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Compositing the Minimum NDVI for MODIS Data
Liu, Ronggao1,2
2017-03-01
Source PublicationIEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
ISSN0196-2892
Volume55Issue:3Pages:1396-1406
Corresponding AuthorLiu, Ronggao(liurg@igsnrr.ac.cn)
AbstractThe 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.
KeywordData processing remote sensing vegetation mapping
DOI10.1109/TGRS.2016.2623746
WOS KeywordAVHRR DATA ; ATMOSPHERIC CORRECTION ; MONITORING VEGETATION ; LAND ; COVER ; ALGORITHMS ; PHENOLOGY ; PRODUCTS ; SCALE
Indexed BySCI
Language英语
Funding ProjectKey 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]
Funding OrganizationKey Research and Development Programs for Global Change and Adaptation ; National Natural Science Foundation from China ; Carbon Project of the Chinese Academy of Sciences
WOS Research AreaGeochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectGeochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000396106700015
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:6[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/64872
Collection中国科学院地理科学与资源研究所
Corresponding AuthorLiu, Ronggao
Affiliation1.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
Recommended Citation
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.
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