Sensitivity of direct canopy gap fraction retrieval from airborne waveform lidar to topography and survey characteristics
Sensitivity of direct canopy gap fraction retrieval from airborne waveform lidar to topography and survey characteristics
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DOI：
10.1016/j.rse.2013.12.010
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发表时间：
2014-03-05
影响因子：
13.5
通讯作者：
Li, J. C.
中科院分区：
文献类型：
--
作者：
Chen, X. T.;Disney, M. I.;Li, J. C.
最近，Armston等人（2013年）已经证明，一种新的，基于物理的方法，直接检索冠层间隙概率P-间隙从波形激光雷达可以提高P-间隙的估计离散返回激光雷达数据。在澳大利亚的热带稀树草原林地环境中证明了这种方法的成功。这种方法的巨大优势在于它使用数据本身来求解冠层对比度项，即冠层和地面的反射率之比，rho（v）/rho（g）。以这种方式，该方法避免了通常需要克服rho（v）或rho（g）中的差异的局部校准。为了更普遍地使用该方法，必须在不同的地点和存在坡度以及不同的传感器和测量配置的情况下进行演示。如果它对这些东西，特别是斜率，都是鲁棒的，那么我们认为它可能会有广泛的用途。在这里，我们测试的鲁棒性检索的P-间隙波形激光雷达使用流域联合遥测实验研究数据集，在黑河流域地区的中国。这些数据包含显著的树冠、地形和测量变化，呈现出与以前使用的条件相当不同的一组条件。结果表明，rho（v）/rho（g）被认为是稳定的所有航班和所有水平的空间聚集。这有力地支持了新的P-间隙检索方法的鲁棒性，该方法假设这种关系是稳定的。P-间隙估计从hemiphotos和从波形激光雷达之间的比较显示协议与皮尔逊相关系数R = 0.91。波形激光雷达推导出的P-间隙估计值与半幅照片推导出的值一致，误差在8%以内，偏差为0.17%。新的波形模型在不同的偏离最低点的扫描角度下是稳定的，并且在所有情况下都存在高达26度的斜率，R >= 0.85。我们还表明，波形模型可以用来计算P-间隙使用的平均值的冠层回报，假设他们的分布是单峰的。最后，我们证明了该方法也可以应用于离散返回激光雷达数据，尽管精度略低，偏差较高，允许与先前收集的激光雷达数据集进行P-间隙比较。我们的研究结果表明，新的方法应该适用于估计P-间隙鲁棒大面积，并从激光雷达数据收集在不同的时间，使用不同的系统，一个越来越重要的要求。(C)2014作者爱思唯尔公司出版All rights reserved.
Recently, Armston et al. (2013) have demonstrated that a new, physically-based method for direct retrieval of canopy gap probability P-gap from waveform lidar can improve the estimation of P-gap over discrete return lidar data. The success of the approach was demonstrated in a savanna woodland environment in Australia. The huge advantage of this method is that it uses the data themselves to solve for the canopy contrast term i.e. the ratio of the reflectance from crown and ground, rho(v)/rho(g). In this way the method avoids local calibration that is typically required to overcome differences in either rho(v) or rho(g). To be more generally useful the method must be demonstrated on different sites and in the presence of slope and different sensor and survey configurations. If it is robust to these things, slope in particular, then we would suggest it is likely to be widely useful. Here, we test the robustness of the retrieval of P-gap from waveform lidar using the Watershed Allied Telemetry Experimental Research dataset, over the Heihe River Basin region of China. The data contain significant canopy, terrain and survey variations, presenting a rather different set of conditions to those previously used. Results show that rho(v)/rho(g) is seen to be stable across all flights and for all levels of spatial aggregation. This strongly supports the robustness of the new P-gap retrieval method, which assumes that this relationship is stable. A comparison between P-gap estimated from hemiphotos and from the waveform lidar showed agreement with Pearson correlation coefficient R = 0.91. The waveform lidar-derived estimates of P-gap agreed to within 8% of values derived from hemiphotos, with a bias of 0.17%. The new waveform model was shown to be stable across different off-nadir scan angles and in the presence of slopes up to 26 degrees with R >= 0.85 in all cases. We also show that the waveform model can be used to calculate P-gap using just the mean value of canopy returns, assuming that their distribution is unimodal. Lastly, we show that the method can also be applied to discrete return lidar data, albeit with slightly lower accuracy and higher bias, allowing P-gap comparisons with previously-collected lidar datasets. Our results show the new method should be applicable for estimating P-gap robustly across large areas, and from lidar data collected at different times and using different systems; an increasingly iinportant requirement. (C) 2014 The Authors. Published by Elsevier Inc. All rights reserved.