不同分辨遥感影像下天山云杉林分形特征

doi:10.6048/j.issn.1001-4330.2024.01.023

摘要/Abstract

摘要：

【目的】研究分辨率改变较小的情况下的天山云杉林分形特征的稳定性,为天山云杉林区划调查提供依据。【方法】以天山云杉林为研究对象,选取分辨率为0.1 m(无人机影像)和0.5 m(WorldView-3影像)2种遥感影像,分别计算其分形维数,使用ENVI、PIX4D等软件对WorldView-3影像和无人机影像进行预处理,在MATLAB中分别采用双毯覆盖模型法和分形布朗运动法计算171个不天山云杉林样方的分形维数。【结果】(1)天山云杉林分形维数的取值范围主要集中在2.3~2.6;在WorldView-3影像下,采用双毯覆盖模型法和分形布朗运动法计算得到:天山云杉林分形维数的取值范围主要集中在2.2~2.7。(2)天山云杉林分形维数的值不会随着值数量的增加而发生较大的改变,始终处于稳定的取值区间内。【结论】无人机影像和WorldView-3影像下天山云杉林分形维数分别为2.451 3和2.478 2,2种不同分辨率(0.1和0.5 m)下的天山云杉林分形维数值取值区间基本相同,即天山云杉林在一定的分辨率下有着稳定的分形特征。

关键词: 分辨率; 天山云杉林; 分形维数

Abstract:

【Objective】 To explore the stability of the fractal characteristics of Tianshan Picea schrenkiana var. tianschanica forest in order to provide new ideas for the zoning investigation of Tianshan spruce forest by taking Picea schrenkiana var. tianschanica forest as the research object. 【Methods】 Taking the Tianshan spruce forest as the research object.Firstly,the worldview-3 image and UAV image were preprocessed by ENVI,PIX4D and other software,and then the fractal dimensions of 171 spruce forest quadrats were calculated by double blanket coverage model method and Fractal Brownian motion method in MATLAB; Finally,the calculation results are analyzed and discussed. 【Results】 (1)The value range of fractal dimension of Picea schrenkiana var. tianschanica forest calculated by the two methods was mainly 2.3-2.6; Under WorldView-3 image,the double blanket coverage model method and Fractal Brownian motion method were used to calculate:the value range of fractal dimension of Picea schrenkiana var. tianschanica forest calculated by the two methods was mainly between 2.2 and 2.7.(2) The value of the fractal dimension of Picea schrenkiana var. tianschanica forest under the two resolution images would not change greatly with the increase of the number of values,and was always in a stable value range. 【Conclusion】 Based on the two methods,the fractal dimensions of Picea schrenkiana var. tianschanica forest under UAV image and worldview-3 image are 2.4513 and 2.4782,respectively. At the same time,its value range of under two different resolutions(0.1and 0.5m) is basically the same,that is,Picea schrenkiana var. tianschanica forest has stable fractal characteristics at a certain resolution.

Key words: resolving power; Picea schrenkiana var. tianschanica; fractal dimension

中图分类号:

S717

马琪瑶, 郝康迪, 胡天祺, 陈哲, 王振锡. 不同分辨遥感影像下天山云杉林分形特征[J]. 新疆农业科学, 2024, 61(1): 209-216.

MA Qiyao, HAO Kangdi, HU Tianqi, CHEN Zhe, WANG Zhenxi. Study on fractal characteristics of Picea schrenkiana var. tianschanica forest under different resolution remote sensing images[J]. Xinjiang Agricultural Sciences, 2024, 61(1): 209-216.

图/表 6

表1 天山云杉林分形维数

Tab. 1 Fractal dimension of Picea schrenkiana var. tianschanica forest

统计 Statistics	双毯覆盖模型 Double blonket coverage model	分形布朗运动 Fractional brownian motion
平均值Avg	2.4573	2.4490
最大值Max	2.5370	2.5988
最小值Min	2.2984	2.3373

图1 天山云杉林分形维数

Fig. 1 Fractal dimension of Picea schrenkiana var. tianschanica forest

表2 天山云杉林分形维数

Tab.2 Fractal dimension of Picea schrenkiana var. tianschanica forest

统计 Statistics	双毯覆盖模型 Double blonket coverage model	分形布朗运动 Fractional brownian motion
平均值Avg	2.502 0	2.499 1
最大值Max	2.687 3	2.641 7
最小值Min	2.258 3	2.262 9

图2 天山云杉林分形维数

Fig. 2 Fractal dimension of Picea schrenkiana var. tianschanica forest

图3 双毯覆盖模型法计算2种影像天山云杉林分形维数

Fig. 3 Calculation of fractal dimension of Picea schrenkiana var. tianschanica forest from two kinds of images by double blanket coverage model

图4 分形布朗运动法计算2种影像天山云杉林分形维数

Fig. 4 Calculation of fractal dimension of Picea schrenkiana var. tianschanica forest by fractal Brownian motion method

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