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当前位置: 首页 > 文章 > 天宫一号高光谱数据的积雪面积比例制图及雪粒径反演 草业科学 2014,31 (8) 1407-1415
Position: Home > Articles > The retrieval of snow grain size and subpixel of snow cover using the domestic hyperspectral data Pratacultural Science 2014,31 (8) 1407-1415

天宫一号高光谱数据的积雪面积比例制图及雪粒径反演

作  者：
郝晓华;王建;马明国;张九星;李绪志
单  位：
中国科学院空间应用工程与技术中心;中国科学院寒区旱区环境与工程研究所
关键词：
高光谱数据;积雪面积比例;雪粒径;稀疏回归;ART
摘  要：
天宫一号高光谱成像仪获取了高空间分辨率和高光谱分辨率的数据。本研究以黑河上游祁连山地区作为试验区,利用其获取的高光谱短波红外波段的数据(SWI)提取了积雪面积比例图和积雪粒径图,以检验其在民用方面的适用性。本研究开发了一个结合VCA(Vertex Component Analysis)组分自动提取技术和稀疏回归解混方法的积雪面积比例制图算法并提取积雪面积比例图,利用同平台携带的更高空间分辨率的图像提取真值对反演结果进行验证。结果显示,两个验证区的均方根误差(RMSE)分别为0.24和0.27,相关系数分别为0.72和0.84,精度较高。利用考虑积雪粒子形状的ART辐射传输理论,获取模型中最佳积雪形状因子和反演波段,并利用SWI数据制作雪粒径图。研究结果表明,天宫一号高光谱数据在积雪遥感方面具有很好应用前景,可以为水文和气候模型提供需要的积雪因子。
译  名：
The retrieval of snow grain size and subpixel of snow cover using the domestic hyperspectral data
作  者：
HAO Xiao-hua;WANG Jian;MA Ming-guo;ZHANG Jiu-xing;LI Xu-zhi;Cold and Arid Regions Environmental and Engineering Research Institute;Technology and Engineering Center for Space Utilization,Chinese Academy of Sciences;
关键词：
hyperspectral data;;snow cove fraction;;snow grain size;;sparse regression;;ART
摘  要：
The remoter sensor from TG-1 platform can provide the hyperspectral and high-resolution images. In the present study,the snow cover fraction and snow size were retrieved from domestic hyperspectral short-wave infrared( SWI) data at Heihe upstream on Qilian Mountains to test its application in the civilian area. A new algorithm that combined Vertex Component Analysis( VCA) component automatic extraction techniques with sparse regression pixels unmixed techniques were developed and to produce snow cover fraction map. The results were verified using the higher spatial resolution images that also been achieved by TG-1 platform. Initial analysis indicated the root mean square error( RMSE) and the correlation coefficient of both validate area was 0. 24 and 0. 27,0. 72 and 0. 84 compared with reference images,respectively. In addition,the ART radiative transfer theory referred to snow particle shape have been approved by the optimizing the shaper factor and retrieval band. The improved algorithm then provided the snow grain size map by domestic hyperspectral data. The maps were validated indirectly by hyperion data which covered the similar field area. The results showed that the domestic hyperspectral data were appropriate to produce SFC and snow grain size map and were feasible to hydrological and climate models.

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