【摘要】：林地葉面積指數(shù)(Leaf area index,LAI)的準(zhǔn)確估測是精準(zhǔn)林業(yè)的重要體現(xiàn)。為了快速、準(zhǔn)確、無損監(jiān)測林地LAI,利用LAI-2200型植物冠層分析儀獲取福建省西部森林樣地的LAI數(shù)據(jù),結(jié)合同期Pleiades衛(wèi)星影像計(jì)算12種遙感植被指數(shù),分析了各樣地實(shí)測LAI數(shù)據(jù)和相應(yīng)植被指數(shù)的相關(guān)性,進(jìn)而使用隨機(jī)森林(RF)算法構(gòu)建了林地LAI估算模型,以支持向量回歸(SVR)模型和反向傳播神經(jīng)網(wǎng)絡(luò)(BP)模型作為參比模型,以決定系數(shù)(R~2)、均方根誤差(RMSE)、平均相對誤差(MAE)和相對分析誤差(RPD)為指標(biāo)評價(jià)并比較了模型預(yù)測精度。結(jié)果表明:全樣本數(shù)據(jù)中,各植被指數(shù)與對應(yīng)LAI值均呈極顯著相關(guān)(P0.01),且相關(guān)系數(shù)都大于0.4;RF模型在3次不同樣本組中的預(yù)測精度均高于同期的SVR模型和BP模型;3個(gè)樣本組中RF模型的LAI估測值與實(shí)測值的R~2分別為0.688、0.796和0.707,RPD分別為1.653、1.984和1.731,均高于同期SVR模型和BP模型,對應(yīng)的RMSE分別為0.509、0.658和0.696,MAE分別為0.417、0.414和0.466,均低于同期其他2種模型。
[Abstract]:The accurate estimation of forest leaf area index (Leaf area index,LAI) is an important embodiment of precision forestry. In order to quickly, accurately and accurately monitor forest land LAI, to obtain LAI data of forest sample land in western Fujian Province by LAI-2200 plant canopy analyzer, and to calculate 12 remote sensing vegetation indices by combining Pleiades satellite images. The correlation between the measured LAI data and the vegetation index was analyzed, and then the estimation model of forest land LAI was constructed by using the stochastic forest (RF) algorithm. The support vector regression (SVR) model and the backpropagation neural network (BP) model were used as the reference model. The prediction accuracy of the model was evaluated and compared with the determination coefficient (Ru 2), the mean relative error (MAE) of the root mean square error (RMSE),) and the relative analysis error (RPD). The results show that, in the whole sample data, Each vegetation index was significantly correlated with the corresponding LAI value (P0.01), and the correlation coefficient was greater than 0.4g RF model. The prediction accuracy of RF model in three different sample groups was higher than that of SVR model and BP model in the same period, and the LAI estimation value of RF model in three sample groups was higher than that of RF model. Compared with the measured values, the RPD-values of RN-2 were 0.688U 0.796 and 0.707 g, respectively, which were 1.653U 1.984 and 1.731respectively, which were higher than those of SVR model and BP model. The corresponding RMSE were 0.509 and 0.658, respectively, and 0.669 were 0.417, 0.414 and 0.466, respectively, which were lower than those of the other two models at the same time.
【作者單位】： 福建農(nóng)林大學(xué)3S技術(shù)與資源優(yōu)化利用福建省高校重點(diǎn)實(shí)驗(yàn)室;福建農(nóng)林大學(xué)林學(xué)院;
【基金】：國家自然科學(xué)基金項(xiàng)目(41401385)
【分類號】：S771.8;TP79

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