Compositing the Minimum NDVI for MODIS Data
文献类型：期刊论文
| 作者 | Liu, Ronggao1,2 |
| 刊名 | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
 |
| 出版日期 | 2017-03-01 |
| 卷号 | 55期号:3页码:1396-1406 |
| 关键词 | Data processing remote sensing vegetation mapping |
| ISSN号 | 0196-2892 |
| DOI | 10.1109/TGRS.2016.2623746 |
| 通讯作者 | Liu, Ronggao(liurg@igsnrr.ac.cn) |
| 英文摘要 | The maximum and minimum normalized difference vegetation indexes (NDVIs) describe two extremes of vegetation greenness during a predefined period. A maximum NDVI image can be composited easily via the direct selection of the maximum NDVI from multiple observations without the need to mask out cloud or snow. But, a minimum NDVI image cannot be built in a similar manner. In this paper, an approach was proposed to composite the minimum NDVI (the least vegetation greenness) image. The minimum spectral index that consists of the green (555 nm) and SWIR bands (2130 nm) from MODIS data, which was named here as the Brown Vegetation Index (BVI), was taken as a proxy to composite the minimum vegetation NDVI. This composite method performs well on a global scale for the NDVIs that were derived from MODIS land surface reflectance (MOD09A1) products. The BVI-based minimum NDVI was compared with the direct selection of the minimum NDVI after excluding contaminated observations using a refined cloud/snow mask. The comparison shows that the differ-ence for 97% of the minimum NDVI between the two approaches is within the range of +/- 0.1 NDVI unit. Various potential spectral indices for compositing the minimum NDVI were compared, which demonstrated the BVI-based approach was top rated. Several examples demonstrated that the composited minimum NDVI is valuable and effective for identifying evergreen forests, monsoon forests, and double cropping. The minimum NDVI combined with the maximum NDVI would simplify the way to describe intraannual vegetation changes. |
| WOS关键词 | AVHRR DATA ; ATMOSPHERIC CORRECTION ; MONITORING VEGETATION ; LAND ; COVER ; ALGORITHMS ; PHENOLOGY ; PRODUCTS ; SCALE |
| 资助项目 | Key Research and Development Programs for Global Change and Adaptation[2016YFA0600201] ; National Natural Science Foundation from China[41171285] ; Carbon Project of the Chinese Academy of Sciences[XDA05090303] |
| WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000396106700015 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | Key Research and Development Programs for Global Change and Adaptation ; National Natural Science Foundation from China ; Carbon Project of the Chinese Academy of Sciences |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/64871]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Liu, Ronggao |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resource & Environm Informat Syst, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Ronggao. Compositing the Minimum NDVI for MODIS Data[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2017,55(3):1396-1406. |
| APA | Liu, Ronggao.(2017).Compositing the Minimum NDVI for MODIS Data.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,55(3),1396-1406. |
| MLA | Liu, Ronggao."Compositing the Minimum NDVI for MODIS Data".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 55.3(2017):1396-1406. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。