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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Monitoring canopy biophysical and biochemical parameters in ecosystem scale using satellite hyperspectral imagery: An application on a Phlomis fruticosa Mediterranean ecosystem using multiangular CHRIS/PROBA observations
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Monitoring canopy biophysical and biochemical parameters in ecosystem scale using satellite hyperspectral imagery: An application on a Phlomis fruticosa Mediterranean ecosystem using multiangular CHRIS/PROBA observations

机译：使用卫星高光谱图像监测生态系统范围内的冠层生物物理和生化参数：使用多角度CHRIS / PROBA观测值在Phlomis fruticosa地中海生态系统中的应用

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This study focuses on the potential of satellite hyperspectral imagery to monitor vegetation biophysical and biochemical characteristics through narrow-band indices and different viewing angles. Hyperspectral images of the CHRIS/PROBA sensor in imaging mode 1 (5 observation angles, 62 bands, 410–1005 nm) were acquired throughout a two-year period for a Mediterranean ecosystem fully covered by the semi-deciduous shrub Phlomis fruticosa. During each acquisition, coincident ecophysiological field measurements were conducted. Leaf area index (LAI), leaf biochemical content (chlorophyll a, chlorophyll b, carotenoids) and leaf water potential were measured. The hyperspectral images were corrected for coherent noises, cloud and atmosphere, in order to produce ground reflectance images. The reflectance spectrum of each image was used to calculate a variety of vegetation indices (VIs) that are already published in relevant literature. Additionally, all combinations of the 62 bands were used in order to calculate Normalized Difference Spectral Indices (NDSI(x,y)) and Simple Subtraction Indices (SSI(x,y)). The above indices along with raw reflectance and reflectance derivatives were examined for linear relationship with the ground-measured variables and the strongest relationships were determined. It is concluded that higher observation angles are better for the extraction of biochemical indices. The first derivative of the reflectance spectra proved to be very useful in the prediction of all measured variables. In many cases, complex and improved spectral indices that are proposed in the literature do not seem to be more accurate than simple NDSIs such as NDVI. Even traditional broadband NDVI is proved to be adequate in LAI prediction, while green bands seem also very useful. However, in biochemical estimation narrow bands are necessary. Indices that incorporate red, blue and IR bands, such as PSRI, SIPI and mNDVI presented good performance in chlorophyll estimation, while CRI did not show any relevance to carotenoids and WI was poorly correlated to water potential. Moreover, analyses indicated that it is very important to use a near red-edge band (701 nm) for effective chlorophyll index design. SSIs that incorporate 701 nm with 511 or 605 nm showed best performance in chlorophyll determination. For carotenoid estimation, a band on the edge of carotenoid absorption (511 nm) combined with a red band performed best, while a normalized index of two water absorption bands (945, 971 nm) proved to be an effective water index. Finally, the attempt to investigate stress conditions through pigment ratios resulted in the use of the band centred at 701 nm.
机译：这项研究侧重于卫星高光谱图像通过窄带指数和不同视角监测植被生物物理和生化特征的潜力。在为期两年的时间内，对于完全被半落叶灌木金缕梅覆盖的地中海生态系统，在成像模式1（5个观察角，62个波段，410-1005 nm）中获取了CHRIS / PROBA传感器的高光谱图像。在每次采集过程中，都要进行同步的生态生理场测量。测量叶面积指数（LAI），叶生化含量（叶绿素a，叶绿素b，类胡萝卜素）和叶水势。为了产生地面反射率图像，对高光谱图像进行了相干噪声，云和大气校正。每个图像的反射光谱用于计算各种植被指数（VI），这些指数已在相关文献中发表。此外，使用62个波段的所有组合来计算归一化差异光谱指数（NDSI（x，y））和简单减法指数（SSI（x，y））。检验了上述指标以及原始反射率和反射率导数与地面测量变量的线性关系，并确定了最强的关系。结论是，较高的观察角度对提取生化指标较好。事实证明，反射光谱的一阶导数对于预测所有测量变量非常有用。在许多情况下，文献中提出的复杂和改进的光谱指数似乎并不比简单的NDSI（例如NDVI）更准确。事实证明，即使传统的宽带NDVI也可以用于LAI预测，而绿色频段似乎也非常有用。然而，在生化估计中，窄带是必要的。包含红色，蓝色和红外波段的指标，例如PSRI，SIPI和mNDVI，在叶绿素估计方面表现出良好的性能，而CRI与类胡萝卜素没有任何相关性，而WI与水势的相关性很差。此外，分析表明，对于有效的叶绿素指数设计，使用近红边带（701 nm）非常重要。将701 nm与511或605 nm结合的SSI在叶绿素测定中表现出最佳性能。对于类胡萝卜素的估计，类胡萝卜素吸收（511 nm）边缘上的带结合红色带表现最佳，而两个吸水带（945、971 nm）的归一化指数被证明是有效的水指数。最后，通过颜料比率研究应力条件的尝试导致使用以701 nm为中心的谱带。

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