A decision tree algorithm for surface soil freeze/thaw classification over China using SSM/I brightness temperature
文献类型：期刊论文
| 作者 | Jin, Rui; Li, Xin; Che, Tao |
| 刊名 | REMOTE SENSING OF ENVIRONMENT
 |
| 出版日期 | 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 |
| WOS记录号 | WOS:000271771300010 |
| 出版者 | ELSEVIER SCIENCE INC |
| URI标识 | http://www.irgrid.ac.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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来源：寒区旱区环境与工程研究所
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