Comparison of object-based and pixel-based Random Forest algorithm for wetland vegetation mapping using high spatial resolution GF-1 and SAR data

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• 作者：Bolin Fu^a ; ^b ; ^c ; Yeqiao Wang^c ; Anthony Campbell^c ; Ying Li^a ; ^{liying_neigae@126.com} ; Bai Zhang^a ; Shubai Yin^d ; Zefeng Xing^a ; ^b ; Xiaomin Jin^a ; ^b
• 关键词：Wetland vegetation mapping ; Image fusion ; Random Forest classifier ; GF-1 ; SAR ; Northeast China
• 刊名：Ecological Indicators
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：73
• 期：Complete
• 页码：105-117
• 全文大小：7243 K
• 卷排序：73

文摘

Random Forest (RF) algorithms for mapping wetland vegetation. Synergistic use of optical and SAR data achieved 89.64% overall accuracy. Object-based classifications outperform pixel-based classifications. PALSAR and Radarsat-2 both provided important variables for wetland mapping. Improved understanding of wetland composition in a major wetland national natural reserve in China.