Extracting individual tree crown by combining spectral and texture features from aerial images

ZHANG Ning; FENG Yue-wen; ZHANG Xiao-li; FAN Jiang-chuan

doi:10.13332/j.1000-1522.20140309

Journal of Beijing Forestry University > 2015 > 37(3): 13-19. > DOI: 10.13332/j.1000-1522.20140309

ZHANG Ning, FENG Yue-wen, ZHANG Xiao-li, FAN Jiang-chuan. Extracting individual tree crown by combining spectral and texture features from aerial images[J]. Journal of Beijing Forestry University, 2015, 37(3): 13-19. DOI: 10.13332/j.1000-1522.20140309

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Extracting individual tree crown by combining spectral and texture features from aerial images

1.
1 College of Forestry,Beijing Forestry University, Beijing,100083, P.R. China
2.
2 Sinotech Minerals Exploration Co. Ltd., Beijing,100012, P.R. China
3.
3 National Engineering Research Center for Information Technology in Agriculture, Beijing,100097, P.R. China.

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Received Date: September 14, 2014
Revised Date: November 07, 2014
Published Date: March 30, 2015

Graphical Abstract

Abstract

Abstract

Aero photogrammetry has been used in forestry successfully for improving the efficiency in forest resources survey with the development and progress of it. However, the results in most studies in single tree crown extraction were biased because the merely image spectral information was considered. Individual tree crown can be extracted by jointly combining the texture and spectral features of the aerial images, then determining the optimal segmentation scale while using object-oriented image segmentation method and multiple comparing the experimental results, and defining the information scope of spectral and texture features with normal distribution method. Using aerial images of Jiufeng National Forest Park of Beijing in 2012 as the data source, and using ENVI5.0 as the data processing platform to segment the images, then extract 32 trees’ crown in the test area, and analyze accuracy combined with the traditional field measured data and stereo image measured data. The results showed that the accuracy could achieve 90.05% by the proposed method, it is close to the accuracy by traditional stereo image measure, and data acquisition is quick, so it meets the basic needs of the forestry survey.
- aerial image,
- tree crown extraction,
- texture feature,
- spectral feature

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References (32)

References

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