首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Mapping tree and shrub leaf area indices in an ombrotrophic peatland through multiple endmember spectral unmixing
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Mapping tree and shrub leaf area indices in an ombrotrophic peatland through multiple endmember spectral unmixing

机译:通过多端元光谱解混绘制全营养泥炭地树木和灌木叶面积指数

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摘要

Leaf area index (LAI) is an important parameter used by most process-oriented ecosystem models. LAI of forest ecosystems has routinely been mapped using spectral vegetation indices (SVI) derived from remote sensing imagery. The application of SVI-based approaches to map LAI in peatlands presents a challenge, mainly due to peatlands characteristic multi-layer canopy comprising shrubs and open, discontinuous tree canopies underlain by a continuous ground cover of different moss species, which reduces the greenness contrast between the canopy and the background. Our goal is to develop a methodology to map tree and shrub LAI in peatlands and similar ecosystems based on multiple endmember spectral mixture analysis (MESMA). This new mapping method is validated using LAI field measurements from a precipitation-fed (ombrotrophic) peatland near Ottawa, Ontario, Canada. We demonstrate first that three commonly applied SVI are not suitable for tree and shrub LAI mapping in ombrotrophic peatlands. Secondly, we demonstrate for a three-endmember model the limitations of traditional linear spectral mixture analysis (SMA) due to the unique and widely varying spectral characteristics of Sphagnum mosses, which are significantly different from vascular plants. Next, by using a geometric-optical radiative transfer model, we determine the nature of the equation describing the empirical relationship between shadow fraction and tree LAI using nonlinear ordinary least square (OLS) regression. We then apply this equation to describe the empirical relationships between shadow and shrub fractions obtained from mixture decomposition with SMA and MESMA, respectively, and tree and shrub LAI, respectively. Less accurate fractions obtained from SMA result in weaker relationships between shadow fraction and tree LAI (R{sup}2=0.61) and shrub fraction and shrub LAI (R{sup}2=0.49) compared to the same relationships based on fractions obtained from MESMA with R{sup}2 = 0.75 and R{sup}2 = 0.68, respectively. Cross-validation of tree LAI (R{sup}2=0.74; RMSE=0,48) and shrub LAI (R{sup}2=0.68; RMSE=0.42) maps using fractions from MESMA shows the suitability of this approach for mapping tree and shrub LAI in ombrotrophic peatlands. The ability to account for a spectrally varying, unique Sphagnum moss ground cover during mixture decomposition and a two layer canopy is particularly important.
机译:叶面积指数(LAI)是大多数面向过程的生态系统模型使用的重要参数。通常使用从遥感影像中得出的光谱植被指数(SVI)绘制森林生态系统的LAI。基于SVI的方法在泥炭地上绘制LAI的地图面临着挑战,这主要是由于泥炭地具有特征性的多层冠层,包括灌木和不连续的不连续苔藓覆盖的不连续树冠层,这降低了之间的绿色对比。顶篷和背景。我们的目标是根据多种末端成员光谱混合分析(MESMA),开发一种方法来绘制泥炭地和类似生态系统中的树木和灌木LAI。这项新的制图方法已通过加拿大安大略省渥太华附近的一个以降水喂养(营养缺陷型)泥炭地的LAI现场测量得到验证。我们首先证明了三种常用的SVI不适合在非营养型泥炭地的树木和灌木LAI绘图。其次,我们证明了一个三端成员模型由于泥炭藓的独特而广泛变化的光谱特征(与维管植物有很大不同)而限制了传统线性光谱混合分析(SMA)的局限性。接下来,通过使用几何光学辐射传递模型,我们使用非线性普通最小二乘(OLS)回归确定描述阴影分数与树LAI之间的经验关系的方程式的性质。然后,我们应用此方程来描述分别通过分别与SMA和MESMA混合分解以及分别由树和灌木LAI分解得到的阴影和灌木部分之间的经验关系。从SMA获得的精度较低的分数导致阴影分数与树LAI(R {sup} 2 = 0.61)和灌木分数与灌木LAI(R {sup} 2 = 0.49)之间的关系较弱,而基于R {sup} 2 = 0.75和R {sup} 2 = 0.68的MESMA。使用MESMA的分数对树LAI(R {sup} 2 = 0.74; RMSE = 0,48)和灌木LAI(R {sup} 2 = 0.68; RMSE = 0.42)映射进行交叉验证显示了此方法适用于映射树和灌木林在非营养营养泥炭地。在混合物分解和两层顶篷中考虑光谱变化,独特的泥炭藓地面覆盖的能力尤其重要。

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