期刊
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
卷 10, 期 4, 页码 1467-1482出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSTARS.2016.2621043
关键词
Image classification; peatlands; polarimetric radar; synthetic aperture radar (SAR)
类别
资金
- Canadian Space Agency and in part by the Natural Sciences and Engineering Council of Canada
The objective of this paper is to assess the accuracy of C-band synthetic aperture radar (SAR) datasets in mapping peat-land types over a region of Canada's subarctic boreal zone. This paper assessed contributions of quad-polarization linear backscatter intensities (sigma degrees HH, sigma degrees HV, sigma degrees VV), image textures, and two polarimetric scattering decompositions: 1) Cloude-Pottier, and 2) Freeman-Durden. Four quad-polarimetric RADADSAT-2 images were studied at incidence angles of 19.4 degrees, 23.1 degrees, 45.8 degrees, and 48.1 degrees. The influence of combining dual-angular information acquired within a short temporal span was also assessed. These C-band SAR data were used to classify peatlands according to isolated flat bogs (bogs), channel fens (fens), raised peat plateaus (plateaus), and forested uplands (uplands) using a supervised support vector machine (SVM) classifier. Numerous classifications were examined to compare the unique contributions of these variables to classification accuracy. Results suggest linear backscatter variables in isolation produce comparable classification results with those of the Freeman-Durden and Cloude-Pottier decompositions. Combining polarimetric decomposition and texture data into classifications with linear backscatter data resulted in only minor (similar to 1-3%) improvement. Combining classifications from small and large incidence angles (dual-angular) significantly improved classification results over those of a single image. Classification accuracy was the highest for isolated bogs and open water surfaces, whereas fens, uplands, and plateaus had lower accuracies. The highest accuracy classification (84% and kappa coefficient of 0.80) used a dual-angular approach, with additional decomposition and texture information. However, it is noted that texture information rarely improved classification results across all tests. This approach identified isolated flat bogs, channel fens, and raised peat plateaus with >76% producer's accuracies.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据