New Vegetation Index and Its Application in Estimating Leaf Area Index of Rice
New Vegetation Index and Its Application in Estimating Leaf Area Index of Rice
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DOI：
10.1016/s1672-6308(07)60027-4
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发表时间：
2007-09
期刊：
影响因子：
4.8
通讯作者：
Fumin Wang;Jingfeng Huang;Yan-lin Tang;Xiuzhen Wang
中科院分区：
文献类型：
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作者：
Fumin Wang;Jingfeng Huang;Yan-lin Tang;Xiuzhen Wang
叶面积指数（LAI）是陆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。利用水稻反射光谱模拟的Landsat-5蓝、绿色和红通道反射率值，分析了各波段对LAI的敏感性，并评价了用红、绿色和蓝色波段组合替代常规NDVI红色波段建立的各种归一化植被指数（NDVI）的响应和估算LAI的能力。最后，用不同条件下的水稻数据对结论进行了检验。红、绿色和蓝色波段对叶面积指数的敏感性在不同条件下不同。当叶面积指数小于3时，红、蓝波段对叶面积指数较敏感。绿色波段对叶面积指数的敏感性低于红、蓝波段，但对叶面积指数的敏感范围更广。当植被指数由红、绿色和蓝色波段的各种组合构成时，使这些植被指数对叶面积指数的敏感性有意义的前提是其中一种组合的值大于0.024，即可见光反射率（维斯）> 0.024。否则，植被指数会饱和，导致LAI的估计精度降低。通过比较红、绿色和蓝色波段的各种组合的植被指数对LAI的估算能力，发现GNDVI（绿色NDVI）和GBNDVI（绿-蓝NDVI）与LAI的相关性最好。在不同条件下对GNDVI和GBNDVI估算叶面积指数的能力进行了检验，得到了相同的结果。结果表明，GNDVI和GBNDVI对LAI的预测效果优于常规NDVI。
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, ie 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.