An Object-Based Linear Weight Assignment Fusion Scheme to Improve Classification Accuracy Using Landsat and MODIS Data at the Decision Level
文献类型：期刊论文
| 作者 | Guan, Xudong1,3; Liu, Gaohuan3; Huang, Chong3; Liu, Qingsheng3; Wu, Chunsheng3; Jin, Yan1,3; Li, Yafei2 |
| 刊名 | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
 |
| 出版日期 | 2017-12-01 |
| 卷号 | 55期号:12页码:6989-7002 |
| 关键词 | Decision fusion fuzzy sets image classification image segmentation remote sensing time-series analysis |
| ISSN号 | 0196-2892 |
| DOI | 10.1109/TGRS.2017.2737780 |
| 通讯作者 | Huang, Chong(huangch@lreis.ac.cn) |
| 英文摘要 | Landsat satellite images are extensively used in land-use studies due to their relatively high spatial resolution. However, the number of usable data sets is limited by the relatively long revisit interval and phenology effects can significantly reduce classification accuracy. Moderate Resolution Imaging Spectroradiometer (MODIS) images have higher temporal frequency and can provide extra time-series information. However, they are limited in their capability to classify heterogeneous landscapes due to their coarse spatial resolution. Fusion of different data sources is a potential solution for improving land-cover classification. This paper proposes a fusion scheme to combine Landsat and MODIS remote sensing data at the decision level. First, multiresolution segmentations on the two kinds of remote sensing data are performed to identify the landscape objects and are used as fusion units in subsequent steps. Then, fuzzy classifications are applied to each of the two different resolution data sets and the classification accuracies are evaluated. According to the performance of the two data sets in classification evaluation, a simple weight assignment technique based on the weighted sum of the membership of imaged objects is implemented in the final classification decision. The weighting factors are calculated based on a confusion matrix and the heterogeneity of detected land cover. The algorithm is capable of integrating the time-series spectral information of MODIS data with spatial contexts extracted from Landsat data, thus improving the land-cover classification accuracy. The overall classification accuracy using the fusion technique increased by 7.43% and 10.46% compared with the results from the individual Landsat and MODIS data, respectively. |
| WOS关键词 | YELLOW-RIVER DELTA ; NDVI TIME-SERIES ; SURFACE REFLECTANCE ; COMPLEX LANDSCAPES ; VEGETATION ; COVER ; CHINA ; INTEGRATION ; DYNAMICS ; SCIENCE |
| 资助项目 | National Natural Science Foundation of China[41661144030] ; National Natural Science Foundation of China[41471335] ; National Natural Science Foundation of China[41561144012] ; National Natural Science Foundation of China[41501430] ; LREIS[O88RA303YA] ; National Science-Technology Support Plan Projects[2013BAD05B03] |
| WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000417363100026 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Natural Science Foundation of China ; LREIS ; National Science-Technology Support Plan Projects |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/60808]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Huang, Chong |
| 作者单位 | 1.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 2.Civil Aviat Univ China, Tianjin 300300, Peoples R China 3.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Guan, Xudong,Liu, Gaohuan,Huang, Chong,et al. An Object-Based Linear Weight Assignment Fusion Scheme to Improve Classification Accuracy Using Landsat and MODIS Data at the Decision Level[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2017,55(12):6989-7002. |
| APA | Guan, Xudong.,Liu, Gaohuan.,Huang, Chong.,Liu, Qingsheng.,Wu, Chunsheng.,...&Li, Yafei.(2017).An Object-Based Linear Weight Assignment Fusion Scheme to Improve Classification Accuracy Using Landsat and MODIS Data at the Decision Level.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,55(12),6989-7002. |
| MLA | Guan, Xudong,et al."An Object-Based Linear Weight Assignment Fusion Scheme to Improve Classification Accuracy Using Landsat and MODIS Data at the Decision Level".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 55.12(2017):6989-7002. |
入库方式： OAI收割
来源：地理科学与资源研究所
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