gapfill-package: Overview
Description
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 Gapfill.
Features
- Gap-filling can be executed in parallel.
- Users may define new
Subset and Predict functions
and run alternative prediction algorithms with little effort.
See Extend for more information and examples.
- Visualization of space-time data are simplified through the
ggplot2-based
function Image.
References
F. Gerber, R. Furrer, G. Schaepman-Strub, R. de Jong, M. E. Schaepman, 2016,
Predicting missing values in spatio-temporal satellite data.
http://arxiv.org/abs/1605.01038.