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New Vegetation Index and Its Application in Estimating Leaf Area Index of Rice

机译:新的植被指数及其在水稻叶面积指数估算中的应用

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摘要

Leaf area index (LAI) is an important characteristic of land surface vegetation system, and is also a key parameter for the models of global water balancing and carbon circulation. By using the reflectance values of Landsat-5 blue, green and red channels simulated from rice reflectance spectrum, the sensitivities of the bands to LAI were analyzed, and the response and capability to estimate LAI of various NDVIs (normalized difference vegetation indices), which were established by substituting the red band of general NDVI with all possible combinations of red, green and blue bands, were assessed. Finally, the conclusion was tested by rice data at different conditions. The sensitivities of red, green and blue bands to LAI were different under various conditions. When LAI was less than 3, red and blue bands were more sensitive to LAI. Though green band in the circumstances was less sensitive to LAI than red and blue bands, it was sensitive to LAI in a wider range. When the vegetation indices were constituted by all kinds of combinations of red, green and blue bands, the premise for making the sensitivity of these vegetation indices to LAI be meaningful was that the value of one of the combinations was greater than 0.024, i.e. visible reflectance (VIS) > 0.024. Otherwise, the vegetation indices would be saturated, resulting in lower estimation accuracy of LAI. Comparison on the capabilities of the vegetation indices derived from all kinds of combinations of red, green and blue bands to LAI estimation showed that GNDVI (Green NDVI) and GBNDVI (Green-Blue NDVI) had the best relations with LAI. The capabilities of GNDVI and GBNDVI to LAI estimation were tested under different circumstances, and the same result was acquired. It suggested that GNDVI and GBNDVI performed better to predict LAI than the conventional NDVI.
机译:叶面积指数(LAI)是陆地表面植被系统的重要特征,也是全球水平衡和碳循环模型的关键参数。通过利用水稻反射光谱模拟的Landsat-5蓝,绿和红通道的反射率值,分析了波段对LAI的敏感性,并估算了各种NDVI(归一化植被指数)的响应和估计LAI的能力,通过将普通NDVI的红色波段替换为红色,绿色和蓝色波段的所有可能组合,可以确定这些信号。最后,通过不同条件下水稻数据对结论进行了检验。在不同条件下,红色,绿色和蓝色谱带对LAI的敏感性不同。当LAI小于3时,红色和蓝色条带对LAI更加敏感。尽管在这种情况下,绿色波段对LAI的敏感程度不及红色和蓝色波段,但在更大范围内,它对LAI的敏感程度更高。当植被指数由红色,绿色和蓝色波段的各种组合构成时,使这些植被指数对LAI的敏感度有意义的前提是,其中一种组合的值大于0.024,即可见反射率(VIS)> 0.024。否则,植被指数将饱和,导致LAI的估计准确性降低。比较红色,绿色和蓝色波段的各种组合得出的植被指数对LAI的估计能力,表明GNDVI(绿色NDVI)和GBNDVI(绿色-蓝色NDVI)与LAI的关系最好。在不同情况下测试了GNDVI和GBNDVI估计LAI的能力,并获得了相同的结果。这表明GNDVI和GBNDVI在预测LAI方面比常规NDVI更好。

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