Inversion Of Disturbed Forest Parameters Based On Linear Array LiDAR

Forest health is a key factor in giving full play to multi-functional benefits.In-depth study of the growth of disturbed forests is an important part of maintaining forest health.Linear array LiDAR is easy to carry and has a fast scanning speed,which has significant advantages in forestry surveys.However,the application of linear array LiDAR in disturbed forests has not been found.The structural parameters of disturbed forests are mostly based on field surveys or the inversion of remote sensing images.Therefore,this paper takes the harvesting forests in Jiaohe and the burned areas in Genhe as research objects.Based on the point cloud data acquired by VLP-16,the following aspects are carried out and corresponding results are obtained:The research and results carried out in the harvesting forests in Jiaohe are as follows:(1)The curve of point cloud numbers-height and point cloud intensity-height are established to extract the parameters of the vertical structure of the stand.Compared with the control plot,there is no vegetation present above 20m in the light and moderate harvesting plots.The vegetation of the harvesting plot is mainly distributed within the height of 0-15m,and the vegetation of the control plot is mainly distributed within the height of 5-20m.(2)The gap fraction is calculated by calculating the ratio of the number of point clouds in the "sky" to the total number of launched point clouds,and then the canopy density is obtained.Compared with the year of harvesting,the canopy density in all plots increased,and the value of moderate harvesting plots was the most obvious.The difference of the canopy density between the harvesting plot and the control plot is smaller than that of the harvesting year.And the difference between the moderate harvesting plot and the control plot is still larger.The research and results carried out in the burned areas in Genhe are as follows:(1)The position of the single tree is identified based on the single-frame point cloud data,and the average DBH of the forest is calculated by the DBH value of single trees.During the recovery period of about ten years,the new trees have not yet grown,and the average DBH of the stands in the burned plots is greater than that of the unburned plots.During the recovery period of more than ten years,the new trees have grown to the sapling stage,and the average DBH of the burned plot has become smaller.(2)The leaf area index is calculated by the extracted gap fraction of burned area combined with the Lambert-Beer law.The gap fraction of the burned plot is much higher than that of the unburned plot.As the recovery period increases,the difference in gap fraction gradually decreases.The change trend of the difference of leaf area index is consistent with the gap fraction.The inversion accuracy of the relevant parameters based on the algorithm of this paper is high,which can reflect the vegetation growth and stand structure of disturbed forests,and provide scientific basis for vegetation recovery.At the same time,the algorithm does not need to mosaicking point cloud,which reduces the time cost and workload.It provides a new method for the inversion of relevant parameters of disturbed forests and a new direction for the application of linear array LiDAR in forestry.