Chinese Journal of Rice Science

• 研究报告 • Previous Articles     Next Articles

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

WANG Fu-min , HUANG Jing-feng , TANG Yan-lin , WANG Xiu-zhen   

  • Received:1900-01-01 Revised:1900-01-01 Online:2007-03-10 Published:2007-03-10

新型植被指数及其在水稻叶面积指数估算上的应用

王福民1;黄敬峰1,*;唐延林2;王秀珍3   

  1. 1浙江大学 农业遥感与信息技术应用研究所, 浙江大学 农业信息科学与技术中心, 浙江省农业遥感与信息技术重点研究实验室, 浙江 杭州 310029; 2贵州大学 理学院 物理系, 贵州 贵阳 550025; 3浙江省气象科学研究所, 浙江 杭州 310029; *通讯联系人, E-mail: hjf@zju.edu.cn

Abstract: Leaf area index(LAI)is not only an important attribute of land surface vegetation system,but also a key parameter for the models of global water balancing and carbon circulation.First of all,the reflectance values of Landsat-5 blue,green and red channels were simulated from rice reflectance spectrum.Secondly,the sensitivity of the bands to LAI was analyzed.Thirdly,the response and capability to estimate LAI of various NDVIs,which were established by substituting the red bands 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 result indicated that the sensitivity of red,green and blue bands to LAI were different under different conditions.When LAI is less than 3,red and blue bands are more sensitive to LAI.Though green band in the circumstances is less sensitive to LAI than red and blue bands,it is sensitive to LAI in a wide range.When the vegetation indices were constituted by all kinds of combinations of red,green and blue bands,the premise of making the sensitivity of these vegetation indices to LAI meaningful is that the value of one of the combinations is greater than 0.024,that is VIS>0.024.Otherwise,the vegetation indices would saturate,which would result in lower estimation accuracy of LAI.The capabilities of these vegetation indices derived from all kinds of combinations of red,green and blue bands to LAI estimation were compared.GNDVI and GBNDVI have the best relation with LAI.The capability of GNDVI and GBNDVI to LAI estimation was tested under different circumstances,and the same result was acquired.It can be seen that GNDVI and GBNDVI performed better to predict LAI than the conventional NDVI.

Key words: vegetation index, rice, leaf area index, reflectance spectrum, remote sensing

摘要: 叶面积指数LAI不仅是陆表植被系统的一个重要属性,而且是全球水平衡、碳循环等模型中的重要输入参数。首先通过使用水稻小区试验冠层光谱数据模拟Landsat5卫星蓝、绿、红光波段;其次分析了各个波段对LAI的敏感性;然后分析了由这个3个波段的所有组合分别代替常规NDVI中的红光波段构成的VNDVI对LAI变化的反应和对LAI的估算能力;最后使用不同条件下的水稻数据进行验证。结果表明,在不同的LAI范围,红绿蓝光3个波段对LAI有不同的敏感性。当LAI<3时,红蓝光波段敏感性较高。虽然这时绿光波段的敏感性不如红蓝光波段,然而绿光波段在更大的范围对LAI都有相当的敏感性。当采用红绿蓝光波段的各种组合构成植被指数时,如果要使这些植被指数不出现饱和现象,并使对LAI的敏感性有意义,其前提是要求这个波段或是波段组合的值要大于0.024,即VNDI(visible NDVI)公式中的VIS>0024,否则将可能产生饱和现象,而使LAI估算准确度降低。综合比较所有由红绿蓝光波段各种组合构成的植被指数对LAI的估算能力,认为GNDVI和GBNDVI与LAI有比较好的关系。使用其他条件下的水稻数据对各种NDVI的LAI估算能力进行了验证,仍然得到了同样的结论。可见,GNDVI和GBNDVI在估算LAI时确实比传统NDVI具有更好的效果。

关键词: 植被指数, 水稻, 叶面积指数, 反射光谱, 遥感