A Bayesian Based Method to Generate a Synergetic Land-Cover Map from Existing Land-Cover Products
文献类型：SCI/SSCI论文
| 作者 | Chen J. |
| 发表日期 | 2014 |
| 关键词 | land cover Bayes theory data fusing IGBP remote sensing validation data set igbp discover avhrr data modis classification model datasets vegetation accuracy design |
| 英文摘要 | Global land cover is an important parameter of the land surface and has been derived by various researchers based on remote sensing images. Each land cover product has its own disadvantages and limitations. Data fusion technology is becoming a notable method to fully integrate existing land cover information. In this paper, we developed a method to generate a synergetic global land cover map (synGLC) based on Bayes theorem. A state probability vector was defined to precisely and quantitatively describe the land cover classification of every pixel and reduce the errors caused by legends harmonization and spatial resampling. Simple axiomatic approaches were used to generate the prior land cover map, in which pixels with high consistency were regarded to be correct and then used as benchmark to obtain posterior land cover map. Validation results show that our hybrid land cover map (synGLC, the dataset is available on request) has the best overall performance compared with the existing global land cover products. Closed shrub-lands and permanent wetlands have the highest uncertainty in our fused land cover map. This novel method can be extensively applied to fusion of land cover maps with different legends, spatial resolutions or geographic ranges. |
| 出处 | Remote Sensing |
| 卷 | 6 |
| 期 | 6 |
| 页 | 5589-5613 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 2072-4292 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/29489]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Chen J.. A Bayesian Based Method to Generate a Synergetic Land-Cover Map from Existing Land-Cover Products. 2014. |
入库方式： OAI收割
来源：地理科学与资源研究所
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