摘要
遥感影像能提供时空特征明确的火场信息,是研究森林火灾分布特征的重要数据来源。选取四川省凉山州木里县2020年3月28日森林火灾前后6期Sentinel-2系列卫星影像数据,利用IR-MAD算法提取林火迹地,通过LUT查找表原理反演计算研究区内叶面积指数、光合有效辐射吸收比、叶绿素含量、冠层含水量和植被覆盖度5种生物物理量指标,定量分析评价当地植被受损以及灾后恢复情况。结果表明:(1)受灾区域林火烈度主要以中度火烧区为主,占受灾总面积的40%,且等级分布呈较强的空间分异特征;(2)研究区植被受损情况严重,叶面积指数下降至同期的20%;(3)截至2020年11月,灾后植被叶绿素含量恢复至灾前一半左右,各项指标均呈上升趋势。
Remote sensing images can provide fire field information with clear temporal and spatial characteristics,and are important data source for studying forest fire distribution characteristics.By selecting six phases of Sentinel-2 series satellite image data before and after the forest fire in Muli County,Liangshan Prefecture,Sichuan Province on March 28,2020,we used the IR-MAD algorithm to extract forest fire sites,calculated five biophysical indicators including leaf area index,fraction of absorbed photosynthetically active radiation,canopy chlorophyll content,canopy water content and fraction of vegetation cover in the study area with the LUT algorithm,and conducted quantitative analysis and evaluation of local vegetation damage and post-disaster recovery.The results show that(1)the forest fire intensity in the disaster area was mainly in moderately fired area,accounting for 40%of the total disaster area,and the grade distribution showed strong spatial differentiation characteristics.(2)The vegetation in the study area was seriously damaged and leaf area index dropped to 20%during the same period.(3)As of November 20,vegetation chlorophyll content after the disaster had recovered to about half of that before the disaster,and all the indicators showed an upward trend.
作者
蒋若凡
杨斌
宋林
潘天奕
邓晓辉
JIANG Ruofan;YANG Bin;SONG Lin;PAN Tianyi;DENG Xiaohui(Institute of Environment and Resources,Southwest University of Science and Technology,Mianyang 621010,China;Mianyang S&T City Division,the National Remote Sensing Center of China,Mianyang 621010,China)
出处
《地理空间信息》
2022年第5期38-44,共7页
Geospatial Information
基金
国家自然科学基金资助项目(41201541)
西南科技大学大学生创新训练计划资助项目(S202010619060)。
