</dl>

Rolf Simoes, <a href='mailto:rolf.simoes@inpe.br'>rolf.simoes@inpe.br</a>

sits_debug_log: sits log functions

Description

Usage

Value

Arguments

Author