应用遥感技术对大兴安岭南段次生阔叶林生物量进行估测,融合2009年8月的SPOT及同期TM影像,结合DEM等资料,利用多源信息复合处理方法,在ENVI软件中计算归一化植被指数、比值植被指数,同时引入海拔、坡度、坡向与阔叶林生物量估测相关的因子,依据地面森林样地生物量实测数据,运用多元回归分析方法,建立阔叶林生物量遥感估测模型B=13220.418－(254.645S+7.218A+46.679RVI)。经过模型检验,各统计量均在合理范围之内,建立的多元回归生物量遥感估测值与实测值平均相对误差≤17.14%,模型预测结果合理精度较高,可用于赛罕乌拉国家级自然保护区阔叶林生物量预测,同时为大兴安岭南段阔叶次生林生物量的遥感估测奠定基础。
The broadleaved forest Biomass model for the southern parst of Daxinganling Mountains was studied by RS technology in this paper.The SPOT-5 data and Landsat 5 TM in August 2009 were used as source data,with other data like DEM.On the basis of multi-source information composite processing method,normalized difference vegetation index and ratio vegetation index were extracted in ENVI .Slope,aspect and altitude were calculated from DEM.The local plot measured biomass data was taken as standard,through multiple regression analysis,remote sensing model for broadleaved forest Biomass 公式 was established.After accuracy test,all statistics were within the rational range,The average relative error was less than 17.4% showing the predicated values of RS model ere accurate,Less than 17.4%.It can be used for broadleaved forest biomass estimation in Saihanwula National Nature Reserve.Meanwhile,the RS model had a certain practical significance for broadleaved forest biomass estimation in broadleaved forest in the southern Daxinganling Mountains.
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