不同生活型植物非光合部分反射光谱和盖度的关系

Abstract

非光合植被（Non-photosynthetic Vegetation，NPV）既是陆地生态系统重要组成部分，也是全球C、N平衡分析中关键节点，其盖度是判断我国北方沙尘源区风沙活动强弱的重要指征。基于ASD光谱仪（Analytical Spectral Devices）所测地面高光谱数据对鄂尔多斯沙地草场不同生活型植物（草本、半灌木和灌木） NPV光谱特征进行了分析，构建了干枯燃料指数（Dead Fuel Index，DFI）、纤维素吸收指数（Cellulose Absorption Index，CAI）和NPV盖度（f_NPV）应用模型，并使用MCD43A4数据在不同草原区进行了验证。结果表明：（1）草本、半灌木、灌木和总体混合NPV光谱反射率具有相似变化趋势，但反射值存在显著差异。（2） DFI和CAI、CAI和f_NPV、DFI和f_NPV均呈显著正相关关系（P<0.001），DFI可以代替CAI进行f_NPV的估算。（3）不同草原区f_NPV存在异质性，草甸草原、典型草原、沙地草场和荒漠草原分别为75.95%、50.61%、45.88%和32.77%。DFI在典型草原区估算f_NPV效果最好（f_NPV1和f_NPV2平均差值为3.11%，最小差值为0.03%）。在草原区进行f_NPV估算时，不可将NPV作为均质体处理，还要剔除裸地干扰。;Non-photosynthetic vegetation (NPV) is a vital component of terrestrial ecosystem, as well as a critical hotspot in global carbon and nitrogen studies. In addition, its coverage in the source area of wind-blown sand in northern China indicates the intensity of wind-blown sand activities. As revealed from recently conducted studies, cellulose absorption index (CAI) was highlighted to be capable of more effectively reflecting the fractional cover of non-photosynthetic vegetation (f_NPV). However, there was no corresponding band (2000-2050 nm, 2080-2130 nm, and 2100-2240 nm) for CAI calculation in the 36 bands of MODIS data. Subsequently, under the introduction of dead fuel index (DFI), it can be employed directly to estimate f_NPV, whereas a question is whether DFI accurately reflect the content of NPV cellulose? Is it necessary to establish the relationship between CAI and DFI to achieve more accurate estimation of f_NPV? It has always been neglected by researchers. Therefore, this paper intended to study the distribution of f_NPV in various grassland, and compared the difference between direct estimation of f_NPV by DFI and indirect estimation of f_NPV by CAI, the influence of bare land on the estimation results were analyzed in order to explain the spatial heterogeneity characteristics of f_NPV in different grasslands. We analyzed the NPV spectral characteristics of different habitats NPV (herb, semi-shrub and shrub) in sandy grassland of Ordos and constructed the application model of DFI, CAI and f_NPV based on the ground hyper-spectral data measured by analytical spectral devices, and then validated in different grassland areas. The results showed that the NPV reflectance had similar trends of herb, semi-shrub, shrub and mixed NPV. There was a significantly positive correlation between DFI and CAI, CAI and f_NPV, DFI and f_NPV at the level of P<0.001, and DFI could better reflect the change of f_NPV. But the f_NPV value directly calculated by DFI was larger than the f_NPV that calculated indirectly by CAI, the average overestimation was 3.11% when eliminating bare ground. The difference between two values in typical grassland areas was 0.03%. In addition, the NPV should not be treated as a homogeneous material, and bare ground interference should be eliminated when performing f_NPV estimation.