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Interpolation and Gap Filling of Landsat Reflectance Time Series
- Source :
- IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
- Publication Year :
- 2020
-
Abstract
- 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.
- Subjects :
- Electrical Engineering and Systems Science - Signal Processing
Subjects
Details
- Database :
- arXiv
- Journal :
- IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
- Publication Type :
- Report
- Accession number :
- edsarx.2012.07987
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.1109/IGARSS.2018.8517503