A Temporal-Spatial Iteration Method to Reconstruct NDVI Time Series Datasets
文献类型：SCI/SSCI论文
| 作者 | Xu L. L.; Li, B. L.; Yuan, Y. C.; Gao, X. Z.; Zhang, T. |
| 发表日期 | 2015 |
| 关键词 | modis ndvi vegetation dynamics cover quality segmentation reflectance extraction regression landsat africa |
| 英文摘要 | Reconstructing normalized difference vegetation index (NDVI) time series datasets is essential for monitoring long-term changes in terrestrial vegetation. Here, a temporal-spatial iteration (TSI) method was developed to estimate the NDVIs of contaminated pixels, based on reliable data. The NDVIs of contaminated pixels were first computed through linear interpolation of adjacent high-quality pixels in the time series. Then, the NDVIs of remaining contaminated pixels were determined based on the NDVI of a high-quality pixel located in the same ecological zone, showing the most similar NDVI change trajectories. These two steps were repeated iteratively, using the estimated NDVIs as high-quality pixels to predict undetermined NDVIs of contaminated pixels until the NDVIs of all contaminated pixels were estimated. A case study was conducted in Inner Mongolia, China. The accuracies of estimated NDVIs using TSI were higher than the asymmetric Gaussian, Savitzky-Golay, and window-regression methods. Root mean square error (RMSE) and mean absolute percent error (MAPE) decreased by 16.7%-86.6% and 18.3%-33.0%, respectively. The TSI method performed better over a range of environmental conditions, the variation of performance by the compared methods was 1.4-5 times that of the TSI method. The TSI method will be most applicable when large numbers of contaminated pixels exist. |
| 出处 | Remote Sensing |
| 卷 | 7 |
| 期 | 7 |
| 页 | 8906-8924 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 2072-4292 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/38963]  |
| 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 | Xu L. L.,Li, B. L.,Yuan, Y. C.,et al. A Temporal-Spatial Iteration Method to Reconstruct NDVI Time Series Datasets. 2015. |
入库方式： OAI收割
来源：地理科学与资源研究所
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