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Evaluation of ALOS/PALSAR L-Band Data for the Estimation of Eucalyptus Plantations Aboveground Biomass in Brazil

机译:ALOS / PALSAR L波段数据评估巴西桉树人工林地上生物量的估算

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The Phased Array L-band Synthetic Aperture Radar (PALSAR-1) has provided very useful images dataset for several applications such as forestry. L-Band radar measurements have been widely used but with somewhat contradictory conclusions on the potential of this radar wavelength to estimate the aboveground biomass (AGB). The first objective of this study was to analyze the L-band SAR backscatter sensitivity to forest biomass for plantations. The results showed that the radar signal is highly dependent on biomass only for values lower than 50 t/ha, which corresponds to plantations of approximately 3 years of age. Next, random forest (RF) regressions were performed to evaluate the potential of PALSAR data to predict the biomass. Regressions were constructed to link the biomass to both radar signal and age of plantations. Results showed that the age was the variable that best explained the biomass followed by the PALSAR HV polarized signal. For biomasses lower than 50 t/ha, HV signal and plantation age were found to have the same level of importance in predicting biomass. For biomasses higher than 50 t/ha, plantation age was the main variable in the RF models. The use of PALSAR signal alone did not correctly predict the biomass of plantations [ lower than 0.5 and root-mean-squared error (RMSE) higher than 46.7 t/ha]. The use of plantation age in addition to the PALSAR signal improved slightly the prediction results ( increased from 0.88 to 0.92 and RMSE decreased from 22.7 to 18.9 t/ha). PALSAR imagery does not allow a direct estimation of planting date of stands but can follow efficiently the occurrence of clear-cuts if images are acquired sequentially, therefore allowing a r- ugh estimate of the following plantation date because a stand of is generally replanted 2–4 months after cutting. With a time series of radar images, it could be, therefore, possible to estimate the plantation age, and therefore improving the estimates of plantation biomass.
机译:相控阵L波段合成孔径雷达(PALSAR-1)为诸如林业等多种应用提供了非常有用的图像数据集。 L波段雷达测量已被广泛使用,但在此雷达波长估计地上生物量(AGB)的潜力方面有一些矛盾的结论。这项研究的首要目的是分析人工林对森林生物量的L波段SAR反向散射敏感性。结果表明,雷达信号仅在值低于50 t / ha时才高度依赖生物量,这对应于大约3岁的人工林。接下来,进行随机森林(RF)回归以评估PALSAR数据预测生物量的潜力。构建回归模型,将生物量与雷达信号和人工林年龄联系起来。结果表明,年龄是最能解释生物量的变量,其次是PALSAR HV极化信号。对于低于50吨/公顷的生物量,HV信号和人工林年龄在预测生物量方面具有相同的重要性水平。对于高于50吨/公顷的生物量,人工林年龄是RF模型中的主要变量。单独使用PALSAR信号不能正确预测人工林的生物量[低于0.5且均方根误差(RMSE)高于46.7 t / ha]。除PALSAR信号外,使用人工林年龄也略微​​改善了预测结果(从0.88增至0.92,RMSE从22.7降至18.9吨/公顷)。 PALSAR图像无法直接估算林分的播种日期,但是如果顺序获取图像,则可以有效跟踪清晰出现的林木,因此可以对下一个播种日期进行粗略的估计,因为通常会重新种植林分2 –切割后4个月。因此,利用雷达图像的时间序列,可以估计人工林的年龄,从而改善人工林生物量的估计。

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