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The R package gapfill

The package provides tools to fill missing values in satellite data. It can be used to gap-fill, e.g., MODIS NDVI data, and is helpful for the development of new gap-fill algorithms. The predictions are based on a subset-predict procedure, i.e., each missing value is predicted separately by (1) subsetting the data to a neighborhood around it and (2) predict the values based on that subset.

Features of the package

  • Gap-filling can be executed in parallel.
  • Users may define Subset and Predict functions and run alternative prediction algorithms with little effort. See ?Extend for more information and examples.
  • The visualization of space-time data is simplified through the ggplot2 based function Image.

Get started

The package can be installed with

R> install.packages("gapfill")

To get started see the example in

R> ?Gapfill

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Install

install.packages('gapfill')

Monthly Downloads

249

Version

0.9.6-1

License

GPL (>= 2)

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Last Published

February 12th, 2021

Functions in gapfill (0.9.6-1)

Score

Score Columns of a Matrix Containing NAs by its Values
ArrayAround

Subset an Array with 4 dimensions
EstimateQuantile

Estimate the Quantile of a Missing Value
Image

Image Panels
Extend

Implement an Alternative Gap-fill Algorithm
Gapfill

Main Function for Gap-Filling
Array2Matrix

Convert an Array with 4 Dimensions into a Matrix
Index

Index Conversions
Validate

Validation with RMSE
Subset-Predict

Subset and Predict Functions
gapfill-package

Overview
ndvi

NDVI Data from Alaska