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植物光学模型估算叶片类胡萝卜素含量的一种双归一化差值-比值植被指数
引用本文:王弘,施润和,刘浦东,高炜. 植物光学模型估算叶片类胡萝卜素含量的一种双归一化差值-比值植被指数[J]. 光谱学与光谱分析, 2016, 36(7): 2189-2194. DOI: 10.3964/j.issn.1000-0593(2016)07-2189-06
作者姓名:王弘  施润和  刘浦东  高炜
作者单位:1. 华东师范大学地理信息科学教育部重点实验室,上海 200241
2. 华东师范大学环境遥感与数据同化联合实验室,上海 200241
3. 华东师范大学、美国科罗拉多州立大学中美新能源与环境联合研究院,上海 200062
4. Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins 80532, USA
基金项目:国家自然科学基金项目(41201358),上海市科委重点项目(15dz1207805,13231203804),上海市卫计委重点学科建设项目(15GWZK0201)
摘    要:运用高光谱技术进行植物叶片探测具有快速、无损、高精度等特点,在叶片色素等生化成分含量估算方面应用前景广阔。类胡萝卜素作为叶片中重要光合色素之一,因其在可见光区域与叶绿素的光谱吸收特征存在重叠,且其含量远低于叶绿素,导致利用光谱信息估算叶片类胡萝卜素含量存在困难,国内外少有针对类胡萝卜素含量的植被指数。利用高光谱数据光谱信息丰富的特点,提出一种以波段组合遍历与相关分析为基础,通过多指数协同来构建组合式的植被光谱指数的新方法。在PROSPECT叶片辐射传输模型模拟出大量具有不同生化和生物物理特征的叶片光谱的基础上,成功构建了一种在叶片水平下具有良好稳定性的类胡萝卜素含量估算新指数RVIDNDVI。结果表明,该方法构建的叶片类胡萝卜素光谱指数由两部分组成:由532和405 nm构建的窄波段NDVI(与类胡萝卜素、叶绿素均强相关)和由548和498 nm构建的窄波段NDVI(仅与叶绿素强相关)进行比值组合,能较好消除叶绿素含量对指数的干扰;通过减去对叶片结构高敏感的916 nm处反射率,能消除叶肉结构参数的影响,进一步提高指数的抗干扰能力。该研究得到的指数RVIDNDVI仅对叶片类胡萝卜素具有高敏感性,相关系数达到-0.94,对其进行指数拟合的R2达到0.834 4。经与模拟数据和实测数据的验证,该指数有较好的估算效果。

关 键 词:类胡萝卜素含量  多指数协同法  植被指数  PROSPECT模型  RVIDNDVI   
收稿时间:2015-05-14

Dual NDVI Ratio Vegetation Index: A Kind of Vegetation Index Assessing Leaf Carotenoid Content Based on Leaf Optical Properties Model
WANG Hong,SHI Run-he,LIU Pu-dong,GAO Wei. Dual NDVI Ratio Vegetation Index: A Kind of Vegetation Index Assessing Leaf Carotenoid Content Based on Leaf Optical Properties Model[J]. Spectroscopy and Spectral Analysis, 2016, 36(7): 2189-2194. DOI: 10.3964/j.issn.1000-0593(2016)07-2189-06
Authors:WANG Hong  SHI Run-he  LIU Pu-dong  GAO Wei
Abstract:With characteristics of rapidness ,non‐destructiveness and high precision in detecting plant leaves ,hyperspectral tech‐nology is promising in assessing the contents of leaf pigments and other biochemical components .Because the spectral absorption features of carotenoid and chlorophyll are overlapped in visible light region and that foliar carotenoid content is far lower than chlorophyll content ,studies about constructing vegetation indices (VIs) for carotenoid is rare at home and abroad though carote‐noid is one of the most important photosynthetic pigments .Hyperspectral data has abundant spectral information ,so this paper proposed a multiple spectral indices collaborative algorithm to construct VIs on the basis of band‐combination traversal and corre‐lation analysis .Through a large number of simulated leaf reflectance spectra under different biochemical components contents run on PROSPECT model ,a radiative transfer model ,we successfully constructed a new kind of stable vegetation index (VI) for as‐sessing carotenoid content at leaf level :RVIDNDVI .Our results indicate that RVIDNDVI is composed of two parts :(1)Narrow band NDVI constructed with 532 and 405 nm is high correlated with both carotenoid content and chlorophyll content while narrow band NDVI constructed with 548 and 498 nm is highly correlated with carotenoid content .The influence of chlorophyll content on RVIDNDVI can be eliminated with the ratio combination of these two indices .(2) The influence of mesophyll structure parame‐ter can be weakened by subtracting the reflectance at 916 nm ,which has strong correlation with mesophyll structure parameter . RVIDNDVI only has high sensitivity to carotenoid content (the correlation coefficient is -0.94) at leaf level and R2 of its exponen‐tial fit is 0.834 4 .The estimation of RVIDNDVI to carotenoid content can be verified with the validations of both simulated data and measured data .
Keywords:Carotenoid content  Multiple spectral indices collaborative algorithm  Vegetation index  PROSPECT model  RVIDNDVI
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