Cloud and Snow Discrimination for CCD Images of HJ-1A/B Constellation Based on Spectral Signature and Spatio-Temporal Context

CORC > 成都山地灾害与环境研究所 > 中国科学院水利部成都山地灾害与环境研究所 > 数字山地与遥感应用中心

	Cloud and Snow Discrimination for CCD Images of HJ-1A/B Constellation Based on Spectral Signature and Spatio-Temporal Context
	Bian, Jinhu1,2 ; Li, Ainong1 ; Liu, Qiannan1,2 ; Huang, Chengquan 3
刊名	REMOTE SENSING
	2016
卷号	8 期号:1 页码:doi:10.3390/rs8010031
关键词	cloud snow HJ-1A B regional covariance matrix spectral spatio-temporal texture context
ISSN号	2072-4292
通讯作者	Li, Ainong
英文摘要	It is highly desirable to accurately detect the clouds in satellite images before any kind of applications. However, clouds and snow discrimination in remote sensing images is a challenging task because of their similar spectral signature. The shortwave infrared (SWIR, e.g., Landsat TM 1.55-1.75 mu m band) band is widely used for the separation of cloud and snow. However, for some sensors such as the CBERS-2 (China-Brazil Earth Resources Satellite), CBERS-4 and HJ-1A/B (HuanJing (HJ), which means environment in Chinese) that are designed without SWIR band, such methods are no longer practical. In this paper, a new practical method was proposed to discriminate clouds from snow through combining the spectral reflectance with the spatio-temporal contextual information. Taking the Mt. Gongga region, where there is frequent clouds and snow cover, in China as a case area, the detailed methodology was introduced on how to use the 181 scenes of HJ-1A/B CCD images in the year 2011 to discriminate clouds and snow in these images. Visual inspection revealed that clouds and snow pixels can be accurately separated by the proposed method. The pixel-level quantitative accuracy validation was conducted by comparing the detection results with the reference cloud masks generated by a random-tile validation scheme. The pixel-level validation results showed that the coefficient of determination (R-2) between the reference cloud masks and the detection results was 0.95, and the average overall accuracy, precision and recall for clouds were 91.32%, 85.33% and 81.82%, respectively. The experimental results confirmed that the proposed method was effective at providing reasonable cloud mask for the SWIR-lacking HJ-1A/B CCD images. Since HJ-1A/B have been in orbit for over seven years and these satellites still run well, the proposed method is helpful for the cloud mask generation of the historical archive HJ-1A/B images and even similar sensors.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Remote Sensing
研究领域[WOS]	Remote Sensing
关键词[WOS]	SPATIAL-RESOLUTION ; TIME-SERIES ; LANDSAT IMAGERY ; MULTISPECTRAL IMAGES ; SATELLITE IMAGERY ; NORTH-AMERICA ; CLASSIFICATION ; SHADOW ; ALGORITHM ; MODIS
收录类别	SCI
语种	英语
WOS记录号	WOS:000369494500008
公开日期	2016-04-26
内容类型	期刊论文
源URL	[http://ir.imde.ac.cn/handle/131551/15107]
专题	成都山地灾害与环境研究所_数字山地与遥感应用中心
作者单位	1.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Univ Maryland, Dept Geog, College Pk, MD 20742 USA
推荐引用方式 GB/T 7714	Bian, Jinhu,Li, Ainong,Liu, Qiannan,et al. Cloud and Snow Discrimination for CCD Images of HJ-1A/B Constellation Based on Spectral Signature and Spatio-Temporal Context[J]. REMOTE SENSING,2016,8(1):doi:10.3390/rs8010031.
APA	Bian, Jinhu,Li, Ainong,Liu, Qiannan,&Huang, Chengquan.(2016).Cloud and Snow Discrimination for CCD Images of HJ-1A/B Constellation Based on Spectral Signature and Spatio-Temporal Context.REMOTE SENSING,8(1),doi:10.3390/rs8010031.
MLA	Bian, Jinhu,et al."Cloud and Snow Discrimination for CCD Images of HJ-1A/B Constellation Based on Spectral Signature and Spatio-Temporal Context".REMOTE SENSING 8.1(2016):doi:10.3390/rs8010031.