gapfill-package

Gapfill-Package

Gapfill-package

gapfill-Package

The package provides tools to fill-in missing values in satellite data.
It can be used to gap-fill, e.g., MODIS NDVI data and
is helpful when developing new gap-fill algorithms.
The methods are tailored to data (images) observed at equally-spaced points in time. 
This is typically the case for MODIS land surface products and AVHRR NDVI data, among others. 
The predictions of the missing values are based on a subset-predict procedure, i.e.,
each missing value is predicted separately by
(1) selecting subsets of the data that are in a neighborhood around the missing point and
(2) predicting the missing value based on the subset.
The main function of the package is <code><a rd-options="" href="/link/Gapfill?package=gapfill&version=0.9.6-1" data-mini-rdoc="gapfill::Gapfill">Gapfill</a></code>.

package

Tools to fill missing values in satellite data and to develop new
gap-fill algorithms. The methods are tailored to data (images) observed
at equally-spaced points in time. The package is illustrated with MODIS
NDVI data.

gapfill

Fill Missing Values in Satellite Data

Florian Gerber

gapfill-package function

<ul>
<li>Gap-filling can be executed in parallel.</li>
<li>Users may define new <code><a rd-options="" href="/link/Subset?package=gapfill&version=0.9.6-1" data-mini-rdoc="gapfill::Subset">Subset</a></code> and <code><a rd-options="" href="/link/Predict?package=gapfill&version=0.9.6-1" data-mini-rdoc="gapfill::Predict">Predict</a></code> functions
and run alternative prediction algorithms with little effort.
See <a rd-options="" href="/link/Extend?package=gapfill&version=0.9.6-1" data-mini-rdoc="gapfill::Extend">Extend</a> for more information and examples.</li>
<li>Visualization of space-time data are simplified through the <code>ggplot2</code>-based
function <code><a rd-options="" href="/link/Image?package=gapfill&version=0.9.6-1" data-mini-rdoc="gapfill::Image">Image</a></code>.</li>
</ul>

Features

The package provides tools to fill-in missing values in satellite data.
It can be used to gap-fill, e.g., MODIS NDVI data and
is helpful when developing new gap-fill algorithms.
The methods are tailored to data (images) observed at equally-spaced points in time. 
This is typically the case for MODIS land surface products and AVHRR NDVI data, among others. 
The predictions of the missing values are based on a subset-predict procedure, i.e.,
each missing value is predicted separately by
(1) selecting subsets of the data that are in a neighborhood around the missing point and
(2) predicting the missing value based on the subset.
The main function of the package is <code><a rd-options='' href='Gapfill'>Gapfill</a></code>.

gapfill-package: Overview

Description

Arguments

Features

References

See Also