Estimation of Grassland Live Fuel Moisture Content From Ratio of Canopy Water Content and Foliage Dry Biomass
Estimation of Grassland Live Fuel Moisture Content From Ratio of Canopy Water Content and Foliage Dry Biomass
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根据冠层含水量与树叶干生物量之比估算草地活燃料含水量
DOI：
10.1109/lgrs.2015.2437391
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发表时间：
2015-06
影响因子：
4.8
通讯作者：
Tang Zhi
中科院分区：
文献类型：
--
作者：
Quan Xingwen;He Binbin;Li Xing;Tang Zhi
探索了一种根据冠层含水量（CWC）和叶子干生物量（FDB）的比率来估计活燃料含水量（LFMC）的新方法。 CWC 使用来自 Landsat 8 产品的 PROSAIL (PROSPECT + SAIL) 辐射传输模型进行估算。采用弱约束4维变分数据同化方法将时间估计的叶面积指数同化到土壤-水-大气-植物（SWAP）模型中，以优化模型控制变量。然后，用这组最佳控制变量重新初始化 SWAP 模型，并获得更好的 FDB 预测。结果表明，与现场测量值相比，估算的 CWC（R2 = 0.91，RMSE = 84.74 g/m2）和 FDB（R2 = 0.88，RMSE = 48.54 g/m2）达到了较高的准确度。然而，估计 LFMC 的准确性水平较差（R2 = 0.59，RMSE = 30.85%）。进一步分析发现，估计的 LFMC 对于低 LFMC 是可靠的，但对于高 LFMC 则受到挑战，这表明所提出的方法对于评估野火风险仍然有意义，因为野火通常发生在植被处于低 LFMC 条件下。
A novel way to estimate the live fuel moisture content (LFMC) was explored from the ratio of canopy water content (CWC) and foliage dry biomass (FDB). The CWC was estimated using the PROSAIL (PROSPECT + SAIL) radiative transfer model from the Landsat 8 product. A weak constraint 4-D variational data assimilation method was employed to assimilate the temporally estimated leaf area index into a soil-water-atmosphere-plant (SWAP) model for optimizing the model control variables. Then, the SWAP model was reinitialized with this optimum set of control variables, and better prediction of FDB was obtained. Results showed that a high accuracy level was achieved for the estimated CWC (R2 = 0.91, RMSE = 84.74 g/m2) and FDB (R2 = 0.88, RMSE = 48.54 g/m2) when compared with in situ measured values. However, the accuracy level of estimated LFMC was poor (R2 = 0.59, RMSE = 30.85%). Further analyses find that the estimated LFMC is reliable for low LFMC but challenged for high LFMC, which indicates that the presented method still makes sense to the assessment of wildfire risk since the wildfire generally occurs when the vegetation is in low LFMC condition.
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DOI：
10.1109/jstars.2009.2014008
发表时间：
2009-02
影响因子：
5.5
作者：
M. Yebra;E. Chuvieco
通讯作者：
M. Yebra;E. Chuvieco
影响因子：
8.2
作者：
M. Montopoli;N. Pierdicca;F. Marzano
通讯作者：
M. Montopoli;N. Pierdicca;F. Marzano
影响因子：
8.2
作者：
J. Qin;S. Liang;Xiaowen Li;Jindi Wang
通讯作者：
J. Qin;S. Liang;Xiaowen Li;Jindi Wang
影响因子：
8.9
作者：
Tremolet, Yannick
通讯作者：
Tremolet, Yannick
DOI：
--
发表时间：
1984-02
期刊：
--
影响因子：
--
作者：
W. Verhoef
通讯作者：
W. Verhoef