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基于无人机高光谱影像的植被覆盖度遥感估算模型比较

韦钦桦 罗文斐 李浩 唐凯丰

韦钦桦, 罗文斐, 李浩, 唐凯丰. 基于无人机高光谱影像的植被覆盖度遥感估算模型比较[J]. 华南师范大学学报(自然科学版), 2021, 53(6): 79-87. doi: 10.6054/j.jscnun.2021096
引用本文: 韦钦桦, 罗文斐, 李浩, 唐凯丰. 基于无人机高光谱影像的植被覆盖度遥感估算模型比较[J]. 华南师范大学学报(自然科学版), 2021, 53(6): 79-87. doi: 10.6054/j.jscnun.2021096
WEI Qinhua, LUO Wenfei, LI Hao, TANG Kaifeng. The Comparison of Remote Sensing Estimation Models for Fractional Vegetation Cover Based on UAV Hyperspectral Image[J]. Journal of South China normal University (Natural Science Edition), 2021, 53(6): 79-87. doi: 10.6054/j.jscnun.2021096
Citation: WEI Qinhua, LUO Wenfei, LI Hao, TANG Kaifeng. The Comparison of Remote Sensing Estimation Models for Fractional Vegetation Cover Based on UAV Hyperspectral Image[J]. Journal of South China normal University (Natural Science Edition), 2021, 53(6): 79-87. doi: 10.6054/j.jscnun.2021096

基于无人机高光谱影像的植被覆盖度遥感估算模型比较

doi: 10.6054/j.jscnun.2021096
基金项目: 

国家自然科学基金项目 40901232

高分辨率对地观测系统重大专项 11-Y20A40-9002-15/17

广东省自然资源厅科技项目 GDZRZYKJ-ZC2020003

广东省自然资源厅科技项目 GDZRZYKJ2020004

详细信息
    通讯作者:

    罗文斐, Email: luowenfei@m.scnu.edu.cn

  • 中图分类号: TP79

The Comparison of Remote Sensing Estimation Models for Fractional Vegetation Cover Based on UAV Hyperspectral Image

  • 摘要: 为了探寻光谱解混模型估算植被覆盖度的精度及适用性,对广东省中山市民众镇义仓村内的一块香蕉林地,利用无人机高光谱数据,比较了3种植被覆盖度估算的经典模型(像元二分模型、Carlson模型和Baret模型)以及目前较为常用的3种光谱解混模型(线性光谱混合模型(Linear Mixed Model, LMM)、后验多项式非线性混合模型(Polynomial Post-nonliner Mixing Model,PPNMM)和考虑光谱变异的正态组分模型(Normal Compositional Model,NCM))估算植被覆盖度的效果. 实验结果表明:像元二分模型高估了植被覆盖度;Carlson模型低估了植被覆盖度;Baret模型在低植被覆盖度区域内高估了植被覆盖度、在高植被覆盖度区域内低估了植被覆盖度;LMM模型在高植被覆盖度区域有较好的估算效果;PPNMM模型在低植被覆盖度出现小幅度高估;NCM模型估算的效果最佳.
  • 图  1  无人机影像实验区域

    Figure  1.  The UAV image of the research area

    图  2  无人机影像预处理流程图

    Figure  2.  The flowchart of UAV image processing

    图  3  无人机影像及4种分类方法的分类结果

    Figure  3.  The UAV images and classification results with 4 classification methods

    图  4  6种模型的植被覆盖度估算值与验证值的拟合

    Figure  4.  Fitting of estimated and verified values of vegetation coverage with 6 models

    表  1  6种模型估算植被覆盖度的精度评价

    Table  1.   The evaluation of the accuracy of the estimation of vegetation coverage with 6 models

    评价指标 像元二分模型 Carlson模型 Baret模型 LMM模型 PPNMM模型 NCM模型
    RMSE 0.132 7 0.087 3 0.076 6 0.058 2 0.064 9 0.040 1
    Ef/% 33.74 16.92 13.89 13.47 15.39 7.53
    下载: 导出CSV

    表  2  低植被覆盖度区域的估算精度评价

    Table  2.   The evaluation of the accuracy of the estimation of fractional low vegetation coverage area

    评价指标 像元二分模型 Carlson模型 Baret模型 LMM模型 PPNMM模型 NCM模型
    RMSE 0.158 4 0.079 3 0.060 9 0.074 4 0.081 2 0.039 5
    Ef/% 57.01 24.14 19.06 23.58 26.80 11.18
    下载: 导出CSV

    表  3  高植被覆盖度区域的估算精度评价

    Table  3.   The evaluation of the accuracy of the estimation of fractional high vegetation coverage area

    评价指标 像元二分模型 Carlson模型 Baret模型 LMM模型 PPNMM模型 NCM模型
    RMSE 0.106 7 0.093 5 0.087 4 0.039 8 0.047 0 0.040 5
    Ef/% 14.36 10.90 9.59 5.05 5.89 4.49
    下载: 导出CSV
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  • 收稿日期:  2020-12-29
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  • 刊出日期:  2021-12-25

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