[1]刘俊,周靖靖*,菅永峰,等. Worldview-2不同波段纹理特征对森林蓄积量估算精度影响[J].西北林学院学报,2021,36(3):175-181.[doi:10.3969/j.issn.1001-7461.2021.03.26]
　LIU Jun,ZHOU Jing-jing*,JIAN Yong-feng,et al. Effects of Texture Parameters of Different Bands of Worldview-2 Images on the Estimation of Forest Volume[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2021,36(3):175-181.[doi:10.3969/j.issn.1001-7461.2021.03.26]
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 Worldview-2不同波段纹理特征对森林蓄积量估算精度影响()
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《西北林学院学报》[ISSN:1001-7461/CN:61-1202/S]

卷:
第36卷
期数:
2021年第3期
页码:
175-181
栏目:
出版日期:
2021-05-31

文章信息/Info

Title:
 Effects of Texture Parameters of Different Bands of Worldview-2 Images on the Estimation of Forest Volume
文章编号:
1001-7461(2021)03-0175-07
作者:
 刘俊1; 周靖靖2; 3*; 菅永峰2; 韩泽民2; 张迎归2; 佃袁勇2; 3
 （1.国家林业和草原局 华东调查规划设计院，浙江 杭州 310019；2.华中农业大学 园艺林学学院，湖北 武汉 430070；3.湖北省林业信息工程技术研究中心，湖北 武汉 430070）
Author(s):
 LIU Jun1; ZHOU Jing-jing2; 3*; JIAN Yong-feng2; HAN Ze-min2; ZHANG Ying-gui2; DIAN Yuan-yong2; 3
 （1.East China Investigation,Planning and Design Institute of National Forestry and Grassland Administration,Hangzhou 310019,Zhejiang,China; 2.College of Horticulture&Forestry Sciences,Huazhong Agricultural University,Wuhan 430070,Hubei,China; 3.Hubei Engineering Technology Research Center for Forestry Information,Wuhan 430070,Hubei,China）
关键词:
 ; 波段; 纹理特征; 蓄积量估算
Keywords:
 ; band;  texture parameter;  forest volume estimation
分类号:
S771.8
DOI:
10.3969/j.issn.1001-7461.2021.03.26
文献标志码:
A
摘要:
 为检测高分辨率遥感影像不同波段纹理特征对于森林蓄积量估算精度的影响，以湖北省荆门市京山县太子山林场马尾松纯林为对象，基于灰度共生矩阵的方法分别提取高分辨率遥感影像Worldview-2 红光、绿光、蓝光、近红外波段和全色波段的纹理特征，利用随机森林算法，分别建立野外样地蓄积量与纹理参数的模型。结果表明，全色波段对马尾松森林的精度最高（R2=0.86，RMSE=47.37 m3·hm-2），其次是绿色波段（R2=0.85，RMSE=50.82 m3·hm-2）和近红外波段（R2=0.85，RMSE=46.85 m3·hm-2），蓝色波段（R2=0.68，RMSE=60.72 m3·hm-2）和红色波段（R2=0.69，RMSE=56.27 m3·hm-2）的精度最低；窗口大小对模型精度影响较小，全色波段的R2取值在0.82~0.86，RMSE取值在47.66~51.99 m3·hm-2，多光谱波段的R2取值在0.88~0.89；蓝色和红色波段的非相似度（DIS）的估算模型精度相对较高，绿色波段的对比度（CON）（R2=0.87，RMSE=46.21 m3·hm-2）估算精度最高，红色波段的非相似度（R2=0.68，RMSE=58.30 m3·hm-2）估算精度较高，近红外波段的角二阶矩阵（ASM）（R2=0.68，RMSE=60.30 m3·hm-2）精度最高，全色波段的对比度、相关性、熵、变化量模型精度较高，R2为0.85。利用高分辨率遥感影像纹理特征估算森林参数时需综合考虑不同波段的纹理特征对模型的贡献。
Abstract:
 To test the influences of texture parameters of different bands of high resolution images on the estimation accuracy of forest volume,pure Pinus massoniana plantations occurring in Taizishan Forest Farm located in Jingshan County,Jingmen City of Hubei Province were used as the research objects.The method of gray-level co-occurrence matrix was adopted to extract texture parameters of red,green,blue,near-infrared and panchromatic bands of Worldview-2 images.Random forest algorithm was applied to establish the models of forest volume based on field investigation and texture parameters.The results showed that panchromatic band had the highest accuracy for the volume estimation of P.massoniana plantations (R2=0.86,RMSE=47.37 m3·hm-2),followed by the green band (R2=0.85,RMSE=50.82 m3·hm-2) and near-infrared band (R2=0.85,RMSE=46.85 m3·hm-2),while the blue band (R2=0.68,RMSE=60.72 m3·hm-2) and red band (R2=0.69,RMSE=56.27 m3·hm-2) had the lowest accuracy.Window size presented little effect on the accuracy of the model.R2 value of the panchromatic band was between 0.82 and 0.86 and RMSE value was between 47.66 and 51.99 m3·hm-2.R2 value of the multispectral band was between 0.88 and 0.89.The accuracy of the dissimilarity (DIS) of the blue and red bands was relatively high,and the contrast (CON) of the green band (R2=0.87,RMSE=46.21 m3·hm-2) had the highest estimation accuracy,and the DIS of the red band (R2=0.68,RMSE=58.30 m3·hm-2) had higher estimation accuracy.Angular Second Moment (ASM) in the near infrared band (R2=0.68,RMSE=60.30 m3·hm-2) had the highest accuracy.The accuracy of contrast,correlation,and entropy of the panchromatic band had higher accuracy,R2 was 0.85.The results indicated that when texture features of high-resolution remote sensing image were used to estimate forest parameters,it was necessary to consider the contribution of texture features of different bands to the model building comprehensively.

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备注/Memo

备注/Memo:
 收稿日期：2020-08-19修回日期：2020-12-26
基金项目：国家重点研发计划项目：南方低效人工林改造与特色生态产业技术（2017YFC0505504）；中央高校科研业务费专项资金资助（2662020YLPY020）。
作者简介：刘俊，博士，工程师。研究方向：森林遥感、林业规划设计。E-mail:james_china@qq.com
*通信作者：周靖靖，博士，讲师。研究方向：森林培育。E-mail:hupodingxiangyu@mail.hzau.edu.cn
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