Forest and Grassland Resources Research >
Extracting Individual Tree Position of Chinese Fir Based on an Improved Local Maximum Method
Received date: 2022-04-19
Revised date: 2022-08-11
Online published: 2022-12-23
Chinese fir is one of the important timber species in China.The extraction of individual tree position and density plays an important role in regulating its stand spatial structure and function,and improving stand quality.Based on the unmanned aerial vehicle(UAV)remote sensing image,taking the Chinese fir pure forest in Longquan City of Lishui as the research object,the improved local maximum method was used to extract the crown position and number of Chinese fir trees,which was compared and analyzed with the measured number of trees.The results show that the sampling interval parameter of the improved local maximum method had an important influence on the extraction accuracy of individual tree number.Under the appropriate sampling interval parameters,the overall accuracy of individual tree position detection for sample plots with dense and sparse tree density were 82.10% and 80.17%,commission errors were 24.12% and 18.18%,and omission errors were 17.90% and 19.83%,respectively.The detected tree density and measured tree density for sample plots with dense and sparse tree density were very similar,and the accuracy was 93.77% and 98.35%,respectively.The tree density had a negative correlation with the overall accuracy and commission error,and a positive correlation with the omission error.The improved local maximum method can accurately extract the number of individual trees of Chinese fir forest with different tree density,which provides a feasible method for intelligent,fast and accurate extraction of individual crown position and tree density of Chinese fir.
Key words: local maximum method; UAV; individual tree; tree density
Suchun LI , Luhua LIN , Lei XIA , Lulu HU , Xiaojun XU . Extracting Individual Tree Position of Chinese Fir Based on an Improved Local Maximum Method[J]. Forest and Grassland Resources Research, 2022 , 0(5) : 60 -68 . DOI: 10.13466/j.cnki.lyzygl.2022.05.008
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