Mosaicking Landsat and Sentinel-2 Data to Enhance LandTrendr Time Series Analysis in Northern High Latitude Permafrost Regions

Permafrost is warming in the northern high latitudes, inducing highly dynamic thaw-related permafrost disturbances across the terrestrial Arctic. Monitoring and tracking of permafrost disturbances is important as they impact surrounding landscapes, ecosystems and infrastructure. Remote sensing provi...

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Published in:Remote Sensing
Main Authors: Alexandra Runge, Guido Grosse
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2020
Subjects:
Online Access:https://doi.org/10.3390/rs12152471
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spelling ftmdpi:oai:mdpi.com:/2072-4292/12/15/2471/ 2023-08-20T04:04:27+02:00 Mosaicking Landsat and Sentinel-2 Data to Enhance LandTrendr Time Series Analysis in Northern High Latitude Permafrost Regions Alexandra Runge Guido Grosse agris 2020-08-01 application/pdf https://doi.org/10.3390/rs12152471 EN eng Multidisciplinary Digital Publishing Institute Environmental Remote Sensing https://dx.doi.org/10.3390/rs12152471 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 12; Issue 15; Pages: 2471 time series analysis data fusion disturbance tracking permafrost permafrost thaw Text 2020 ftmdpi https://doi.org/10.3390/rs12152471 2023-07-31T23:52:02Z Permafrost is warming in the northern high latitudes, inducing highly dynamic thaw-related permafrost disturbances across the terrestrial Arctic. Monitoring and tracking of permafrost disturbances is important as they impact surrounding landscapes, ecosystems and infrastructure. Remote sensing provides the means to detect, map, and quantify these changes homogeneously across large regions and time scales. Existing Landsat-based algorithms assess different types of disturbances with similar spatiotemporal requirements. However, Landsat-based analyses are restricted in northern high latitudes due to the long repeat interval and frequent clouds, in particular at Arctic coastal sites. We therefore propose to combine Landsat and Sentinel-2 data for enhanced data coverage and present a combined annual mosaic workflow, expanding currently available algorithms, such as LandTrendr, to achieve more reliable time series analysis. We exemplary test the workflow for twelve sites across the northern high latitudes in Siberia. We assessed the number of images and cloud-free pixels, the spatial mosaic coverage and the mosaic quality with spectral comparisons. The number of available images increased steadily from 1999 to 2019 but especially from 2016 onward with the addition of Sentinel-2 images. Consequently, we have an increased number of cloud-free pixels even under challenging environmental conditions, which then serve as the input to the mosaicking process. In a comparison of annual mosaics, the Landsat+Sentinel-2 mosaics always fully covered the study areas (99.9–100 %), while Landsat-only mosaics contained data-gaps in the same years, only reaching coverage percentages of 27.2 %, 58.1 %, and 69.7 % for Sobo Sise, East Taymyr, and Kurungnakh in 2017, respectively. The spectral comparison of Landsat image, Sentinel-2 image, and Landsat+Sentinel-2 mosaic showed high correlation between the input images and mosaic bands (e.g., for Kurungnakh 0.91–0.97 between Landsat and Landsat+Sentinel-2 mosaic and 0.92–0.98 between ... Text Arctic permafrost Taymyr Siberia MDPI Open Access Publishing Arctic Taymyr ENVELOPE(89.987,89.987,68.219,68.219) Remote Sensing 12 15 2471
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic time series analysis
data fusion
disturbance tracking
permafrost
permafrost thaw
spellingShingle time series analysis
data fusion
disturbance tracking
permafrost
permafrost thaw
Alexandra Runge
Guido Grosse
Mosaicking Landsat and Sentinel-2 Data to Enhance LandTrendr Time Series Analysis in Northern High Latitude Permafrost Regions
topic_facet time series analysis
data fusion
disturbance tracking
permafrost
permafrost thaw
description Permafrost is warming in the northern high latitudes, inducing highly dynamic thaw-related permafrost disturbances across the terrestrial Arctic. Monitoring and tracking of permafrost disturbances is important as they impact surrounding landscapes, ecosystems and infrastructure. Remote sensing provides the means to detect, map, and quantify these changes homogeneously across large regions and time scales. Existing Landsat-based algorithms assess different types of disturbances with similar spatiotemporal requirements. However, Landsat-based analyses are restricted in northern high latitudes due to the long repeat interval and frequent clouds, in particular at Arctic coastal sites. We therefore propose to combine Landsat and Sentinel-2 data for enhanced data coverage and present a combined annual mosaic workflow, expanding currently available algorithms, such as LandTrendr, to achieve more reliable time series analysis. We exemplary test the workflow for twelve sites across the northern high latitudes in Siberia. We assessed the number of images and cloud-free pixels, the spatial mosaic coverage and the mosaic quality with spectral comparisons. The number of available images increased steadily from 1999 to 2019 but especially from 2016 onward with the addition of Sentinel-2 images. Consequently, we have an increased number of cloud-free pixels even under challenging environmental conditions, which then serve as the input to the mosaicking process. In a comparison of annual mosaics, the Landsat+Sentinel-2 mosaics always fully covered the study areas (99.9–100 %), while Landsat-only mosaics contained data-gaps in the same years, only reaching coverage percentages of 27.2 %, 58.1 %, and 69.7 % for Sobo Sise, East Taymyr, and Kurungnakh in 2017, respectively. The spectral comparison of Landsat image, Sentinel-2 image, and Landsat+Sentinel-2 mosaic showed high correlation between the input images and mosaic bands (e.g., for Kurungnakh 0.91–0.97 between Landsat and Landsat+Sentinel-2 mosaic and 0.92–0.98 between ...
format Text
author Alexandra Runge
Guido Grosse
author_facet Alexandra Runge
Guido Grosse
author_sort Alexandra Runge
title Mosaicking Landsat and Sentinel-2 Data to Enhance LandTrendr Time Series Analysis in Northern High Latitude Permafrost Regions
title_short Mosaicking Landsat and Sentinel-2 Data to Enhance LandTrendr Time Series Analysis in Northern High Latitude Permafrost Regions
title_full Mosaicking Landsat and Sentinel-2 Data to Enhance LandTrendr Time Series Analysis in Northern High Latitude Permafrost Regions
title_fullStr Mosaicking Landsat and Sentinel-2 Data to Enhance LandTrendr Time Series Analysis in Northern High Latitude Permafrost Regions
title_full_unstemmed Mosaicking Landsat and Sentinel-2 Data to Enhance LandTrendr Time Series Analysis in Northern High Latitude Permafrost Regions
title_sort mosaicking landsat and sentinel-2 data to enhance landtrendr time series analysis in northern high latitude permafrost regions
publisher Multidisciplinary Digital Publishing Institute
publishDate 2020
url https://doi.org/10.3390/rs12152471
op_coverage agris
long_lat ENVELOPE(89.987,89.987,68.219,68.219)
geographic Arctic
Taymyr
geographic_facet Arctic
Taymyr
genre Arctic
permafrost
Taymyr
Siberia
genre_facet Arctic
permafrost
Taymyr
Siberia
op_source Remote Sensing; Volume 12; Issue 15; Pages: 2471
op_relation Environmental Remote Sensing
https://dx.doi.org/10.3390/rs12152471
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/rs12152471
container_title Remote Sensing
container_volume 12
container_issue 15
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