应用生态学报2017，Vol.28Issue(11)：3711-3719,9.DOI:10.13287/j.1001-9332.201711.012
基于多源遥感数据的面向对象林分类型识别
Object-oriented stand type classification based on the combination of multi-source remote sen-sing data
摘要
Abstract
The recognition of forest type is one of the key problems in forest resource monitoring.The Radarsat-2 data and QuickBird remote sensing image were used for object-based classification to study the object-based forest type classification and recognition based on the combination of multisource remote sensing data.In the process of object-based classification,three segmentation schemes (segmentation with QuickBird remote sensing image only,segmentation with Radarsat-2 data only,segmentation with combination of QuickBird and Radarsat-2) were adopted.For the three segmentation schemes,ten segmentation scale parameters were adopted (25-250,step 25),and modified Euclidean distance 3 index was further used to evaluate the segmented results to determine the optimal segmentation scheme and segmentation scale.Based on the optimal segmented result,three forest types of Chinese fir,Masson pine and broad-leaved forest were classified and recognized using Support Vector Machine (SVM) classifier with Radial Basis Foundation (RBF) kernel according to different feature combinations of topography,height,spectrum and common features.The results showed that the combination of Radarsat-2 data and QuickBird remote sensing image had its advantages of object-based forest type classification over using Radarsat-2 data or QuickBird remote sensing image only.The optimal scale parameter for QuickBird&Radarsat-2 segmentation was 100,and at the optimal scale,the accuracy of object-based forest type classification was the highest (OA =86％,Kappa =0.86),when using all features which were extracted from two kinds of data resources.This study could not only provide a reference for forest type recognition using multi-source remote sensing data,but also had a practical significance for forest resource investigation and monitoring.关键词
面向对象/Radarsat/QuickBird/合成孔径雷达/支持向量机Key words
object-based/Radarsat/QuickBird/synthetic aperture radar/support vector machine引用本文复制引用
毛学刚,魏晶昱..基于多源遥感数据的面向对象林分类型识别[J].应用生态学报,2017,28(11):3711-3719,9.基金项目
本文由国家自然科学基金项目(31300533)资助 This work was supported by the National Natural Science Foundation of China (31300533). （31300533）
