Updating land cover automatically based on change detection using satellite images: case study of national forests in Southern California
文献类型：期刊论文
| 作者 | Huang, Shengli1; Ramirez, Carlos1; Kennedy, Kama1; Mallory, Jeffrey1; Wang, Juanle2 ; Chu, Christine3
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| 刊名 | GISCIENCE & REMOTE SENSING
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| 出版日期 | 2017 |
| 卷号 | 54期号:4页码:495-514 |
| 关键词 | land cover update time series images change detection remote sensing |
| ISSN号 | 1548-1603 |
| DOI | 10.1080/15481603.2017.1286727 |
| 通讯作者 | Huang, Shengli(shenglihuang@fs.fed.us) |
| 英文摘要 | Observing dynamic change patterns and higher-order complexities from remotely sensed images is warranted, but the main challenges include image inconsistency, plant phenological differences, weather variations, and difficulties of incorporating natural conditions into automatic image processing. In this study, we proposed a new algorithm and demonstrated it by producing 2002-2008 and 2010 land-cover maps in heterogeneous Southern California based on an existing 2009 land-cover map. The new algorithm improves the baseline land-cover map quality by discarding potential bad land-cover pixels and dividing each land-cover type into several subclasses. Time series Landsat images were used to detect changed and unchanged areas between baseline year and target year t. Subsequently, for each individual year t, each pixel that was identified as unchanged inherited the baseline classification. Otherwise, each pixel in the changed areas was classified by a similar surrogate majority classifier. The demonstration results in Southern California showed that the land-cover temporal pattern captured the observed successional stages of the ecosystem very well. The accuracy assessment had an overall classification accuracies ranging from 81% to 86% and overall kappa coefficients ranging from 0.79 to 0.83. |
| WOS关键词 | CLASSIFICATION ; GENERATION ; INVENTORY ; SYSTEM ; MAPS ; USA |
| 资助项目 | United States Department of Agriculture (USDA), Forest Service, Forest Health Monitoring Program |
| WOS研究方向 | Physical Geography ; Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:000401522100003 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 资助机构 | United States Department of Agriculture (USDA), Forest Service, Forest Health Monitoring Program |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/64452]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Huang, Shengli |
| 作者单位 | 1.US Forest Serv, USDA, Informat Management, Remote Sensing Lab, Reg 5,3237 Peacekeeper Way,Suite 201, Mcclellan, CA 95652 USA 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, 11A,Datun Rd, Beijing 100101, Peoples R China 3.10811 US Forest Serv, Tahoe Natl Forest, Truckee, CA 96161 USA |
| 推荐引用方式 GB/T 7714 | Huang, Shengli,Ramirez, Carlos,Kennedy, Kama,et al. Updating land cover automatically based on change detection using satellite images: case study of national forests in Southern California[J]. GISCIENCE & REMOTE SENSING,2017,54(4):495-514. |
| APA | Huang, Shengli,Ramirez, Carlos,Kennedy, Kama,Mallory, Jeffrey,Wang, Juanle,&Chu, Christine.(2017).Updating land cover automatically based on change detection using satellite images: case study of national forests in Southern California.GISCIENCE & REMOTE SENSING,54(4),495-514. |
| MLA | Huang, Shengli,et al."Updating land cover automatically based on change detection using satellite images: case study of national forests in Southern California".GISCIENCE & REMOTE SENSING 54.4(2017):495-514. |
入库方式： OAI收割
来源：地理科学与资源研究所
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