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Retrieval biomass of a large Venezuelan pine plantation using JERS-1 SAR data: analysis of forest structure impact on radar signature

机译:使用JERS-1 SAR数据检索委内瑞拉大松人工林的生物量:分析森林结构对雷达特征的影响

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Studies are needed to evaluate the ability of present or future SAR data to extract forest attributes over various sites. This study focuses on large unmanaged pine plantations in a vast flat area of ca. 500,000 ha where the tree biomass ranges from 0 to 200 m{sup}3/ha corresponding to different forest canopy structures. Results show a good correlation between the backscattering coefficient σ{sup}0 (with a 6-dB dynamic range and R{sup}2≥.8), the stand timber volume and the stand density. The trend is mainly driven by stand density and different relationships are observed according to age class, which explicitly points out the effects of canopy structure on the backscattering level. Stem volume is derived from the inversion of statistical and semiempirical models, which take these effects into account. Inversion results show that forest biomass attributes can be estimated with relatively small errors commensurate with those achieved by field measurements. Best overall accuracy of ca. 21 m{sup}3/ha is reached with the semiempirical model. Error decomposition as a function of age classes shows that, for the same biomass range, errors are higher for old stands than for young stands. Finally, the results indicate that (1) JERS-1 data can be used in an operational way for estimating the biomass of such plantations and (2) it is necessary to take forest stand structure into account. In order to develop reliable biomass-retrieval schemes, future research should focus on examining in a more mechanistic way the relationship between canopy structure and radar signature.
机译:需要进行研究以评估当前或将来的SAR数据在各个站点上提取森林属性的能力。这项研究的重点是在约一个广阔的平坦区域中的大型未经管理的松树人工林。 500,000公顷,其中树木生物量范围从0到200 m {sup} 3 / ha,对应于不同的林冠结构。结果表明,背向散射系数σ{sup} 0(动态范围为6 dB,R {sup}2≥.8)与林分木材体积和林分密度之间具有良好的相关性。这种趋势主要是由林分密度驱动的,并且根据年龄类别观察到了不同的关系,从而明确指出了冠层结构对反向散射水平的影响。茎的体积源自统计和半经验模型的反演,这些模型考虑了这些影响。反演结果表明,森林生物量属性的估计误差与通过实地测量获得的误差相当小。最佳整体精度半经验模型达到21 m {sup} 3 / ha。作为年龄等级函数的误差分解表明,对于相同的生物量范围,旧林分的误差高于年轻林分。最后,结果表明:(1)JERS-1数据可以以可操作的方式用于估算此类人工林的生物量,(2)必须考虑林分结构。为了开发可靠的生物量回收方案,未来的研究应集中在以一种更机械的方式研究冠层结构与雷达特征之间的关系。

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