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利用航空象片信息提取小班调查因子。首先利用航片对每个小班的林分类型、龄组、郁闭度和最大冠幅进行判读;其次根据以往的资料,建立林木株数分布,每公顷株数预测,直径与最大冠幅及胸径与树高、年龄等相关模型;最后由判读因子和上述模型借助于计算机求出林分蓄积量、断面积、各径阶株数,平均直径、平均高、平均年龄等因子。该试验是在我国北方次生林区进行的,多数小班因子可由航片提取,蓄积量估测的精度达到85％以上,可提高工作效率1—2倍。为我国二类森林调查提出了一种新的方法。
Using Airplane Image Information to Extract Small Class Survey Factors. First of all, aerial photos were used to interpret the stand type, age group, canopy density and maximum crown of each small class. Secondly, according to the previous data, the distribution of the number of trees, the number of trees per hectare, the diameter and the maximum crown, Tree height, age and other related models. Finally, factors such as stock volume, area, diameter of each diameter, average diameter, average height, average age and other factors were calculated by the interpretation factor and the above model. The test was carried out in the secondary forest area of northern China. Most of the small-scale factors can be extracted from the aerial photos. The accuracy of the stock volume estimation is over 85%, which can improve work efficiency by 1-2 times. A new method is proposed for the second type of forest survey in our country.