基于ICESat-GLAS的坡地最大树高估测模型比较研究

地形坡度对星载LiDAR(lightdetection and ranging)估测最大树高具有较大的影响。为了提高坡度条件下树高的反演精度,通过建立坡地条件下5种不同的最大树高估测模型,前3个模型分别使用不同DEM(digital elevation model)数据的地形指数来量化地形坡度的Xing模型,第4个模型使用波形参数-未改进边缘长度来量化地形坡度,第5个模型与第4个模型类似,用改进边缘长度来替换未改进边缘长度。结果可知,波形参数模型的精度要高于使用DEM数据的地形指数的Xing模型的精度,第5个模型的精度要高于第4个模型的精度。表明波形参数量化地形坡度的能力要优于DEM数据的地形指数,而改进边缘长度模型更适合估测坡地的最大树高。

Comparison of ICESat-GLAS-based Estimation Models of Maximum Tree Height under Slope Terrain Condition

There is a great influence from the terrain slope in estimating the maximum tree height using spaceborne LiDAR (light detection and ranging).To improve the accuracy under the slope conditions,five different models for estimating the maximum tree height were proposed in this paper.The first three models were based on Xing s model,using the topographic index of different DEM (digital elevation model) data to quantify the terrain slope.The fourth model used the waveform parameter,original edge length,to quantify the terrain slope.Lastly,the fifth model was similar to the fourth,using improved edge length to replace the original.By analyzing the results of above-mentioned 5 models,it was found that the forth and fifty models based on the waveform parameter were with significantly higher accuracy than those of the first three models based on the topographic index of DEM data.Furthermore,the fifth model was with a better performance compared with the fourth.This investigation showed that waveform parameters,especially optimized edge length,were more capable than using the terrain index of DEM data to accurately assess the maximum tree height,due to its advantage in quantifying the terrain slope.