首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Burned area mapping time series in Canada (1984-1999) from NOAA-AVHRR LTDR: A comparison with other remote sensing products and fire perimeters
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Burned area mapping time series in Canada (1984-1999) from NOAA-AVHRR LTDR: A comparison with other remote sensing products and fire perimeters

机译:NOAA-AVHRR LTDR在加拿大的燃烧区域制图时间序列(1984-1999):与其他遥感产品和火灾周边的比较

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摘要

A new algorithm for mapping burned areas in boreal forest using AVHRR archival data Long Term Data Record (LTDR) (0.05°, ca. 5km, version 3) was developed in Canada using burn records for the period between 1984 and 1999 and evaluated against AVHRR 1km and AVHRR-PAL 8km burned area map products. The algorithm combined 1) absolute and relative radiometric thresholds, 2) a Bayesian network classifier, and 3) neighborhood analysis for spatial fire coherence. Fire event records from Canadian Forest Service National Fire Database (CFSNFD) for western Canada were used to train the algorithm. LTDR and AVHRR 1km burned area mapping were similar for the same area, and correlated well to CFSNFD annual fire event records for western Canada, r ~2=0.72 and 0.77, respectively. In addition, the LTDR mapping correlated well with fires for all of Canada in the CFSNFD database (r ~2=0.65). This mapping product was a significant improvement over an 8km AVHRR-PAL burned area map product. For mapping boreal forests burned areas globally, this study demonstrates the potential accuracy for where LTDR represents the highest spatial and temporal resolution of daily images available since the 1980s.
机译:加拿大使用1984年至1999年期间的燃烧记录,开发了一种使用AVHRR档案数据长期数据记录(LTDR)(0.05°,约5 km,版本3)绘制北方森林烧伤区域的新算法,并针对AVHRR进行了评估1公里和AVHRR-PAL 8公里燃烧区地图产品。该算法结合了1)绝对和相对辐射阈值,2)贝叶斯网络分类器和3)空间火连贯性的邻域分析。来自加拿大西部加拿大森林服务局国家火灾数据库(CFSNFD)的火灾事件记录用于训练该算法。同一区域的LTDR和AVHRR 1 km燃烧面积图相似,并且与加拿大西部CFSNFD年度火灾记录有很好的相关性,r〜2 = 0.72和0.77。另外,在CFSNFD数据库中,LTDR映射与整个加拿大的大火有很好的相关性(r〜2 = 0.65)。该地图产品比8公里的AVHRR-PAL燃烧区域地图产品有了重大改进。为了绘制全球北方森林烧毁地区的地图,这项研究证明了LTDR代表自1980年代以来可用的每日图像的最高时空分辨率的潜在准确性。

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