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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Application of AVIRIS data in detection of oil-induced vegetation stress and cover change at Jornada, New Mexico
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Application of AVIRIS data in detection of oil-induced vegetation stress and cover change at Jornada, New Mexico

机译：AVIRIS数据在新墨西哥州乔纳达市的石油诱发植被应力和覆盖变化检测中的应用

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摘要

On June 1, 2000, an oil spill accident occurred along transportation pipeline located in the Jornada Experimental Range (USDA), Jornada, New Mexico, a long-term ecological research (LTER). In order to detect potential vegetation stress caused by the accident, two AVIRIS data sets of the oil spill area, before and after the oil release, are analyzed and the reliability of several techniques in the detection of vegetation stress is examined. The polynomial fitting and Lagrangian interpolation, and spectral mixture analysis (SMA) are applied to the AVIRIS data sets. The first two methods are applied for the detection of the "red-edge" shift in vegetation reflectance spectra, and the last for the detection of change in vegetation fraction. The results indicate that the polynomial fitting and Lagrangian interpolation both are able to detect a red-shift of the vegetation "red-edge", but the latter's performance depends on the band combination used and is sensitive to data noise. The polynomial fitting results are inconsistent in detection of "the red-edge" shift, while Lagrangian interpolation is not. Within the oil spill area, the fraction estimates of vegetation resulting from SMA demonstrate a decrease (10-30%) of the vegetation fraction after the accident, indicating stressed vegetation and cover change. The result also indicates that areas of extremely large decrease (>40%) in plant cover outside of the oil spill area is due to the response of grasses due to the water stress in 2000, and that the integration of some auxiliary data on ecological and climatological data with the analysis of remotely sensed data is thus very important to the interpretation of the detection results. A sensitivity analysis indicates that the detected vegetation cover change is insensitive to the noise introduced by the radiometric normalization.
机译：2000年6月1日，长期生态研究（LTER）在新墨西哥州乔纳达（Jornada）乔纳达实验区（USDA）的运输管道上发生了一次漏油事故。为了发现事故造成的潜在植被压力，分析了泄油前后两个溢油区的AVIRIS数据集，并检验了几种检测植被压力的技术的可靠性。将多项式拟合和拉格朗日插值以及频谱混合分析（SMA）应用于AVIRIS数据集。前两种方法用于检测植被反射光谱中的“红边”位移，后一种方法用于检测植被分数的变化。结果表明，多项式拟合和拉格朗日插值均能够检测植被“红边”的红移，但后者的性能取决于所使用的波段组合，并且对数据噪声敏感。多项式拟合结果在检测“红边”偏移时不一致，而在拉格朗日插值中则不一致。在溢油区域内，SMA造成的植被分数估算表明，事故发生后植被分数减少了（10-30％），这表明植被和覆盖物发生了变化。结果还表明，在漏油区之外的植物覆盖率下降幅度最大（> 40％）的区域是由于2000年的水分胁迫对草的响应，并且整合了一些有关生态和生态的辅助数据。因此，气候数据和遥感数据的分析对于解释检测结果非常重要。敏感性分析表明，检测到的植被覆盖度变化对辐射归一化引入的噪声不敏感。

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