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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Estimation of vegetation water content and photosynthetic tissue area from spectral reflectance: a comparison of indices based on liquid water and chlorophyll absorption features
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Estimation of vegetation water content and photosynthetic tissue area from spectral reflectance: a comparison of indices based on liquid water and chlorophyll absorption features

机译:从光谱反射率估算植被含水量和光合组织面积:基于液态水和叶绿素吸收特征的指标比较

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Because of the high water content of vegetation, water absorption features dominate spectral reflectance of vegetation in the near-infrared region of the spectrum. In comparison to indices based on chlorophyll absorption features (such as the normalized difference vegetation index (NDVI)), indices based on the water absorption bands are expected to "see" more deeply into thick canopies and have a preferential sensitivity to thin as opposed to thick tissues. These predictions are based on the much lower absorption coefficients for water in the short wavelength water bands as compared to chlorophyll. Thus, the water bands may have advantages over NDVI for remote sensing of photosynthetic tissues. Pres ions studies have primarily related water band indices (WI) to leaf area index (LAI). Here we expand the definition of photosynthetic tissues to include thin green stems and fruit and measure a wide range of species to determine the influence of variable tissue morphologies and canopy structures on these relationships. As expected, indices based on reflectance in the water absorption bands in the near infrared were best correlated with the water content of thin tissues (less than 0.5-cm thickness). The choice of wavelength for a water index was much more important for thick than for thin canopies, and the best wavelengths were those where water absorptance was weak to moderate. We identified three wavelength regions (950-970, 1150-1260 and 1520-1540 nm) that produced the best overall correlations with water content. Comparison of these wavelength regions with the atmospheric 'windows" where water vapor absorption is minimal suggests that the 1150-1260 and 1520-1540 nm regions would be the best wavelengths for satellite remote sensing of water content. We also developed and tested a ness' Canopy Structure Index (CSI) that combines the low absorptance water bands with the simple ratio vegetation index (SR) to produce an index with a wider range of sensitivity to photosynthetic tissue area at all canopy thicknesses. CSI was better than either WI or SR alone for prediction of total area of photosynthetic tissues. However, SR was best for prediction of leaf area when other green tissues were excluded. All of these relation ships showed good generality across a wide range of species and functional types.
机译:由于植被的含水量高,在光谱的近红外区域中,水分吸收特征主导着植被的光谱反射率。与基于叶绿素吸收特征的指数(例如归一化植被指数(NDVI))相比,基于吸水带的指数有望更“深入”到厚冠层中,并且对薄层具有优先的敏感性。厚组织。这些预测是基于与叶绿素相比,短波长水带中的水吸收系数低得多。因此,对于光合组织的遥感,水带可能具有优于NDVI的优势。离子研究主要将水带指数(WI)与叶面积指数(LAI)相关。在这里,我们将光合作用组织的定义扩展到包括稀薄的绿色茎和果实,并测量各种各样的物种,以确定可变的组织形态和冠层结构对这些关系的影响。不出所料,基于近红外吸水带反射率的指标与薄组织(厚度小于0.5厘米)的水分含量最相关。较厚的冠层,对于厚的冠层来说,水分指数的波长选择更为重要,而最佳的波长是吸水率弱至中等的波长。我们确定了三个波长区域(950-970、1150-1260和1520-1540 nm),它们与水含量产生了最佳的整体相关性。将这些波长区域与水蒸气吸收最少的大气“窗口”进行比较表明,1150-1260和1520-1540 nm区域将是卫星遥感水含量的最佳波长。我们还开发并测试了一种结合了低吸收水带和简单比率植被指数(SR)的冠层结构指数(CSI),可得出在所有冠层厚度下对光合组织区域的敏感性范围更广的指数,CSI比单独使用WI或SR都要好SR用于预测光合组织的总面积,但是当排除其他绿色组织时,SR最适合预测叶的面积,所有这些关系在所有物种和功能类型上均显示出良好的通用性。

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