气候变化领域集成服务门户(CCPortal): First study of Sentinel-3 SLSTR active fire detection and FRP retrieval: Night-time algorithm enhancements and global intercomparison to MODIS and VIIRS AF products

CCPortal

DOI	10.1016/j.rse.2020.111947
	First study of Sentinel-3 SLSTR active fire detection and FRP retrieval: Night-time algorithm enhancements and global intercomparison to MODIS and VIIRS AF products
	Xu W.; Wooster M.J.; He J.; Zhang T.
发表日期	2020
ISSN	00344257
卷号	248
英文摘要	The Sea and Land Surface Temperature Radiometer (SLSTR) now operates concurrently onboard the European Sentinel-3A and –3B satellites. Its observations are expected ultimately to become the main global source of active fire (AF) detections and fire radiative power (FRP) retrievals for the mid-morning and evening low earth orbit timeslots – data currently supplied by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra. Here we report for the first-time the significant adjustments made to the pre-launch Sentinel-3 AF detection and fire characterisation algorithm required to optimize its performance with real SLSTR data collected from the Sentinel-3A and –3B satellites. SLSTR possesses both an S7 ‘standard’ and an F1 ‘fire’ channel that operate in the same middle infrared (MIR) waveband, but which use different detectors with differing dynamic ranges and which are located at different focal plane locations. When S7 provides saturated observations, for example over higher FRP active fire pixels, F1 must be used to provide a reliable MIR spectral measurement. However, the two channels differing data characteristics (slightly different size, shape and spatial location of the matching pixels) means that swapping between their measurements is non-trivial. The main algorithm enhancement has therefore been the addition of a dedicated active fire pixel clustering component, required to cluster the detected AF pixels into individual fires as a solution to this issue. Focusing on night-time data due to the added complexity of daytime implementation, we compare AF information derived with this updated SLSTR algorithm to that from near-simultaneous MODIS Terra, and we find that SLSTR has a lower minimum FRP detection limit which enables more lower FRP active fire pixels to be identified than is the case with MODIS. When both sensors detect the same fire cluster at the same time, SLSTR typically measures a slightly higher FRP due to it being able to detect more of the low FRP AF pixels lying at the cluster edge (the OLS linear best fit between matched SLSTR and MODIS per-fire FRP matchups has a slope of 1.08). At the regional scale, SLSTR detects 90% of the AF pixels that the matching MODIS data contains, but also identifies an additional 44% more AF pixels – the vast majority of which have FRP < 5 MW. Regional FRP totals derived from SLSTR appear slightly higher than those from MODIS because of this, and the OLS linear best fit between these regional FRP matchup datasets has a slope of 1.10. Global fire mapping at 1° grid cell resolution for January 2019 shows very similar fire patterns and FRP totals from SLSTR onboard of Sentinel-3B and MODIS Terra, with SLSTR detecting seven times more AF pixels but very similar FRP totals. Case studies in 5° grid cell areas show the same pattern, and longer-term comparisons like these will provide the data required to mesh MODIS and SLSTR data into a single compatible time-series for long-term trend analysis. The night-time SLSTR AF product based largely on this algorithm has been fully operational from March 2020 and is available from near real-time feeds. A non-time critical (NTC) version based on a similar processing chain will follow shortly after, with products available from the Sentinel-3 Data Hub. © 2020
语种	英语
scopus关键词	Clustering algorithms; Fires; Land surface temperature; Orbits; Radiometers; Time series analysis; Data characteristics; Detection limits; Fire radiative power; Fully operational; Intercomparisons; Low earth orbits; Moderate resolution imaging spectroradiometer; Spectral measurement; Pixels; algorithm; complexity; detection method; measurement method; MODIS; performance assessment; pixel; satellite data; Sentinel; Terra (satellite); trend analysis
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/179210
作者单位	King's College London, Leverhulme Centre for Wildfires, Environment and Society, Department of Geography, Aldwych, WC2B 4BG, London, United Kingdom; NERC National Centre for Earth Observation (NCEO), King's College London, United Kingdom
推荐引用方式 GB/T 7714	Xu W.,Wooster M.J.,He J.,et al. First study of Sentinel-3 SLSTR active fire detection and FRP retrieval: Night-time algorithm enhancements and global intercomparison to MODIS and VIIRS AF products[J],2020,248.
APA	Xu W.,Wooster M.J.,He J.,&Zhang T..(2020).First study of Sentinel-3 SLSTR active fire detection and FRP retrieval: Night-time algorithm enhancements and global intercomparison to MODIS and VIIRS AF products.Remote Sensing of Environment,248.
MLA	Xu W.,et al."First study of Sentinel-3 SLSTR active fire detection and FRP retrieval: Night-time algorithm enhancements and global intercomparison to MODIS and VIIRS AF products".Remote Sensing of Environment 248(2020).