Usable observations over Europe: evaluation of compositing windows for Landsat and Sentinel-2 time series

被引:2
|
作者
Lewinska, Katarzyna Ewa [1 ,2 ]
Frantz, David [3 ]
Leser, Ulf [4 ]
Hostert, Patrick [1 ,5 ]
机构
[1] Humboldt Univ, Geog Dept, Unter Linden 6, D-10099 Berlin, Germany
[2] Univ Wisconsin, Dept Forest & Wildlife Ecol, SILVIS Lab, Madison, WI USA
[3] Trier Univ, Geoinformat Spatial Data Sci, Trier, Germany
[4] Humboldt Univ, Dept Comp Sci, Berlin, Germany
[5] Humboldt Univ, Integrat Res Inst Transformat Human Environm Syst, Geog, Berlin, Germany
关键词
Time-series; data availability; aggregation; long-term analyses; MODIS SURFACE REFLECTANCE; SPECTRAL-TEMPORAL METRICS; NATIONAL-SCALE; REVISIT INTERVAL; COVER DYNAMICS; VEGETATION; CLASSIFICATION; CLOUD; ALGORITHMS; WATER;
D O I
10.1080/22797254.2024.2372855
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Landsat and Sentinel-2 data archives provide ever-increasing amounts of satellite data. However, the availability of usable observations greatly varies spatially and temporally. Pixel-based compositing that generates temporally equidistant cloud-free synthetic images can mitigate temporal variability, by constructing uninterrupted time series using different compositing windows. Here, we evaluated the feasibility of using compositing windows ranging from five days to one year for 1984-2021 Landsat and 2015-2021 Sentinel 2 time series to derive uninterrupted time series across Europe. We considered separate and joint use of both data archives and analyzed the spatio-temporal availability of composites during each calendar year and pixel-specific growing season across a variety of time windows and hypothesizing data interpolation. Our results demonstrated opportunities and limitations in the available data records to support medium- and long-term analyses requiring uninterrupted time series of composites with sub-annual temporal resolution. Spatial disparities across different compositing windows provide guidance on the feasibility of workflows relying on different data densities and on the challenges in wall-to-wall analyses. The feasibility of consistent time series based on composites with sub-monthly aggregation periods was mostly limited to the combined Landsat and Sentinel-2 archives after 2015, yet in some geographies requires interpolation of up to 50% of data.
引用
收藏
页数:28
相关论文
共 50 条
  • [1] Global overview of usable Landsat and Sentinel-2 data for 1982-2023
    Lewinska, Katarzyna Ewa
    Ernst, Stefan
    Frantz, David
    Leser, Ulf
    Hostert, Patrick
    DATA IN BRIEF, 2024, 57
  • [2] Evaluation of Landsat-9 interoperability with Sentinel-2 and Landsat-8 over Europe and local comparison with field surveys
    Trevisiol, F.
    Mandanici, E.
    Pagliarani, A.
    Bitelli, G.
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2024, 210 : 55 - 68
  • [3] Broad-area-search of new construction using time series analysis of Landsat and Sentinel-2 data
    Tang, Xiaojing
    Barrett, Madison G.
    Cho, Kangjoon
    Bratley, Kelsee H.
    Tarrio, Katelyn
    Zhang, Yingtong
    Gu, Hanfeng
    Rasmussen, Peter
    Bosch, Marc
    Woodcock, Curtis E.
    SCIENCE OF REMOTE SENSING, 2024, 9
  • [4] Evaluation of Sentinel-2 time-series for mapping floodplain grassland plant communities
    Rapinel, Sebastien
    Mony, Cendrine
    Lecoq, Lucie
    Clement, Bernard
    Thomas, Alban
    Hubert-Moy, Laurence
    REMOTE SENSING OF ENVIRONMENT, 2019, 223 : 115 - 129
  • [5] Sentinel-2 Time Series Analysis for Identification of Underutilized Land in Europe
    Sobe, Carina
    Hirschmugl, Manuela
    Wimmer, Andreas
    REMOTE SENSING, 2021, 13 (23)
  • [6] Preliminary Evaluation of the Consistency of Landsat 8 and Sentinel-2 Time Series Products in An Urban Area-An Example in Beijing, China
    Nie, Zhen
    Chan, Karen Kie Yan
    Xu, Bing
    REMOTE SENSING, 2019, 11 (24)
  • [7] Fast Fusion of Sentinel-2 and Sentinel-3 Time Series over Rangelands
    Senty, Paul
    Guzinski, Radoslaw
    Grogan, Kenneth
    Buitenwerf, Robert
    Ardoe, Jonas
    Eklundh, Lars
    Koukos, Alkiviadis
    Tagesson, Torbern
    Munk, Michael
    REMOTE SENSING, 2024, 16 (11)
  • [8] Forest Stand Species Mapping Using the Sentinel-2 Time Series
    Grabska, Ewa
    Hostert, Patrick
    Pflugmacher, Dirk
    Ostapowicz, Katarzyna
    REMOTE SENSING, 2019, 11 (10)
  • [9] Assessing Combinations of Landsat, Sentinel-2 and Sentinel-1 Time series for Detecting Bark Beetle Infestations
    Koenig, Simon
    Thonfeld, Frank
    Foerster, Michael
    Dubovyk, Olena
    Heurich, Marco
    GISCIENCE & REMOTE SENSING, 2023, 60 (01)
  • [10] Retrieval of Harmonized LAI Product of Agricultural Crops from Landsat OLI and Sentinel-2 MSI Time Series
    Tomicek, Jiri
    Misurec, Jan
    Lukes, Petr
    Potuckova, Marketa
    AGRICULTURE-BASEL, 2022, 12 (12):