UAV Remote Sensing for Urban Vegetation Mapping Using Random Forest and Texture Analysis

	UAV Remote Sensing for Urban Vegetation Mapping Using Random Forest and Texture Analysis
	Feng, Quanlong 1; Liu, Jiantao 1; Gong, Jianhua 1
刊名	REMOTE SENSING
	2015
卷号	7 期号:1 页码:150-154
关键词	UAV vegetation mapping urban landscape random forest texture analysis
通讯作者	Gong, JH (reprint author), Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing, 20 Datun Rd, Beijing 100101, Peoples R China.
英文摘要	Unmanned aerial vehicle (UAV) remote sensing has great potential for vegetation mapping in complex urban landscapes due to the ultra-high resolution imagery acquired at low altitudes. Because of payload capacity restrictions, off-the-shelf digital cameras are widely used on medium and small sized UAVs. The limitation of low spectral resolution in digital cameras for vegetation mapping can be reduced by incorporating texture features and robust classifiers. Random Forest has been widely used in satellite remote sensing applications, but its usage in UAV image classification has not been well documented. The objectives of this paper were to propose a hybrid method using Random Forest and texture analysis to accurately differentiate land covers of urban vegetated areas, and analyze how classification accuracy changes with texture window size. Six least correlated second-order texture measures were calculated at nine different window sizes and added to original Red-Green-Blue (RGB) images as ancillary data. A Random Forest classifier consisting of 200 decision trees was used for classification in the spectral-textural feature space. Results indicated the following: (1) Random Forest outperformed traditional Maximum Likelihood classifier and showed similar performance to object-based image analysis in urban vegetation classification; (2) the inclusion of texture features improved classification accuracy significantly; (3) classification accuracy followed an inverted U relationship with texture window size. The results demonstrate that UAV provides an efficient and ideal platform for urban vegetation mapping. The hybrid method proposed in this paper shows good performance in differentiating urban vegetation mapping. The drawbacks of off-the-shelf digital cameras can be reduced by adopting Random Forest and texture analysis at the same time.
研究领域[WOS]	Remote Sensing
收录类别	SCI
语种	英语
WOS记录号	WOS:000348401900051
内容类型	期刊论文
源URL	[http://ir.ceode.ac.cn/handle/183411/38334]
专题	遥感与数字地球研究所_SCI/EI期刊论文_期刊论文
作者单位	1.[Feng, Quanlong 2.Liu, Jiantao 3.Gong, Jianhua] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing, Beijing 100101, Peoples R China 4.[Gong, Jianhua] Zhejiang CAS Applicat Ctr Geoinformat, Jiashan 314100, Peoples R China
推荐引用方式 GB/T 7714	Feng, Quanlong,Liu, Jiantao,Gong, Jianhua. UAV Remote Sensing for Urban Vegetation Mapping Using Random Forest and Texture Analysis[J]. REMOTE SENSING,2015,7(1):150-154.
APA	Feng, Quanlong,Liu, Jiantao,&Gong, Jianhua.(2015).UAV Remote Sensing for Urban Vegetation Mapping Using Random Forest and Texture Analysis.REMOTE SENSING,7(1),150-154.
MLA	Feng, Quanlong,et al."UAV Remote Sensing for Urban Vegetation Mapping Using Random Forest and Texture Analysis".REMOTE SENSING 7.1(2015):150-154.