Data Likelihood of Active Fires Satellite Detection and Applications to Ignition Estimation and Data Assimilation

被引:0
作者
Haley, James [1 ]
Farguell Caus, Angel [1 ,2 ]
Kochanski, Adam K. [3 ]
Schranz, Sher [4 ]
Mandel, Jan [1 ]
机构
[1] Univ Colorado, Denver, CO 80202 USA
[2] Autonomous Univ Barcelona, Barcelona, Spain
[3] Univ Utah, Salt Lake City, UT USA
[4] Colorado State Univ, CIRA, Ft Collins, CO USA
来源
ADVANCES IN FOREST FIRE RESEARCH 2018 | 2018年
关键词
Active Fires; MODIS; VIIRS; Coupled Fire-Atmosphere Modeling; Remote Sensing; Maximum Likelihood; Data Assimilation; Data-Driven Simulation; VALIDATION; ALGORITHM; PRODUCT;
D O I
10.14195/978-989-26-16-506_105
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
Data likelihood of fire detection is the probability of the observed detection outcome given the state of the fire spread model. We derive fire detection likelihood of satellite data as a function of the fire arrival time on the model grid. The data likelihood is constructed by a combination of the burn model, the logistic regression of the active fires detections, and the Gaussian distribution of the geolocation error. The use of the data likelihood is then demonstrated by an estimation of the ignition point of a wildland fire by the maximization of the likelihood of MODIS and VIIRS data over multiple possible ignition points.
引用
收藏
页码:959 / 968
页数:10
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