6533b7d3fe1ef96bd1261488
RESEARCH PRODUCT
Interpolation and Gap Filling of Landsat Reflectance Time Series
ÁLvaro Moreno-martínezMarco MonetaLuca MartinoNathaniel P. RobinsonBrady W. AllredGustau Camps VallsSteven W. Runningsubject
Signal Processing (eess.SP)Image fusion010504 meteorology & atmospheric sciencesComputer scienceMultispectral image0211 other engineering and technologies02 engineering and technology01 natural sciencesReflectivitySpectroradiometerFOS: Electrical engineering electronic engineering information engineeringTime seriesElectrical Engineering and Systems Science - Signal ProcessingScale (map)Image resolution021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingInterpolationDownscalingdescription
Products derived from a single multispectral sensor are hampered by a limited spatial, spectral or temporal resolutions. Image fusion in general and downscaling/blending in particular allow to combine different multiresolution datasets. We present here an optimal interpolation approach to generate smoothed and gap-free time series of Landsat reflectance data. We fuse MODIS (moderate-resolution imaging spectroradiometer) and Landsat data globally using the Google Earth Engine (GEE) platform. The optimal interpolator exploits GEE ability to ingest large amounts of data (Landsat climatologies) and uses simple linear operations that scale easily in the cloud. The approach shows very good results in practice, as tested over five sites with different vegetation types and climatic characteristics in the contiguous US.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2018-07-01 |