单 位：
国家林业局调查规划设计院;北京林业大学省部共建森林培育与保护教育部重点实验室
关键词：
森林生物;遥感;MODIS;多元线性回归模型
摘 要：
以东北三省为试验区,利用MOD IS时间序列上的植被指数NDVI,结合森林资源清查样地数据测算的林分生物量,以及年均降水量、年均蒸散量、年均湿润度、年均积温、经度、纬度等地理环境因子,采用多元线性回归的方法构建森林生物量遥感估测模型。通过样本检验,该模型对东北三省的森林生物量密度估测精度较高,与检验样本的平均每公顷生物量平均相差1.30%;通过样本定位检验,平均相差21.87%。该模型适宜在宏观尺度上估测森林生物量。
译 名：
Study on Monitoring Method of Forest Biomass Based on MODIS
作 者：
HAN Aihui1,2,ZHI Changgui2,WANG Xuejun1,2,XIA Chaozong2(1.The Key Laboratory for Silviculture and Conservation of Ministry of Education,Beijing Forestry University,Beijing,100083;2.Academy of Forestry Inventory and Planning,State Forestry Administration,Beijing,100714,China)
关键词：
forest biomass,remote sensing,MODIS,multiple linear regression model
摘 要：
In this paper,3 northeast provinces are used as the trial area.Multiple Linear Regression method is used to build the forest biomass RS estimation model.In the model building process,some plots' data of national forest inventory are used as the basic data,and time-serial NDVI of MODIS data and Annual Average Precipitation,Annual Average Evapotranspiration,Annual Average Wettability,Annual Average accumulated temperature,longitude and latitude are also used as independent variables.Test result shows that the accuracy of the model estimation is relatively high,the difference between average biomass per hectare of test plots and the estimated value based on MODIS is 1.30%;but the average difference by positioning test analyzing is 21.87%.So this forest biomass model is suitable for forest biomass macro monitoring.
