地球信息科学学报 ›› 2019, Vol. 21 ›› Issue (6): 948-957.doi: 10.12082/dqxxkx.2019.180513

• 遥感科学与应用技术 • 上一篇    下一篇

南方红壤侵蚀区长汀县不同生态恢复年限下芒萁叶绿素含量的高光谱估算模型

邓超1,2(), 陈志彪1,2,*(), 陈海滨1,2, 陈志强1,2   

  1. 1. 福建师范大学 湿润亚热带生态地理过程教育部重点实验室,福州 350007
    2. 福建师范大学地理科学学院,福州 350007
  • 收稿日期:2018-10-12 修回日期:2019-02-25 出版日期:2019-06-15 发布日期:2019-06-15
  • 通讯作者: 陈志彪 E-mail:1558083334@qq.com;chenzhib408@vip163.com
  • 作者简介:

    作者简介:邓超(1992-),女,四川资阳人,硕士生,研究方向为侵蚀过程与生态调控。E-mail: 1558083334@qq.com

  • 基金资助:
    国家重点研发计划项目(2016YFC0502905);福建省社会发展引导性(重点)项目(2016Y0024);福建省教育厅中青年教师教育科研项目(JT180292)

Hyperspectral Estimation Models of Chlorophyll Content for Dicranopteris Dichotoma Leaves at Different Ecological Restoration Stages in the Eroded Red Soil Areas of Southern China

Chao DENG1,2(), Zhibiao CHEN1,2,*(), Haibin CHEN1,2, Zhiqiang CHEN1,2   

  1. 1. Key Laboratory for Humid Subtropical Eco-geographical Processes of the Ministry of Education, Fujian Normal University, Fuzhou 350007, China
    2. College of Geographical Science, Fujian Normal University, Fuzhou 350007, China
  • Received:2018-10-12 Revised:2019-02-25 Online:2019-06-15 Published:2019-06-15
  • Contact: Zhibiao CHEN E-mail:1558083334@qq.com;chenzhib408@vip163.com
  • Supported by:
    National Key Research and Development Program of China, No.2016YFC0502905;Social Development Pilot Project of Fujian, No.2016Y0024;Education Research Project for Young and middle-aged Teachers of Fujian Education Department, No.JT180292

摘要:

芒萁是南方红壤侵蚀区生态恢复重要的地带性草本植物,对生态系统修复具有重要作用,监测其叶绿素含量能有效诊断生长健康状况。本文以福建省长汀县朱溪流域6个不同生态恢复年限下的芒萁叶片高光谱反射数据以及实测叶绿素含量为数据源,借助高光谱遥感技术分析不同恢复年限芒萁叶片原始光谱特征,筛选出光谱敏感波段并构建光谱指数,基于相关性分析,建立芒萁叶绿素单变量以及多元逐步回归模型,并确定最佳估算模型。结果表明:高光谱指数建立的单变量估算模型中,改进红边归一化植被指数(mNDVI705)、叶面叶绿素指数(LCI)、红边指数(Vog)、比值光谱指数(RVI603/407)、NDVI[603,407]高光谱指数建立的二次模型精度高,建模决定系数R2均超过了0.8,其中以高光谱指数为自变量建立的多元回归模型拟合R2值(0.886)最高。综合建模精度和模型验证精度,LCI指数构建的单变量模型以及基于高光谱指数的多元回归模型是估算芒萁叶片叶绿素含量最佳模型。本研究建立的叶绿素高光谱估算模型对快速、无损地监测水保植物芒萁生长具有重要意义。

关键词: 南方红壤侵蚀区, 生态恢复, 芒萁, 叶绿素含量, 高光谱指数, 估算模型, 长汀县朱溪流域

Abstract:

Dicranopteris dichotoma is an important zonal herbaceous plant for ecological restoration in the eroded red soil areas of southern China, and is an effective control of soil erosion. Using remote sensing techniques to monitor the chlorophyll content can help diagnose the vegetation growth and healthy condition of dicranopteris dichotoma. Based on hyperspectral reflectance data and the corresponding chlorophyll contents of dicranopteris dichotoma leaf from six different ecological restoration stages in Zhuxi small watershed of Changting County, Fujian Province, this study analyzed the hyperspectral curve properties of leaf, transformed the original spectral into the first derivative, and selected the sensitive wavebands to create ratio (RVI) and normalized (NDVI, FDNDVI) hyperspectral indices. Then correlation analysis was conducted for the chlorophyll contents and hyperspectral indices which were selected from reported indices and newly constructed indcies with sensitive wavelengths. Based on the correlation coefficients, we can chose the best indices to create estimation models. The linear, exponential, multiplicative, quadratic polynomial, logarithmic, and multivariate regression models were constructed for comparison. Furthermore, the optimal estimation model was determined by the accuracy of each estimation model. Results showed that the sensitive wavelengths of the original spectral for dicranopteris dichotoma leaf at different ecological restoration stages were 407 nm, 603 nm, and that the optimal wavebands of the first derivative were 463 nm, 554 nm, 674 nm, and 739 nm. The relationship between the chlorophyll content of dicranopteris dichotoma leaf and the hyperspectral indices of red edge position (λr), NDVI[603, 407], Modified Red Edge Normalized Difference Vegetation Index (mNDVI705), Vogelmann Index (Vog) were very significant, and the correlation coefficients were over 0.85. The estimation models of chlorophyll content established by hyperspectral indices of mNDVI705, Leaf Chlorophyll Index (LCI), Vog, RVI603/407, NDVI[603, 407] showed better test results, and the R2 were over 0.8. The model established by FDNDVI[739, 463] index had the highest verification accuracy, and the R2 reached 0.741. The multivariate regression model based on hyperspectral indices got highest test results with the highest R2. Therefore, the LCI index and the multivariate regression model based on hyperspectral indices have the strongest ability for predicting chlorophyll concentration, which provides scientific basis for dynamic monitoring of dicranopteris dichotoma in the eroded red soil regions of southern China. It is significant for monitoring soil and water conservation plants. Meanwhile, the objective of this research was to provide effective technical support for ecological restoration by building hyperspectral estimation models of chlorophyll content, with a rapid and non-destructive method for monitoring vegetation growth.

Key words: eroded red soil areas, ecological restoration, dicranopteris dichotoma, chlorophyll content, spectral index, estimation, Zhuxi small watershed of Changting County