基于像元二分模型的森林郁闭度遥感估算

实现森林郁闭度的高精度估测,对于森林资源的监测与管理具有非常重要的意义。本文以小兴安岭带岭林业实验管理局为研究区,基于植被指数的像元二分模型进行了森林郁闭度的遥感反演,结果表明:模型的预估精度达到89.01%,决定系数R2达到0.859,RMSE为0.039,模型的一致性较好,可以实现大区域范围森林郁闭度的监测,满足了林业经营管理的需求。

Estimate of Forest Canopy Density Based on the Dimidiate Pixel Model by Using Remote Sensing Imagery

The high accuracy estimate of forest canopy is very important for the monitor and manages of forest resources. The study area was located in Dailing Forestry operation management zone. According to remote sensing and forest resource inventory data, dimidiate pixel model based on normalized difference vegetation index ( NDVI) was used to estimate the forest canopy density. Though the veri-fication, the predict accuracy of model is reached 89. 01％, the correlation coefficient is 0. 859 and root meant square error is 0. 039 between estimated value and measured value. The result of forest canopy density model has a good consistency and it can use in large area for monitor and manage forest resource.