Site quality evaluation of uneven-aged mixed coniferous and broadleaved stands in Guangdong Province of southern China based on BP neural network

Shen Jianbo; Wang Yingkuan; Lei Xiangdong; Lei Yuancai; Wang Qiulai; Ye Jinsheng

doi:10.13332/j.1000-1522.20190028

Journal of Beijing Forestry University > 2019 > 41(5): 38-47. > DOI: 10.13332/j.1000-1522.20190028

Shen Jianbo, Wang Yingkuan, Lei Xiangdong, Lei Yuancai, Wang Qiulai, Ye Jinsheng. Site quality evaluation of uneven-aged mixed coniferous and broadleaved stands in Guangdong Province of southern China based on BP neural network[J]. Journal of Beijing Forestry University, 2019, 41(5): 38-47. DOI: 10.13332/j.1000-1522.20190028

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Site quality evaluation of uneven-aged mixed coniferous and broadleaved stands in Guangdong Province of southern China based on BP neural network

1.
Chinese Academy of Agricultural Engineering, Beijing 100125, China
2.
Research Institute of Forest Resources Information Techniques, Beijing 100091, China
3.
Forestry Surveying and Designing Institute of Guangdong Province, Guangzhou 510520, Guangdong, China
4.
Graduate School, Nanjing Forestry University, Nanjing 210037, Jiangsu, China

More Information

Received Date: January 14, 2019
Revised Date: March 03, 2019
Available Online: May 06, 2019
Published Date: April 30, 2019

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Abstract

Abstract

ObjectiveThe calculation to the site index of uneven-aged coniferous and broadleaved mixed stands has always been a difficult point in the evaluation of site quality. At home and abroad, there are few studies on the site index model of uneven-aged coniferous and broadleaved mixed stands. In order to establish a more accurate site index of coniferous and broadleaved mixed stands, the model introduces the neural network model into the site quality evaluation of uneven-aged coniferous and broadleaved mixed stands.
MethodIn this study, uneven-aged coniferous and broad-leaved mixed stands in Guangdong province were used as study object, the stand dominant tree height model and site index model to uneven-aged coniferous and broadleaved mixed forests were estabished based on neural network. Besides the age factor, altitude, slope, slope direction, slope position, soil thickness and humus layer thickness were added. The influence of the basal area ratio of coniferous and broad-leaved species on the site index were also considered, then the site index model of coniferous and broadleaved mixed stands was estabished.
ResultThe results showed that the maximum value of the site index to the uneven-aged coniferous and broadleaved mixed stands was 21.4 m, the minimum value was 6.1 m, the average value was 13.7 m, the median was 13.6 m, and the standard deviation was 3.2 m. The difference between the maximum and minimum values of the site index was 15.3 m.
ConclusionFrom the results, it can be reflected that the landforms in Guangdong Province are complex and fragmented, and there are more mountains and less flat land, and the site conditions are different one another. In addition, due to the complexity and diversity of tree species and tree species ratio in Guangdong Province, then it lead to quite different in the reference age. Therefore, the site index is not the same one another. In the computation of the site index of coniferous and broadleaved mixed stands, the site factors such as altitude, slope, slope aspect, slope position, soil thickness and humus layer thickness were added to improve the prediction accuracy of the site index of coniferous and broadleaved mixed stands. The results provide a more accurate method for the calculation of the site index of uneven-aged coniferous and broadleaved mixed stands.
- uneven-aged mixed coniferous and broadleaved stands,
- neural network,
- site index,
- site factor

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References (22)

References

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Site quality evaluation of uneven-aged mixed coniferous and broadleaved stands in Guangdong Province of southern China based on BP neural network