An Effective Compound Algorithm for Reconstructing MODIS NDVI Time Series Data and Its Validation Based on Ground Measurements
文献类型：期刊论文
| 作者 | Geng, Liying1; Ma, Mingguo2; Wang, Haibo1 |
| 刊名 | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
 |
| 出版日期 | 2016-08-01 |
| 卷号 | 9期号:8页码:3588-3597 |
| 关键词 | Moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) noise reduction reconstruction techniques regional validation remote sensing products |
| ISSN号 | 1939-1404 |
| DOI | 10.1109/JSTARS.2015.2495112 |
| 通讯作者 | Geng, Liying(gengly@lzb.ac.cn) |
| 英文摘要 | In this study, a compound technique was developed using eight denoising techniques for reconstructing high-quality normalized difference vegetation index (NDVI) time series data. The new algorithm consists of two major procedures: 1) detecting noisy data according to variation in the modification rates of eight selected denoising techniques and 2) using the medians of the denoised values of the eight techniques to replace the noisy data. The eight techniques include the modified best index slope extraction (M-BISE) technique, the Savitzky-Golay (S-G) technique, the mean value iteration (MVI) filter, the asymmetric Gaussian (A-G) technique, the double logistic (D-L) technique, the changing-weight (CW) filter, the interpolation for data reconstruction (IDR) technique, and theWhittaker smoother (WS) technique. The technique was tested with moderate resolution imaging spectroradiometer (MODIS) NDVI time series data derived from MOD09GQ of the Heihe River Basin in China. In situ NDVI data were obtained during one nearly complete growing season for six land-use types in the study area. Analysis of the temporal and spatial characteristics of the reconstructed data revealed that the compound technique performs better than the other techniques. In addition, the lower root-mean-square error (RMSE) of the compound technique, which was calculated using ground measurements, demonstrated the improved performance of the new technique. The main advantage of the new technique is its ability to effectively denoise data and maintain fidelity such that it can be widely used for other NDVI time series data and for other study areas. |
| 收录类别 | SCI |
| WOS关键词 | HEIHE RIVER-BASIN ; IN-SITU MEASUREMENTS ; VEGETATION DYNAMICS ; SMOOTHING ALGORITHMS ; SEASONAL DYNAMICS ; NOISE-REDUCTION ; CHINA ; PHENOLOGY ; PRODUCTS ; INDEX |
| WOS研究方向 | Engineering ; Physical Geography ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS类目 | Engineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000384907200023 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| URI标识 | http://www.irgrid.ac.cn/handle/1471x/2557539 |
| 专题 | 寒区旱区环境与工程研究所 |
| 通讯作者 | Geng, Liying |
| 作者单位 | 1.Chinese Acad Sci, Key Lab Remote Sensing Gansu Prov, Heihe Remote Sensing Expt Res Stn, Cold & Arid Reg Environm & Engn Res Inst, Lanzhou 730000, Peoples R China 2.Southwest Univ, Sch Geog Sci, Chongqing 400715, Peoples R China |
| 推荐引用方式 GB/T 7714 | Geng, Liying,Ma, Mingguo,Wang, Haibo. An Effective Compound Algorithm for Reconstructing MODIS NDVI Time Series Data and Its Validation Based on Ground Measurements[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2016,9(8):3588-3597. |
| APA | Geng, Liying,Ma, Mingguo,&Wang, Haibo.(2016).An Effective Compound Algorithm for Reconstructing MODIS NDVI Time Series Data and Its Validation Based on Ground Measurements.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,9(8),3588-3597. |
| MLA | Geng, Liying,et al."An Effective Compound Algorithm for Reconstructing MODIS NDVI Time Series Data and Its Validation Based on Ground Measurements".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 9.8(2016):3588-3597. |
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来源：寒区旱区环境与工程研究所
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