[1]刘恺,周小成.采用决策树方法的高分一号PMS影像山区森林覆盖提取[J].华侨大学学报(自然科学版),2019,40(3):376-383.[doi:10.11830/ISSN.1000-5013.201809022]
　LIU Kai,ZHOU Xiaocheng.Forest Cover Extraction From Gaofen-1 PMS Image in Mountain Area Using Decision Tree[J].Journal of Huaqiao University(Natural Science),2019,40(3):376-383.[doi:10.11830/ISSN.1000-5013.201809022]
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采用决策树方法的高分一号PMS影像山区森林覆盖提取()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第40卷
期数:
2019年第3期
页码:
376-383
栏目:
出版日期:
2019-05-20

文章信息/Info

Title:
Forest Cover Extraction From Gaofen-1 PMS Image in Mountain Area Using Decision Tree
文章编号:
1000-5013(2019)03-0376-08
作者:
刘恺1; 2;  周小成1; 2
1. 福州大学 卫星空间信息技术综合应用国家地方联合工程研究中心, 福建 福州 350108;2. 福州大学 空间数据挖掘与信息共享教育部重点实验室, 福建 福州 350108
Author(s):
LIU Kai1; 2;  ZHOU Xiaocheng1; 2
1. National and Local Joint Engineering Research Center of Satellite Geospatial Information Technology, Fuzhou University, Fuzhou 350108, China; 2. Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University,
关键词:
山区;  森林覆盖;  决策树模型;  面向对象;  高分一号
Keywords:
mountain area;  forest cover;  decision tree model;  object oriented;  gaofen-1 satellite
分类号:
TP79
DOI:
10.11830/ISSN.1000-5013.201809022
文献标志码:
A
摘要:
以福建省龙岩市新罗区为例,选取单期国产高分一号(GF-1)PMS影像,采用面向对象决策树模型进行森林覆盖提取.针对山区地形因素引起的阴坡森林区域光谱值异常现象,灵活运用坡度因子、红绿比值植被指数、比值植被指数、归一化水体指数特征进行森林覆盖提取,并将该方法与其他分类器算法进行对比.结果表明:决策树模型的森林制图精度为96.1%,Kappa系数为0.84;该模型可提取高精度的山区森林覆盖信息,且具有可靠性.
Abstract:
Taking Xinluo District, Longyan City, Fujian Province as an example, a single phase domestic gaofen-1 satellite(GF-1)PMS image was selected, and an object-oriented decision tree model was used for forest cover extraction. Aiming at the anomalous optical spectral value of shady forest area caused by mountainous terrain factors, the slope coverage, red-green ratio vegetation index, ratio vegetation index and normalized water body index are used to extract forest cover, and the used method is combined with other classifier algorithms comparing. The results show that the forest mapping accuracy of the decision tree model is 96.1%, and the Kappa coefficient is 0.84. This model can extract high-precision mountain forest coverage information with reliability.

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备注/Memo

备注/Memo:
收稿日期: 2018-09-11
通信作者: 周小成(1977-),男,副研究员,博士,主要从事高分辨率遥感影像信息提取的研究.E-mail:zhouxc@fzu.edu.cn.
基金项目: 中央引导地方科技发展专项(2017L3012); 福建省自然科学基金资助项目(2015H6008)
更新日期/Last Update: 2019-05-20