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Comparative Assessment of Two Vegetation Fractional Cover Estimating Methods and Their Impacts on Modeling Urban Latent Heat Flux Using Landsat Imagery

机译:两种植被覆盖度估算方法的比较评价及其对利用Landsat影像建立城市潜热通量的影响。

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Quantifying vegetation fractional cover (VFC) and assessing its role in heat fluxes modeling using medium resolution remotely sensed data has received less attention than it deserves in heterogeneous urban regions. This study examined two approaches (Normalized Difference Vegetation Index (NDVI)-derived and Multiple Endmember Spectral Mixture Analysis (MESMA)-derived methods) that are commonly used to map VFC based on Landsat imagery, in modeling surface heat fluxes in urban landscape. For this purpose, two different heat flux models, Two-source energy balance (TSEB) model and Pixel Component Arranging and Comparing Algorithm (PCACA) model, were adopted for model evaluation and analysis. A comparative analysis of the NDVI-derived and MESMA-derived VFCs showed that the latter achieved more accurate estimates in complex urban regions. When the two sources of VFCs were used as inputs to both TSEB and PCACA models, MESMA-derived urban VFC produced more accurate urban heat fluxes (Bowen ratio and latent heat flux) relative to NDVI-derived urban VFC. Moreover, our study demonstrated that Landsat imagery-retrieved VFC exhibited greater uncertainty in obtaining urban heat fluxes for the TSEB model than for the PCACA model.
机译:量化植被分数覆盖度(VFC)并使用中分辨率遥感数据评估其在热通量建模中的作用受到的关注比异类城市地区要少。这项研究检查了两种方法(基于归一化植被指数(NDVI)和多端元光谱混合分析(MESMA)的方法),这些方法通常用于基于Landsat影像绘制VFC,以对城市景观中的表面热通量进行建模。为此,采用了两种不同的热通量模型,即两源能量平衡(TSEB)模型和像素分量安排和比较算法(PCACA)模型,以进行模型评估和分析。对源自NDVI和源自MESMA的VFC的比较分析表明,后者在复杂的城市地区实现了更准确的估算。当将两种VFC来源同时用作TSEB和PCACA模型的输入时,相对于NDVI衍生的城市VFC,源自MESMA的城市VFC产生了更准确的城市热通量(Bowen比和潜热通量)。此外,我们的研究表明,与PCACA模型相比,TSEB模型获得的Landsat影像校正VFC在获得城市热通量方面显示出更大的不确定性。

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