Global overview of usable Landsat and Sentinel-2 data for 1982-2023

被引:0
|
作者
Lewinska, Katarzyna Ewa [1 ,2 ]
Ernst, Stefan [1 ]
Frantz, David [3 ]
Leser, Ulf [4 ]
Hostert, Patrick [1 ,3 ,5 ]
机构
[1] Humboldt Univ, Geog Dept, Unter Linden 6, D-10099 Berlin, Germany
[2] Univ Wisconsin Madison, Dept Forest & Wildlife Ecol, SILVIS Lab, 1630 Linden Dr, Madison, WI 53706 USA
[3] Trier Univ, Behringstr 21, D-54296 Trier, Germany
[4] Humboldt Univ, Dept Comp Sci, Unter Linden 6, D-10099 Berlin, Germany
[5] Humboldt Univ, Integrat Res Inst Transformat Human Environm Syst, Unter Linden 6, D-10099 Berlin, Germany
来源
DATA IN BRIEF | 2024年 / 57卷
关键词
Data availability; Aggregation; Long-term analyses; Terrestrial; Vegetation; Time series; CLOUD;
D O I
10.1016/j.dib.2024.111054
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Landsat and Sentinel-2 acquisitions are among the most widely used medium-resolution optical data adopted for terrestrial vegetation applications, such as land cover and land use mapping, vegetation condition and phenology monitoring, and disturbance and change mapping. When combined, both data archives provide over 40 years, and counting, of continuous and consistent observations. Although the spatiotemporal availability of both data archives is well-known at the scene level, information on the actual availability of cloud-, snow-, and shade-free observations at the pixel level is lacking and should be explored individually for each study to correctly parametrize subsequent analyses. However, data exploration is time- and resource-consuming, thus is rarely performed a-priori. Consequently, the spatio-temporal heterogeneity of usable data is often inadequately accounted for in the analysis design, risking ill-advised selection of algorithms and hypotheses, and thus inferior quality of final results. Here we present precomputed data on the daily 1982 2023 availability of usable Landsat and Sentinel-2 acquisitions across the globe. We assembled the dataset by sampling individual pixels at regular intervals with 0.18 degrees spacing in the latitudinal and longitudinal directions and reporting the data availability across the complete time depth of Land- sat and Sentinel-2 data archives. The dataset comprises separate Landsat- and Sentinel-2-specific data records. To facilitate data exploration the data availability records are accompanied by a growing season information, also sampled at the pixel-level in regular intervals with 0.18 degrees spacing. The dataset was derived based on freely available 1982-2023 Landsat surface reflectance (Collection 2) and Sentinel-2 top-of-the- atmosphere reflectance (pre-Collection-1 and Collection-1) scenes from 2015 through 2023, following the methodology developed in the recent study on data availability over Europe [1]. Growing season information was derived based on 2001-2019 time series of the yearly 500 m MODIS land cover dynamics product (MCD12Q2; Collection 6) [1]. As such, the dataset presents a unique overview of the spatio-temporal availability of usable daily Landsat and Sentinel-2 data at the global scale, hence offering much-needed a-priori information aiding identification of appropriate methods and challenges for terrestrial vegetation analyses at the local to global scale. (c) 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
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页数:9
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