Performance Evaluation of Long NDVI Timeseries from AVHRR, MODIS and Landsat Sensors over Landslide-Prone Locations in Qinghai-Tibetan Plateau
文献类型：期刊论文
| 作者 | Sajadi, Payam4; Sang, Yan-Fang4 ; Gholamnia, Mehdi5; Bonafoni, Stefania6; Brocca, Luca1; Pradhan, Biswajeet2,3,7; Singh, Amit8
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| 刊名 | REMOTE SENSING
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| 出版日期 | 2021-08-01 |
| 卷号 | 13期号:16页码:27 |
| 关键词 | HANTS NDVI reconstruction wavelet threshold denoising Qinghai-Tibetan Plateau |
| DOI | 10.3390/rs13163172 |
| 通讯作者 | Sang, Yan-Fang(sangyf@igsnrr.ac.cn) |
| 英文摘要 | The existence of several NDVI products in Qinghai-Tibetan Plateau (QTP) makes it challenging to identify the ideal sensor for vegetation monitoring as an important factor for landslide detection studies. A pixel-based analysis of the NDVI time series was carried out to compare the performances of five NDVI products, including ETM+, OLI, MODIS Series, and AVHRR sensors in QTP. Harmonic analysis of time series and wavelet threshold denoising were used for reconstruction and denoising of the five NDVI datasets. Each sensor performance was assessed based on the behavioral similarity between the original and denoised NDVI time series, considering the preservation of the original shape and time series values by computing correlation coefficient (CC), mean absolute error (MAE), root mean square error (RMSE), and signal to noise ratio (SNR). Results indicated that the OLI slightly outperformed the other sensors in all performance metrics, especially in mosaic natural vegetation, grassland, and cropland, providing 0.973, 0.015, 0.022, and 27.220 in CC, MAE, RMSE, and SNR, respectively. AVHRR showed similar results to OLI, with the best results in the predominant type of land covers (needle-leaved, evergreen, closed to open). The MODIS series performs lower across all vegetation classes than the other sensors, which might be related to the higher number of artifacts observed in the original data. In addition to the satellite sensor comparison, the proposed analysis demonstrated the effectiveness and reliability of the implemented methodology for reconstructing and denoising different NDVI time series, indicating its suitability for long-term trend analysis of different natural land cover classes, vegetation monitoring, and change detection. |
| WOS关键词 | NEURAL-NETWORK MODELS ; TIME-SERIES ; VEGETATION INDEX ; WAVELET ANALYSIS ; GLOBAL LANDSLIDE ; NORTHERN-TIBET ; CLIMATE-CHANGE ; TREND ANALYSIS ; COVER CHANGES ; TM IMAGES |
| 资助项目 | Second Tibetan Plateau Scientific Expedition and Research Program (STEP)[2019QZKK0903] ; National Natural Science Foundation of China[41971040] ; Youth Innovation Promotion Association of CAS[2017074] ; CAS Interdisciplinary Innovation Team[JCTD-2019-04] |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000689989800001 |
| 出版者 | MDPI |
| 资助机构 | Second Tibetan Plateau Scientific Expedition and Research Program (STEP) ; National Natural Science Foundation of China ; Youth Innovation Promotion Association of CAS ; CAS Interdisciplinary Innovation Team |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/165086]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Sang, Yan-Fang |
| 作者单位 | 1.CNR, Res Inst Geohydrol Protect, I-06128 Perugia, Italy 2.Univ Technol Sydney, Fac Engn & IT, Ctr Adv Modelling & Geospatial Informat Syst CAMG, Sydney, NSW 2007, Australia 3.King Abdulaziz Univ, Ctr Excellence Climate Change Res, Jeddah 21589, Saudi Arabia 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China 5.Islamic Azad Univ, Sanandaj Branch, Dept Civil Engn, Sanandaj 6616935391, Iran 6.Univ Perugia, Dept Engn, I-06125 Perugia, Italy 7.Univ Kebangsaan Malaysia, Inst Climate Change, Earth Observat Ctr, Bangi 43600, Selangor, Malaysia 8.TERI Sch Adv Studies, Dept Energy & Environm, New Delhi 110070, India |
| 推荐引用方式 GB/T 7714 | Sajadi, Payam,Sang, Yan-Fang,Gholamnia, Mehdi,et al. Performance Evaluation of Long NDVI Timeseries from AVHRR, MODIS and Landsat Sensors over Landslide-Prone Locations in Qinghai-Tibetan Plateau[J]. REMOTE SENSING,2021,13(16):27. |
| APA | Sajadi, Payam.,Sang, Yan-Fang.,Gholamnia, Mehdi.,Bonafoni, Stefania.,Brocca, Luca.,...&Singh, Amit.(2021).Performance Evaluation of Long NDVI Timeseries from AVHRR, MODIS and Landsat Sensors over Landslide-Prone Locations in Qinghai-Tibetan Plateau.REMOTE SENSING,13(16),27. |
| MLA | Sajadi, Payam,et al."Performance Evaluation of Long NDVI Timeseries from AVHRR, MODIS and Landsat Sensors over Landslide-Prone Locations in Qinghai-Tibetan Plateau".REMOTE SENSING 13.16(2021):27. |
入库方式： OAI收割
来源：地理科学与资源研究所
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