气候变化领域集成服务门户(CCPortal): Continental-scale land surface phenology from harmonized Landsat 8 and Sentinel-2 imagery

CCPortal

DOI	10.1016/j.rse.2020.111685
	Continental-scale land surface phenology from harmonized Landsat 8 and Sentinel-2 imagery
	Bolton D.K.; Gray J.M.; Melaas E.K.; Moon M.; Eklundh L.; Friedl M.A.
发表日期	2020
ISSN	00344257
卷号	240
英文摘要	Dense time series of Landsat 8 and Sentinel-2 imagery are creating exciting new opportunities to monitor, map, and characterize temporal dynamics in land surface properties with unprecedented spatial detail and quality. By combining imagery from the Landsat 8 Operational Land Imager and the MultiSpectral Instrument on-board Sentinel-2A and -2B, the remote sensing community now has access to moderate (10–30 m) spatial resolution imagery with repeat periods of ~3 days in the mid-latitudes. At the same time, the large combined data volume from Landsat 8 and Sentinel-2 introduce substantial new challenges for users. Land surface phenology (LSP) algorithms, which estimate the timing of phenophase transitions and quantify the nature and magnitude of seasonality in remotely sensed land surface conditions, provide an intuitive way to reduce data volumes and redundancy, while also furnishing data sets that are useful for a wide range of applications including monitoring ecosystem response to climate variability and extreme events, ecosystem modelling, crop-type discrimination, and land cover, land use, and land cover change mapping, among others. To support the need for operational LSP data sets, here we describe a continental-scale land surface phenology algorithm and data product based on harmonized Landsat 8 and Sentinel-2 (HLS) imagery. The algorithm creates high quality times series of vegetation indices from HLS imagery, which are then used to estimate the timing of vegetation phenophase transitions at 30 m spatial resolution. We present results from assessment efforts evaluating LSP retrievals, and provide examples illustrating the character and quality of information related to land cover and terrestrial ecosystem properties provided by the continental LSP dataset that we have developed. The algorithm is highly successful in ecosystems with strong seasonal variation in leaf area (e.g., deciduous forests). Conversely, results in evergreen systems are less interpretable and conclusive. © 2020 The Authors
英文关键词	Harmonized Landsat Sentinel; Image time series; Land surface phenology; Multi-sensor; Vegetation index
语种	英语
scopus关键词	Climate change; Ecosystems; Forestry; Image resolution; Land use; Remote sensing; Surface measurement; Time series; Vegetation; Image time-series; Land surface phenology; LANDSAT; Multi sensor; Vegetation index; Mapping; algorithm; ecosystem response; land cover; land surface; Landsat; leaf area; phenology; remote sensing; satellite imagery; seasonal variation; seasonality; Sentinel; spatial resolution; terrestrial ecosystem
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179416
作者单位	Department of Earth & Environment, Boston University, 685 Commonwealth Avenue, Boston, MA 02215, United States; Center for Geospatial Analytics, North Carolina State University, 2800 Faucette Dr., Raleigh, NC 27695, United States; Indigo Ag, 500 Rutherford Avenue, Boston, MA 02129, United States; Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, Lund, 223 62, Sweden
推荐引用方式 GB/T 7714	Bolton D.K.,Gray J.M.,Melaas E.K.,et al. Continental-scale land surface phenology from harmonized Landsat 8 and Sentinel-2 imagery[J],2020,240.
APA	Bolton D.K.,Gray J.M.,Melaas E.K.,Moon M.,Eklundh L.,&Friedl M.A..(2020).Continental-scale land surface phenology from harmonized Landsat 8 and Sentinel-2 imagery.Remote Sensing of Environment,240.
MLA	Bolton D.K.,et al."Continental-scale land surface phenology from harmonized Landsat 8 and Sentinel-2 imagery".Remote Sensing of Environment 240(2020).