干旱区生态环境知识资源中心(Arid): 主被动遥感数据协同估算干旱区草原植被生物量

Arid

	主被动遥感数据协同估算干旱区草原植被生物量
其他题名	Estimation of Vegetation Biomass in Arid Region with Active and Passive Remote Sensing Data
	行敏锋; 何彬彬
来源期刊	遥感技术与应用
ISSN	1004-0323
出版年	2015
卷号	30 期号:6 页码:1122-1128
中文摘要	结合主动微波遥感和被动光学遥感反映地表植被的各自优势,发展了一种主被动遥感协同估算干旱区草原植被生物量的模型。该模型将植被覆盖度作为水云模型的附加参数,将总体散射分为植被覆盖区散射和裸土区散射两部分,将水云模型应用到了植被覆盖稀疏区域。利用改进的水云模型和双极化ASAR数据,通过建立方程组估算植被生物量。将该方法用于乌图美仁草原植被生物量的估算,验证了该方法的有效性。结果表明:该主被动遥感协同估算模型能够成功地估算干旱区草原植被生物量,并且取得了较好的估算精度(R~2=0.8562,RMSE=0.1813kg/m~2)。最后,分析了该方法估算植被生物量的误差来源。
英文摘要	Integrating the respective advantages of optical and microwave data for the vegetation,an optical and microwave synergistic method for the Above Ground Biomass(AGB)in the prairie of arid regions was developed in this paper.Vegetation coverage was combined in water cloud model as additional information. The total backscattering was divided into the amount attributed to areas covered with vegetation and attributed to areas of bare soil.Thus,the water cloud model can be applied in the sparse vegetation cover area. Using the modified water cloud model and dual-polarization ASAR data,the vegetation biomass was estimated by the established equations.The method was applied to estimate the AGB of Wutumeiren prairie. The results indicated that the method of active and passive remote sensing synergy was of the operational potential in AGB.And the better accuracy of the biomass retrieval was achieved(R~2=0.8562,RMSE= 0.1813kg/m~2).Finally,the error of biomass estimation using this method was analyzed.
中文关键词	生物量 ; 水云模型 ; 协同估算 ; 干旱区草原
英文关键词	Biomass Water Cloud Model Synergistic estimation Prairie of arid regions
语种	中文
国家	中国
收录类别	CSCD
WOS类目	REMOTE SENSING
WOS研究方向	Remote Sensing
CSCD记录号	CSCD:5617952
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/233559
作者单位	电子科技大学资源与环境学院, 成都, 四川 611731, 中国
推荐引用方式 GB/T 7714	行敏锋,何彬彬. 主被动遥感数据协同估算干旱区草原植被生物量[J],2015,30(6):1122-1128.
APA	行敏锋,&何彬彬.(2015).主被动遥感数据协同估算干旱区草原植被生物量.遥感技术与应用,30(6),1122-1128.
MLA	行敏锋,et al."主被动遥感数据协同估算干旱区草原植被生物量".遥感技术与应用 30.6(2015):1122-1128.