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基于ZY-3卫星多光谱影像估算浙江省乔木林地上碳密度

郑冬梅 王海宾 夏朝宗 陈健 侯瑞萍 郝月兰 安天宇

郑冬梅, 王海宾, 夏朝宗, 陈健, 侯瑞萍, 郝月兰, 安天宇. 基于ZY-3卫星多光谱影像估算浙江省乔木林地上碳密度[J]. 北京林业大学学报, 2020, 42(1): 65-74. doi: 10.12171/j.1000-1522.20180351
引用本文: 郑冬梅, 王海宾, 夏朝宗, 陈健, 侯瑞萍, 郝月兰, 安天宇. 基于ZY-3卫星多光谱影像估算浙江省乔木林地上碳密度[J]. 北京林业大学学报, 2020, 42(1): 65-74. doi: 10.12171/j.1000-1522.20180351
Zheng Dongmei, Wang Haibin, Xia Chaozong, Chen Jian, Hou Ruiping, Hao Yuelan, An Tianyu. Estimation of above-ground carbon density of arbor forest in Zhejiang Province of southern China based on ZY-3 satellite multispectral image[J]. Journal of Beijing Forestry University, 2020, 42(1): 65-74. doi: 10.12171/j.1000-1522.20180351
Citation: Zheng Dongmei, Wang Haibin, Xia Chaozong, Chen Jian, Hou Ruiping, Hao Yuelan, An Tianyu. Estimation of above-ground carbon density of arbor forest in Zhejiang Province of southern China based on ZY-3 satellite multispectral image[J]. Journal of Beijing Forestry University, 2020, 42(1): 65-74. doi: 10.12171/j.1000-1522.20180351

基于ZY-3卫星多光谱影像估算浙江省乔木林地上碳密度

doi: 10.12171/j.1000-1522.20180351
基金项目: 国家林业局948项目(2015-4-23),国家重点林业工程监测技术示范推广项目([2015]02号)
详细信息
    作者简介:

    郑冬梅,教授级高级工程师。主要研究方向:森林资源监测及遥感技术应用。Email:zhengdm2001@sina.com 地址:100714北京市东城区和平里东街18号国家林业和草原局调查规划设计院

  • 中图分类号: S771.5; TP701

Estimation of above-ground carbon density of arbor forest in Zhejiang Province of southern China based on ZY-3 satellite multispectral image

  • 摘要: 目的基于覆盖浙江省的ZY-3卫星影像以及LULUCF碳汇监测样地数据,以浙江省乔木林地上碳密度为研究对象,尝试构建一个自动化提取浙江省乔木林地上碳密度的技术方法。方法分别在矢量标志建立、光谱信息提取、解译标志提纯、ZY-3卫星影像分类、自变量优选、建模方法优选、碳密度图制作等方面开展相关研究测试。结果本研究在解译标志提纯后对ZY-3影像进行分类的精度高于提纯前的影像分类精度;采用的kNN法对ZY-3影像进行分类的精度(平均总精度为80.31%,平均Kappa系数为0.69,乔木林平均用户精度为91.86%,乔木林平均生产者精度为80.85%)高于最大似然分类法(平均总精度为78.56%,平均Kappa系数为0.62,乔木林平均用户精度为89.68%,乔木林平均生产者精度为77.79%);在选用的建模方法中,kNN法构建的模型精度(平均RMSE为15.64 t/hm2,平均RRMSE为23.53%)优于稳健估计法(平均RMSE为17.63 t/hm2,平均RRMSE为25.11%)。最后,生成了浙江省乔木林地上碳密度分布图。结论本研究可为省域或更大尺度范围的乔木林地上或森林碳密度估算提供一个新的路径,为实现自动化估算碳密度以及其他森林参数提供参考。

     

  • 图  1  研究技术路线

    Figure  1.  Technology roadmap of the study

    图  2  LULUCF碳汇监测样地分布图和样地区划图

    Figure  2.  Distribution map of LULUCF carbon sink monitoring plots and plot division map

    图  3  基于单景ZY-3影像建立的矢量标志

    Figure  3.  Extraction result of vector signs from single-view ZY-3 image

    图  4  灰度值梯度法提纯解译标志示意图

    Figure  4.  Gray scale gradient method for purification interpretation signs

    图  5  乔木林解译标志提纯前和提纯后

    Figure  5.  Interpretation signs before and after purification

    图  6  单个解译标志的提纯结果

    Figure  6.  Purification results of single interpretation mark

    图  7  ZY-3影像的分类精度及Kappa系数变化趋势图(27景)

    Figure  7.  Classification accuracy and Kappa coefficient trend of ZY-3 images (27 scenes)

    图  8  ZY-3影像的分类总精度及Kappa系数变化趋势图(27景)

    Figure  8.  Classification accuracy and Kappa coefficient trend of ZY-3 images (27 scenes)

    图  9  两种不同估算方法的均方根误差和相对均方根误差变化趋势(27景)

