气候变化领域集成服务门户(CCPortal): Assessing satellite-derived fire patches with functional diversity trait methods

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DOI	10.1016/j.rse.2020.111897
	Assessing satellite-derived fire patches with functional diversity trait methods
	Moreno M.V.; Laurent P.; Ciais P.; Mouillot F.
发表日期	2020
ISSN	00344257
卷号	247
英文摘要	Fire disturbance is a significant component of the climate system. Analysis of satellite-derived burned areas has allowed the identification of fire patches and their morphology as a new resource for tracking fire spread to improve fire models used to assess the impact of fires on climate and the carbon cycle. A critical parameter of the flood-fill algorithm used to create fire patches is the cut-off (in days) below which it aggregates two contiguous burned pixels to the same fire patch. However, the current level of validation is insufficient to understand the effect of the cut-off values and sensor resolutions on the subsequent fire-patch morphology. The FRY v1.0 database of functional fire-patch traits (e.g., size, elongation, and direction) emanates from the analyses of two global burned-area products derived from MODIS and MERIS sensors with different spatial and temporal resolutions and with cut-off values of 3, 5, 9, and 14 days. To evaluate whether the FRY products are accurately identifying the spatial features of fire patches and what are the most realistic cut-off values to use in different sub-regions of North America, we propose a new functional diversity trait-based approach, which compares the satellite-derived fire patches to forest service perimeters as reference data. This paper shows the accuracy of the FRY fire patches ≥300 ha in North America during 2005–2011. Our analysis demonstrates that fire patches with a high cut-off of 14 days and those derived from the MODIS sensor, with their high temporal resolution, better identify the fire diversity in North America. In conclusion, our statistical framework can be used for assessing satellite-derived fire patches. Furthermore, the temporal resolution of satellite sensors is the most important factor in identifying fire patches — thus space agencies should consider it when planning the future development of cost-effective climate observation systems. © 2020 Elsevier Inc.
英文关键词	DGVMs; Essential Climate Variable; Fire Spread; Fire-Patch Morphology; Flood-Fill Algorithm; Functional Beta Diversity; Functional Diversity Indices; MERIS; MODIS; Validation
语种	英语
scopus关键词	Climate models; Cost effectiveness; Morphology; Radiometers; Satellites; Climate observations; Functional diversity; High temporal resolution; Sensor resolution; Spatial and temporal resolutions; Statistical framework; Temporal resolution; Trait-based approaches; Fires; algorithm; database; forest fire; functional response; MERIS; MODIS; satellite altimetry; satellite sensor; North America
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/179267
作者单位	UMR CEFE 5175, Univ Montpellier, CNRS, EPHE, IRD, Univ Paul Valéry Montpellier 3, Montpellier, France; Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, UMR8212, Gif-sur-Yvette, France
推荐引用方式 GB/T 7714	Moreno M.V.,Laurent P.,Ciais P.,et al. Assessing satellite-derived fire patches with functional diversity trait methods[J],2020,247.
APA	Moreno M.V.,Laurent P.,Ciais P.,&Mouillot F..(2020).Assessing satellite-derived fire patches with functional diversity trait methods.Remote Sensing of Environment,247.
MLA	Moreno M.V.,et al."Assessing satellite-derived fire patches with functional diversity trait methods".Remote Sensing of Environment 247(2020).