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林业资源管理 ›› 2010, Vol. 0 ›› Issue (1): 118-122.

• 科学技术 • 上一篇    下一篇

专家分类方法在森林资源清查中的应用研究

张晓星   

  1. 山西省太原市林业调查规划院,太原 030012
  • 收稿日期:2009-09-25 修回日期:2010-02-02 发布日期:2020-12-14
  • 作者简介:张晓星(1964-),男,山西太原人,工程师,硕士研究生,主要从事林业调查规划及3S在林业中的应用。Email:tylyj001@163.com
  • 基金资助:
    教育部新世纪人才支持计划(NCET-06-0122)

Application of Expert Classification Method in Forest Resources Investigation

ZHNAG Xiaoxing   

  1. Taiyuan Municipal Institute of Forest Inventory and Planning, Taiyuan 030012, Shanxi Province, China
  • Received:2009-09-25 Revised:2010-02-02 Published:2020-12-14

摘要: 以太原市的6个建城区为研究区,利用一类数据与SPOT5遥感数据,根据《山西省森林资源规划调查外业工作细则》中林地、林分分类标准,采用专家分类的方法,成功地分出了15个乔木树种和16个灌木及其组合。在不改变原小班划分的基础上,对采用目视解译方法在同时相SPOT5遥感数据上完成的森林资源清查数据进行校验,结果表明专家分类方法可以消除个人因素对解译结果的影响,在解译细节上强于目视解译;专家分类方法更科学、实用,在生产更具有推广意义。

关键词: 专家分类, 遥感, 森林资源, SPOT5影像

Abstract: The study takes six urban districts as the research area. According to the forest land and forest stand classification standards in Detailed Regulations on Field Work of Forest Planning and Inventory in Shanxi Province, expert classfication method is adopted with the NFI data and SPOT5 remote sensing data, and 15 tree species and 16 shrubs and their combinations are identified successfully after the repeated tests. Without changing the original subcompartment division, the visual interpretation method is used to test and check the accuracy of the forest resources inventory data. The result shows that expert classification method can eliminate the influence of personal behavior on interpretation, which is better than visual interpretation in terms of details of interpretation. Expert classification method is more scientific and practical and has greater extention significance in aspect of production.

Key words: expert classification, remote sensing, forest resource, images of SPOT 5

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