AVHRR NDVI Compositing Method Comparison and Generation of Multi-Decadal Time Series—A TIMELINE Thematic Processor
Remote sensing image composites are crucial for a wide range of remote sensing applications, such as multi-decadal time series analysis. The Advanced Very High Resolution Radiometer (AVHRR) instrument has provided daily data since the early 1980s at a spatial resolution of 1 km, allowing analyses of...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/6/1631 |
| _version_ | 1797609207962271744 |
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| author | Sarah Asam Christina Eisfelder Andreas Hirner Philipp Reiners Stefanie Holzwarth Martin Bachmann |
| author_facet | Sarah Asam Christina Eisfelder Andreas Hirner Philipp Reiners Stefanie Holzwarth Martin Bachmann |
| author_sort | Sarah Asam |
| collection | DOAJ |
| description | Remote sensing image composites are crucial for a wide range of remote sensing applications, such as multi-decadal time series analysis. The Advanced Very High Resolution Radiometer (AVHRR) instrument has provided daily data since the early 1980s at a spatial resolution of 1 km, allowing analyses of climate change-related environmental processes. For monitoring vegetation conditions, the Normalized Difference Vegetation Index (NDVI) is the most widely used metric. However, to actually enable such analyses, a consistent NDVI time series over the AVHRR time-span needs to be created. In this context, the aim of this study is to thoroughly assess the effect of different compositing procedures on AVHRR NDVI composites, as no standard procedure has been established. Thirteen different compositing methods have been implemented; daily, decadal, and monthly composites over Europe and Northern Africa have been calculated for the year 2007, and the resulting data sets have been thoroughly evaluated according to six criteria. The median approach was selected as the best-performing compositing algorithm considering all the investigated aspects. However, the combination of the NDVI value and viewing and illumination angles as the criteria for the best-pixel selection proved to be a promising approach, too. The generated NDVI time series, currently ranging from 1981–2018, shows a consistent behavior and close agreement to the standard MODIS NDVI product. The conducted analyses demonstrate the strong influence of compositing procedures on the resulting AVHRR NDVI composites. |
| first_indexed | 2024-03-11T05:57:18Z |
| format | Article |
| id | doaj.art-71672c0054d84bf8b8e17a6b81bae1b3 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T05:57:18Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-71672c0054d84bf8b8e17a6b81bae1b32023-11-17T13:39:48ZengMDPI AGRemote Sensing2072-42922023-03-01156163110.3390/rs15061631AVHRR NDVI Compositing Method Comparison and Generation of Multi-Decadal Time Series—A TIMELINE Thematic ProcessorSarah Asam0Christina Eisfelder1Andreas Hirner2Philipp Reiners3Stefanie Holzwarth4Martin Bachmann5German Remote Sensing Data Center (DFD), German Aerospace Center (DLR), 82234 Wessling, GermanyGerman Remote Sensing Data Center (DFD), German Aerospace Center (DLR), 82234 Wessling, GermanyGerman Remote Sensing Data Center (DFD), German Aerospace Center (DLR), 82234 Wessling, GermanyGerman Remote Sensing Data Center (DFD), German Aerospace Center (DLR), 82234 Wessling, GermanyGerman Remote Sensing Data Center (DFD), German Aerospace Center (DLR), 82234 Wessling, GermanyGerman Remote Sensing Data Center (DFD), German Aerospace Center (DLR), 82234 Wessling, GermanyRemote sensing image composites are crucial for a wide range of remote sensing applications, such as multi-decadal time series analysis. The Advanced Very High Resolution Radiometer (AVHRR) instrument has provided daily data since the early 1980s at a spatial resolution of 1 km, allowing analyses of climate change-related environmental processes. For monitoring vegetation conditions, the Normalized Difference Vegetation Index (NDVI) is the most widely used metric. However, to actually enable such analyses, a consistent NDVI time series over the AVHRR time-span needs to be created. In this context, the aim of this study is to thoroughly assess the effect of different compositing procedures on AVHRR NDVI composites, as no standard procedure has been established. Thirteen different compositing methods have been implemented; daily, decadal, and monthly composites over Europe and Northern Africa have been calculated for the year 2007, and the resulting data sets have been thoroughly evaluated according to six criteria. The median approach was selected as the best-performing compositing algorithm considering all the investigated aspects. However, the combination of the NDVI value and viewing and illumination angles as the criteria for the best-pixel selection proved to be a promising approach, too. The generated NDVI time series, currently ranging from 1981–2018, shows a consistent behavior and close agreement to the standard MODIS NDVI product. The conducted analyses demonstrate the strong influence of compositing procedures on the resulting AVHRR NDVI composites.https://www.mdpi.com/2072-4292/15/6/1631AVHRRNDVItime seriesremote sensingmulti-spectralcompositing |
| spellingShingle | Sarah Asam Christina Eisfelder Andreas Hirner Philipp Reiners Stefanie Holzwarth Martin Bachmann AVHRR NDVI Compositing Method Comparison and Generation of Multi-Decadal Time Series—A TIMELINE Thematic Processor Remote Sensing AVHRR NDVI time series remote sensing multi-spectral compositing |
| title | AVHRR NDVI Compositing Method Comparison and Generation of Multi-Decadal Time Series—A TIMELINE Thematic Processor |
| title_full | AVHRR NDVI Compositing Method Comparison and Generation of Multi-Decadal Time Series—A TIMELINE Thematic Processor |
| title_fullStr | AVHRR NDVI Compositing Method Comparison and Generation of Multi-Decadal Time Series—A TIMELINE Thematic Processor |
| title_full_unstemmed | AVHRR NDVI Compositing Method Comparison and Generation of Multi-Decadal Time Series—A TIMELINE Thematic Processor |
| title_short | AVHRR NDVI Compositing Method Comparison and Generation of Multi-Decadal Time Series—A TIMELINE Thematic Processor |
| title_sort | avhrr ndvi compositing method comparison and generation of multi decadal time series a timeline thematic processor |
| topic | AVHRR NDVI time series remote sensing multi-spectral compositing |
| url | https://www.mdpi.com/2072-4292/15/6/1631 |
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