Augmenting Landsat time series with Harmonized Landsat Sentinel-2 data products: Assessment of spectral correspondence
An increase in the temporal revisit of satellite data is often sought to increase the likelihood of obtaining cloud- and shadow-free observations as well as to improve mapping of rapidly- or seasonally-changing features. Currently, as a tandem, Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and −8 O...
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doaj-a50e682ed535471f8470f9ddd63f0f192021-10-09T04:41:31ZengElsevierScience of Remote Sensing2666-01722021-12-014100031Augmenting Landsat time series with Harmonized Landsat Sentinel-2 data products: Assessment of spectral correspondenceMichael A. Wulder0Txomin Hermosilla1Joanne C. White2Geordie Hobart3Jeffrey G. Masek4Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, 506 West Burnside Road, Victoria, British Columbia, V8Z 1M5, Canada; Corresponding author.Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, 506 West Burnside Road, Victoria, British Columbia, V8Z 1M5, CanadaCanadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, 506 West Burnside Road, Victoria, British Columbia, V8Z 1M5, CanadaCanadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, 506 West Burnside Road, Victoria, British Columbia, V8Z 1M5, CanadaBiospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, 20771, USAAn increase in the temporal revisit of satellite data is often sought to increase the likelihood of obtaining cloud- and shadow-free observations as well as to improve mapping of rapidly- or seasonally-changing features. Currently, as a tandem, Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and −8 Operational Land Imager (OLI) provide an acquisition opportunity on an 8-day revisit interval. Sentinel-2A and -2B MultiSpectral Instrument (MSI), with a wider swath, have a 5-day revisit interval at the equator. Due to robust pre- and post-launch cross-calibration, it has been possible for NASA to produce the Harmonized Landsat Sentinel-2 (HLS) data product from Landsat-8 OLI and Sentinel-2 MSI: L30 and S30, respectively. Knowledge of the agreement of HLS outputs (especially S30) with historic Landsat surface reflectance products will inform the ability to integrate historic time-series information with new and more frequent measures as delivered by HLS. In this research, we control for acquisition date and data source to cross-compare the HLS data (L30, S30) with established Landsat-8 OLI surface-reflectance measures as delivered by the USGS (hereafter BAP, Best Available Pixel). S30 and L30 were found to have high agreement (R = 0.87–0.96) for spectral channels and an r = 0.99 for Normalized Burn Ratio (NBR) with low relative root-mean-square difference values (1.7%–3.3%). Agreement between L30 and BAP was lower, with R values ranging from 0.85 to 0.92 for spectral channels and R = 0.94 for NBR. S30 and BAP had the lowest agreement, with R values ranging from 0.71 to 0.85 for spectral channels and r = 0.90 for NBR. Comparisons indicated a stronger agreement at latitudes above 55° N. Some dependency between spectral agreement and land cover was found, with stronger correspondence for non-vegetated cover types. The level of agreement between S30 and BAP reported herein would enable integration of HLS outputs with historic Landsat data. The resulting increased temporal frequency of data allows for improvements to current cloud screening practices and increases data density and the likelihood of temporal proximity to target date for pixel compositing approaches. Furthermore, additional within-year observations will enable change products with a higher temporal fidelity and allow for the incorporation of phenological trends into land cover classification algorithms.http://www.sciencedirect.com/science/article/pii/S2666017221000183Virtual constellationAnalysis ready dataLand coverMonitoringARDHLS |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Michael A. Wulder Txomin Hermosilla Joanne C. White Geordie Hobart Jeffrey G. Masek |
spellingShingle |
Michael A. Wulder Txomin Hermosilla Joanne C. White Geordie Hobart Jeffrey G. Masek Augmenting Landsat time series with Harmonized Landsat Sentinel-2 data products: Assessment of spectral correspondence Science of Remote Sensing Virtual constellation Analysis ready data Land cover Monitoring ARD HLS |
author_facet |
Michael A. Wulder Txomin Hermosilla Joanne C. White Geordie Hobart Jeffrey G. Masek |
author_sort |
Michael A. Wulder |
title |
Augmenting Landsat time series with Harmonized Landsat Sentinel-2 data products: Assessment of spectral correspondence |
title_short |
Augmenting Landsat time series with Harmonized Landsat Sentinel-2 data products: Assessment of spectral correspondence |
title_full |
Augmenting Landsat time series with Harmonized Landsat Sentinel-2 data products: Assessment of spectral correspondence |
title_fullStr |
Augmenting Landsat time series with Harmonized Landsat Sentinel-2 data products: Assessment of spectral correspondence |
title_full_unstemmed |
Augmenting Landsat time series with Harmonized Landsat Sentinel-2 data products: Assessment of spectral correspondence |
title_sort |
augmenting landsat time series with harmonized landsat sentinel-2 data products: assessment of spectral correspondence |
publisher |
Elsevier |
series |
Science of Remote Sensing |
issn |
2666-0172 |
publishDate |
2021-12-01 |
description |
An increase in the temporal revisit of satellite data is often sought to increase the likelihood of obtaining cloud- and shadow-free observations as well as to improve mapping of rapidly- or seasonally-changing features. Currently, as a tandem, Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and −8 Operational Land Imager (OLI) provide an acquisition opportunity on an 8-day revisit interval. Sentinel-2A and -2B MultiSpectral Instrument (MSI), with a wider swath, have a 5-day revisit interval at the equator. Due to robust pre- and post-launch cross-calibration, it has been possible for NASA to produce the Harmonized Landsat Sentinel-2 (HLS) data product from Landsat-8 OLI and Sentinel-2 MSI: L30 and S30, respectively. Knowledge of the agreement of HLS outputs (especially S30) with historic Landsat surface reflectance products will inform the ability to integrate historic time-series information with new and more frequent measures as delivered by HLS. In this research, we control for acquisition date and data source to cross-compare the HLS data (L30, S30) with established Landsat-8 OLI surface-reflectance measures as delivered by the USGS (hereafter BAP, Best Available Pixel). S30 and L30 were found to have high agreement (R = 0.87–0.96) for spectral channels and an r = 0.99 for Normalized Burn Ratio (NBR) with low relative root-mean-square difference values (1.7%–3.3%). Agreement between L30 and BAP was lower, with R values ranging from 0.85 to 0.92 for spectral channels and R = 0.94 for NBR. S30 and BAP had the lowest agreement, with R values ranging from 0.71 to 0.85 for spectral channels and r = 0.90 for NBR. Comparisons indicated a stronger agreement at latitudes above 55° N. Some dependency between spectral agreement and land cover was found, with stronger correspondence for non-vegetated cover types. The level of agreement between S30 and BAP reported herein would enable integration of HLS outputs with historic Landsat data. The resulting increased temporal frequency of data allows for improvements to current cloud screening practices and increases data density and the likelihood of temporal proximity to target date for pixel compositing approaches. Furthermore, additional within-year observations will enable change products with a higher temporal fidelity and allow for the incorporation of phenological trends into land cover classification algorithms. |
topic |
Virtual constellation Analysis ready data Land cover Monitoring ARD HLS |
url |
http://www.sciencedirect.com/science/article/pii/S2666017221000183 |
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