    Figure  9.  RMSE and RRMSE trends of two different estimation methods (27 scenes)

    图  10  基于ZY-3影像反演的浙江省乔木林地上碳密度灰度图

    Figure  10.  Gray scale of arbor forest carbon density retrievaled by ZY-3 images in Zhejiang Province

    表  1  ZY-3卫星参数

    Table  1.   Technical parameters for ZY-3 satellite

    波段序号 Band No.光谱范围 Spectral range/μm波段名称 Band name空间分辨率 Spatial resolution/m
    10.45 ~ 0.52蓝光 Blue light5.8
    20.52 ~ 0.59绿光 Green light5.8
    30.63 ~ 0.69红光 Red light5.8
    40.77 ~ 0.89近红外 Near infrared5.8
    50.50 ~ 0.80全色波段 Panchromatic band2.1
    下载: 导出CSV

    表  2  解译标志数量与图班面积的关系

    Table  2.   Relationship between the number of interpretation signs and the area of subcompartments

    图斑面积/hm2
    Area of subcompartment/ha
    < 22 ~ 34 ~ 78 ~ 1213 ~ 20 > 21
    解译标志个数
    Number of interpretation signs
    123456
    下载: 导出CSV

    表  3  矢量标志提取的光谱信息

    Table  3.   Spectral information extracted by vector signs

    变量类型
    Variable type
    变量
    Variable
    计算公式
    Calculation formula
    单波段
    Single band
    Blue
    Green
    Red
    NIR
    植被指数
    Vegetation
    index
    归一化植被指数
    Normalized difference
    vegetation index (NDVI)
    $\scriptstyle{\rm{NDVI}} = \frac{\scriptstyle{{\rm{NIR}} - {\rm{RED}}}}{\scriptstyle{{\rm{NIR}} + {\rm{RED}}}}$
    比值植被指数
    Ratio vegetation index (RVI)
    RVI = NIR/RED
    差值植被指数
    Difference vegetation index (DVI)
    DVI = NIR− RED
    注:Blue、Green、Red、NIR为ZY-3影像的蓝、绿、红、近红外波段。Notes: Blue, Green, Red and NIR are the blue, green, red and near infrared bands of ZY-3 image.
    下载: 导出CSV

    表  4  基于提纯前后解译标志的ZY-3影像平均分类精度(27景)

    Table  4.   ZY-3 image classification accuracy based on interpretation signs before and after purification (27 scenes)

    分类样本
    Classified sample
    分类总精度(平均)
    Total classification
    accuracy (average)/%
    Kappa(平均)
    Kappa (average)
    乔木林用户精度(平均)
    User accuracy of arbor
    forest (average)/%
    乔木林生产者精度(平均)
    Producer precision of arbor
    forest (average)/%
    提纯前 Before purification 79.70 0.67 85.28 77.31
    提纯后 After purification 80.31 0.69 91.86 80.85
    下载: 导出CSV

    表  5  土地利用类型划分表

    Table  5.   Land use type classification of study area

    一级地类名称
    First-class land name
    一级地类代码
    First-class land code
    二级地类名称
    Secondary land name
    二级地类代码
    Secondary land code
    林地 Forestland 1 乔木林地 Arbor forestand 11
    竹林地 Bamboo forestland 12
    灌木林地 Shrubland 13
    其他林地 Other forestland 14
    农地 Framland 2 农地 Framland
    草地 Grassland 3 草地 Grassland
    湿地 Wetland 4 湿地 Wetland
    聚居地 Settlement 5 聚居地 Settlement
    其他土地 Other land 6 其他土地 Other land
    下载: 导出CSV

    表  6  基于两种分类方法的ZY-3影像平均分类精度(27景)

    Table  6.   ZY-3 image classification accuracy based on MLC and kNN methods (27 scenes)

    分类方法
    Classificaton method
    分类总精度(平均)
    Total classification
    accuracy (average)/%
    Kappa(平均)
    Kappa (average)
    乔木林用户精度(平均)
    User accuracy of arbor
    forest (average)/%
    乔木林生产者精度(平均)
    Producer precision of
    arbor forest (average)/%
    最大似然法
    Maximum likelihood method
    78.56 0.62 89.68 77.79
    kNN法 kNN method 80.31 0.69 91.86 80.85
    下载: 导出CSV

    表  7  两种估算方法的平均估算精度(27景ZY-3影像)

    Table  7.   Average estimation accuracy of two estimation methods (27 ZY-3 images)

    估算方法
    Estimation method
    RMSE(平均)/(t·hm− 2
    Average RMSE/ (t·ha− 1)
    RRMSE(平均)
    Average RRMSE/%
    稳健估计
    Robust estimation
    17.63 25.11
    kNN法
    kNN method
    15.64 23.53
    下载: 导出CSV
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出版历程
  • 收稿日期:  2018-10-25
  • 修回日期:  2019-01-31
  • 网络出版日期:  2019-11-13
  • 刊出日期:  2020-01-14

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