首页> 外文期刊>Journal of Korean Forestry Society >Forest Thematic Maps and Forest Statistics Using the k-Nearest Neighbor Technique for Pyeongchang-Gun, Gangwon-Do
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Forest Thematic Maps and Forest Statistics Using the k-Nearest Neighbor Technique for Pyeongchang-Gun, Gangwon-Do

机译:利用k-最近邻技术的江原道平昌郡森林专题图和森林统计

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摘要

This study was conducted to produce forest thematic maps and estimate forest statistics for Pyeongchang Gun using the kNN technique, which has been applied to produce thematic maps of variables of interest including unobserved plots by combining fieldplot data, remotely sensed data and other digital map data in forest inventories. The estimation errors for three horizontal reference areas (HRAs), whose radii are 20, 40 and 60 km respectively, were compared. Although the precision for the 40 km radius was lower compared to that for the 60 km radius, the 40 km radius was found to be an efficient HRA because their difference in precision was modest. At a value of k=5 nearest neighbors for the selected HRA, the overall accuracy was high. As a result, using the k=5 neighbors within the HRA of 40 km radius, thematic maps of number of trees, basal area, and growing stock per hectare were generated. As compared to the forest statistics based on field sample plots, the estimated means of each parameter from the produced maps were underestimated.
机译:这项研究的目的是利用kNN技术制作平昌郡的森林专题图并估算森林统计数据,该技术已被用于通过结合现场图数据,遥感数据和其他数字地图数据来制作感兴趣的变量专题图,包括未观察到的样地。森林清单。比较了半径分别为20、40和60 km的三个水平参考区域(HRA)的估计误差。尽管40 km半径的精度比60 km半径的精度低,但是40 km半径被认为是一种有效的HRA,因为它们的精度差异不大。对于所选HRA,在k = 5最近邻的值下,总体准确性很高。结果,使用半径为40 km的HRA中的k = 5个邻居,生成了树木数量,基础面积和每公顷生长种群的专题图。与基于实地样地的森林统计数据相比,从生产的地图中估算出的每个参数的均值被低估了。

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