Analysing NDVI for the African continent using the geostationary meteosat second generation SEVIRI sensor
This study presents first results on Normalized Difference Vegetation Index (NDVI), from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor onboard the geostationary satellite Meteosat Second Generation (MSG) covering the African continent. With a temporal resolution of 15 min MSG off...
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          | Published in | Remote sensing of environment Vol. 101; no. 2; pp. 212 - 229 | 
|---|---|
| Main Authors | , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        New York, NY
          Elsevier Inc
    
        30.03.2006
     Elsevier Science  | 
| Subjects | |
| Online Access | Get full text | 
| ISSN | 0034-4257 1879-0704  | 
| DOI | 10.1016/j.rse.2005.11.013 | 
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| Abstract | This study presents first results on Normalized Difference Vegetation Index (NDVI), from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor onboard the geostationary satellite Meteosat Second Generation (MSG) covering the African continent. With a temporal resolution of 15 min MSG offers complementary information for NDVI monitoring compared to vegetation monitoring based on polar orbiting satellites. The improved temporal resolution has potential implications for accurate NDVI assessment of the African continent; e.g. the increased amount of available scenes are expected to help overcome problems related to cloud cover which makes the MSG data particularly well suited for early warning systems. Time series of 2004 MSG NDVI was compared to MODIS (Moderate Resolution Imaging Spectroradiometer) Terra and Aqua NDVI for the Dahra site in the Senegalese Sahel, West Africa. It was found that NDVI was available for 82 days with multiple cloud free acquisitions per day during the growing season as compared to 47 days with information from either MODIS Terra or Aqua for that particular site. Differences in MSG SEVIRI and MODIS BRDF on a seasonal scale were found to influence the time series of NDVI for the test site; MSG NDVI being higher than MODIS in July–August and lower in October–November. Preliminary composite analysis suggests that the period of compositing to produce continent scale cloud free products can be reduced to ∼5 days using MSG NDVI as compared to polar orbiting data. With the availability of diurnal reflectance information the significance of differences between the red and near-infrared wavelengths due to anisotropy become evident, causing diurnal variations in observed NDVI. Diurnal MSG NDVI was compared to in situ measured MSG NDVI at the test site in Senegal and the same “bowl-shaped” diurnal curve was found for a medium dense cover of annual grasses. The range in observed NDVI and time of diurnal minimum was different due to different viewing geometry. Daily minimum of in situ measured NDVI was around solar noon whereas minimum MSG NDVI occurs one hour prior to noon due to the test site location 12° west of the satellite sensor. Diurnal variation in observed NDVI was studied for a number of pixels characterized by different sensor view zenith angles and vegetation types. This analysis illustrated the diurnal NDVI dependency of illumination conditions, view angle and vegetation intensity and pinpoints the importance of proper BRDF modeling to produce daily values of MSG NDVI normalized for acquisition time, which will be the subject of a forthcoming paper. | 
    
