Code Record


[DOI: 10.21982/nkd7-cd05] gapfill
Gerber, Florian
Tools to predict 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.

Code Link:
Code Size: 206474 bytes
Code MD5 Checksum: 501a7acb19c9b8f42b5fe9edd1b2a355

Appears in: Gerber, F., de Jong, R., Schaepman, M. E., Schaepman-Strub, G., and Furrer, R. Predicting missing values in spatio-temporal remote sensing data. IEEE Transactions on Geoscience and Remote Sensing, 56(5):2841–2853, 2018. doi: 10.1109/TGRS.2017.2785240

See Also:,

Code Languages: C++, R

To compile code: The statistical software R is needed (runs on most Mac, Windows, and Linux operating systems).

Sensor Categories: Optical Radiometer, Optical Imager, Optical Spectrometer

Instrument Processing and Calibration Categories: Optical Radiometer, Optical Imager, Optical Spectrometer, Other - Sensor

Keywords: gapfill, gap-fill, prediction, missing values, low quality values, R, clouds, parallel processing, parallel, R package,