Multi-year MODIS active fire type classification over the Brazilian Tropical Moist Forest Biome

作     者：D.P.Roy S.S.Kumar 

作者机构：Geospatial Sciences Center of ExcellenceSouth Dakota State UniversityBrookingsSDUSA 

出 版 物：《International Journal of Digital Earth》 (国际数字地球学报（英文）)

年 卷 期：2017年第10卷第1期

页      面：54-84页

核心收录：

学科分类：090703[农学-森林保护学] 0907[农学-林学] 09[农学] 

基　　金：NASA[grant number NNX10AN72H] 

主　　题：Earth observation land cover remote sensing 

摘      要：The Brazilian Tropical Moist Forest Biome(BTMFB)spans almost 4 million km^(2) and is subject to extensive annual fires that have been categorized into deforestation,maintenance,and forest fire *** on fire types is important as they have different atmospheric emissions and ecological impacts.A supervised classification methodology is presented to classify the fire type of MODerate resolution Imaging Spectroradiometer(MODIS)active fire detections using training data defined by consideration of Brazilian government forest monitoring program annual land cover maps,and using predictor variables concerned with fuel flammability,fuel load,fire behavior,fire seasonality,fire annual frequency,proximity to surface transportation,and local *** fire seasonality,local temperature,and fuel flammability were the most influential on the *** fire type results for all 1.6 million MODIS Terra and Aqua BTMFB active fire detections over eight years(2003–2010)are presented with an overall fire type classification accuracy of 90.9%(kappa 0.824).The fire type user’s and producer’s classification accuracies were respectively 92.4%and 94.4%(maintenance fires),88.4%and 87.5%(forest fires),and,88.7%and 75.0%(deforestation fires).The spatial and temporal distribution of the classified fire types are presented and are similar to patterns reported in the available recent literature.