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| AbstractList | This study presents first results on Normalized Difference Vegetation Index (NDVI), from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor onboard the geostationary satellite Meteosat Second Generation (MSG) covering the African continent. With a temporal resolution of 15 min MSG offers complementary information for NDVI monitoring compared to vegetation monitoring based on polar orbiting satellites. The improved temporal resolution has potential implications for accurate NDVI assessment of the African continent; e.g. the increased amount of available scenes are expected to help overcome problems related to cloud cover which makes the MSG data particularly well suited for early warning systems. Time series of 2004 MSG NDVI was compared to MODIS (Moderate Resolution Imaging Spectroradiometer) Terra and Aqua NDVI for the Dahra site in the Senegalese Sahel, West Africa. It was found that NDVI was available for 82 days with multiple cloud free acquisitions per day during the growing season as compared to 47 days with information from either MODIS Terra or Aqua for that particular site. Differences in MSG SEVIRI and MODIS BRDF on a seasonal scale were found to influence the time series of NDVI for the test site; MSG NDVI being higher than MODIS in July–August and lower in October–November. Preliminary composite analysis suggests that the period of compositing to produce continent scale cloud free products can be reduced to ∼5 days using MSG NDVI as compared to polar orbiting data. With the availability of diurnal reflectance information the significance of differences between the red and near-infrared wavelengths due to anisotropy become evident, causing diurnal variations in observed NDVI. Diurnal MSG NDVI was compared to in situ measured MSG NDVI at the test site in Senegal and the same “bowl-shaped” diurnal curve was found for a medium dense cover of annual grasses. The range in observed NDVI and time of diurnal minimum was different due to different viewing geometry. Daily minimum of in situ measured NDVI was around solar noon whereas minimum MSG NDVI occurs one hour prior to noon due to the test site location 12° west of the satellite sensor. Diurnal variation in observed NDVI was studied for a number of pixels characterized by different sensor view zenith angles and vegetation types. This analysis illustrated the diurnal NDVI dependency of illumination conditions, view angle and vegetation intensity and pinpoints the importance of proper BRDF modeling to produce daily values of MSG NDVI normalized for acquisition time, which will be the subject of a forthcoming paper. This study presents first results on Normalized Difference Vegetation Index (NDVI), from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor onboard the geostationary satellite Meteosat Second Generation (MSG) covering the African continent. With a temporal resolution of 15 min MSG offers complementary information for NDVI monitoring compared to vegetation monitoring based on polar orbiting satellites. The improved temporal resolution has potential implications for accurate NDVI assessment of the African continent; e.g. the increased amount of available scenes are expected to help overcome problems related to cloud cover which makes the MSG data particularly well suited for early warning systems. Time series of 2004 MSG NDVI was compared to MODIS (Moderate Resolution Imaging Spectroradiometer) Terra and Aqua NDVI for the Dahra site in the Senegalese Sahel, West Africa. It was found that NDVI was available for 82 days with multiple cloud free acquisitions per day during the growing season as compared to 47 days with information from either MODIS Terra or Aqua for that particular site. Differences in MSG SEVIRI and MODIS BRDF on a seasonal scale were found to influence the time series of NDVI for the test site; MSG NDVI being higher than MODIS in July-August and lower in October- November. Preliminary composite analysis suggests that the period of compositing to produce continent scale cloud free products can be reduced to 5 days using MSG NDVI as compared to polar orbiting data. With the availability of diurnal reflectance information the significance of differences between the red and near-infrared wavelengths due to anisotropy become evident, causing diurnal variations in observed NDVI. Diurnal MSG NDVI was compared to in situ measured MSG NDVI at the test site in Senegal and the same "bowl-shaped" diurnal curve was found for a medium dense cover of annual grasses. The range in observed NDVI and time of diurnal minimum was different due to different viewing geometry. Daily minimum of in situ measured NDVI was around solar noon whereas minimum MSG NDVI occurs one hour prior to noon due to the test site location 12 degree west of the satellite sensor. Diurnal variation in observed NDVI was studied for a number of pixels characterized by different sensor view zenith angles and vegetation types. This analysis illustrated the diurnal NDVI dependency of illumination conditions, view angle and vegetation intensity and pinpoints the importance of proper BRDF modeling to produce daily values of MSG NDVI normalized for acquisition time, which will be the subject of a forthcoming paper.  | 
    
| Author | Stisen, Simon Fensholt, Rasmus Tucker, Compton Sandholt, Inge  | 
    
| Author_xml | – sequence: 1 givenname: Rasmus surname: Fensholt fullname: Fensholt, Rasmus email: rf@geogr.ku.dk organization: Institute of Geography, University of Copenhagen, Øster Voldgade 10, DK-1350 Copenhagen, Denmark – sequence: 2 givenname: Inge surname: Sandholt fullname: Sandholt, Inge organization: Institute of Geography, University of Copenhagen, Denmark – sequence: 3 givenname: Simon surname: Stisen fullname: Stisen, Simon organization: Institute of Geography, University of Copenhagen, Denmark – sequence: 4 givenname: Compton surname: Tucker fullname: Tucker, Compton organization: NASA Goddard Space Flight Center, Greenbelt Maryland, United States  | 
    
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| Keywords | MSG In situ measurements Vegetation monitoring Geostationary NDVI Africa time series analysis Spectroradiometry Vegetation index Image processing Growing season vegetation measurement sensor clouds measurement evaluation imagery Cloudiness reflectance Space remote sensing Geostationary satellite monitoring in situ Polar orbiting satellite seasonal variations  | 
    
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| Snippet | This study presents first results on Normalized Difference Vegetation Index (NDVI), from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor... | 
    
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| SubjectTerms | Africa Animal, plant and microbial ecology Applied geophysics Biological and medical sciences Earth sciences Earth, ocean, space Exact sciences and technology Fundamental and applied biological sciences. Psychology General aspects. Techniques Geostationary In situ measurements Internal geophysics MSG NDVI Teledetection and vegetation maps Vegetation monitoring  | 
    
| Title | Analysing NDVI for the African continent using the geostationary meteosat second generation SEVIRI sensor | 
    
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