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	A decision tree algorithm for surface soil freeze/thaw classification over China using SSM/I brightness temperature
	Jin, Rui; Li, Xin; Che, Tao
刊名	REMOTE SENSING OF ENVIRONMENT
	2009-12-15
卷号	113期号:12页码:2651-2660
关键词	Surface soil freeze/thaw Frozen ground Classification Decision tree SSM/I
ISSN号	0034-4257
DOI	10.1016/j.rse.2009.08.003
通讯作者	Li, Xin(lixin@lzb.ac.cn)
英文摘要	This paper reports the development of a decision tree algorithm to classify the surface soil freeze/thaw states. The algorithm uses SSM/I brightness temperatures recorded in the early morning. Three critical indices are used as classification criteria-the scattering index (SI), the 37 GHz vertical polarization brightness temperature (T(37v)), and the 19 GHz polarization difference (PD(19)). The thresholds of these criteria were obtained from samples of frozen soil, thawed soil, desert, and snow. The algorithm is capable of distinguishing between frozen soil, thawed soil, desert and precipitation. In-situ 4-cm deep soil temperatures on the Qinghai-Tibetan Plateau were used to validate the classification results, and the average classification accuracy was found to be 87% Regarding the misclassified pixels, about 40% and 73% of them appeared when the surface soil temperature ranged from -0.5 degrees C to 0.5 degrees C and from -2.0 degrees C to 2.0 degrees C, respectively, which means that most misclassifications occurred near the soil freezing point In addition, misclassifications mainly occurred from April to May and September to October, the transition periods between warm and cold seasons. A grid-to-grid Kappa analysis was also conducted to evaluate the consistency between the map of the actual number of frozen days obtained using the decision tree classification algorithm and the reference map of geocryological regionalization and classification in China. The overall classification accuracy was 91.7%, and the Kappa index was 80.5%. The boundary between the frozen and thawed soil was consistent with the southern limit of seasonally frozen ground from the reference map. The statistics show that the maximum area of frozen soil is about 6.82 x 10(6) km(2) in late January, accounting for 69% of total Chinese land area. (C) 2009 Elsevier Inc. All rights reserved.
收录类别	SCI
WOS关键词	NASA SCATTEROMETER NSCAT ; SENSOR MICROWAVE IMAGER ; SNOW COVER ; CYCLES ; FROZEN
WOS研究方向	Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
出版者	ELSEVIER SCIENCE INC
WOS记录号	WOS:000271771300010
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2556178
专题	寒区旱区环境与工程研究所
通讯作者	Li, Xin
作者单位	Chinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, Lanzhou 730000, Peoples R China
推荐引用方式 GB/T 7714	Jin, Rui,Li, Xin,Che, Tao. A decision tree algorithm for surface soil freeze/thaw classification over China using SSM/I brightness temperature[J]. REMOTE SENSING OF ENVIRONMENT,2009,113(12):2651-2660.
APA	Jin, Rui,Li, Xin,&Che, Tao.(2009).A decision tree algorithm for surface soil freeze/thaw classification over China using SSM/I brightness temperature.REMOTE SENSING OF ENVIRONMENT,113(12),2651-2660.
MLA	Jin, Rui,et al."A decision tree algorithm for surface soil freeze/thaw classification over China using SSM/I brightness temperature".REMOTE SENSING OF ENVIRONMENT 113.12(2009):2651-2660.

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