Gap-Filling of NDVI Satellite Data Using Tucker Decomposition: Exploiting Spatio-Temporal Patterns Article Swipe
Andri Freyr Þórðarson
,
Andreas Baum
,
Mónica García
,
Sergio M. Vicente‐Serrano
,
Anders Stockmarr
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/rs13194007
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/rs13194007
Remote sensing satellite images in the optical domain often contain missing or misleading data due to overcast conditions or sensor malfunctioning, concealing potentially important information. In this paper, we apply expectation maximization (EM) Tucker to NDVI satellite data from the Iberian Peninsula in order to gap-fill missing information. EM Tucker belongs to a family of tensor decomposition methods that are known to offer a number of interesting properties, including the ability to directly analyze data stored in multidimensional arrays and to explicitly exploit their multiway structure, which is lost when traditional spatial-, temporal- and spectral-based methods are used. In order to evaluate the gap-filling accuracy of EM Tucker for NDVI images, we used three data sets based on advanced very-high resolution radiometer (AVHRR) imagery over the Iberian Peninsula with artificially added missing data as well as a data set originating from the Iberian Peninsula with natural missing data. The performance of EM Tucker was compared to a simple mean imputation, a spatio-temporal hybrid method, and an iterative method based on principal component analysis (PCA). In comparison, imputation of the missing data using EM Tucker consistently yielded the most accurate results across the three simulated data sets, with levels of missing data ranging from 10 to 90%.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/rs13194007
- https://www.mdpi.com/2072-4292/13/19/4007/pdf?version=1633771940
- OA Status
- gold
- Cited By
- 8
- References
- 64
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3206149017
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- OpenAlex ID
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https://openalex.org/W3206149017Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/rs13194007Digital Object Identifier
- Title
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Gap-Filling of NDVI Satellite Data Using Tucker Decomposition: Exploiting Spatio-Temporal PatternsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2021Year of publication
- Publication date
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2021-10-06Full publication date if available
- Authors
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Andri Freyr Þórðarson, Andreas Baum, Mónica García, Sergio M. Vicente‐Serrano, Anders StockmarrList of authors in order
- Landing page
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https://doi.org/10.3390/rs13194007Publisher landing page
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https://www.mdpi.com/2072-4292/13/19/4007/pdf?version=1633771940Direct link to full text PDF
- Open access
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- OA status
-
goldOpen access status per OpenAlex
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https://www.mdpi.com/2072-4292/13/19/4007/pdf?version=1633771940Direct OA link when available
- Concepts
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Missing data, Computer science, Imputation (statistics), Normalized Difference Vegetation Index, Data set, Remote sensing, Principal component analysis, Satellite, Data mining, Artificial intelligence, Geography, Geology, Climate change, Aerospace engineering, Engineering, Machine learning, OceanographyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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8Total citation count in OpenAlex
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2025: 3, 2024: 3, 2023: 2Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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