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Leaf Area Index Earth System Data Records from Satellite-borne Sensors

Sangram Ganguly, Boston University, sganguly@bu.edu (Presenting)
Ranga Babu Myneni, Boston University, rmyneni@bu.edu (Presenting)
Yuri Knyazikhin, Boston University, jknjazi@bu.edu

The generation of multi-decade long Earth System Data Records of Leaf Area Index (LAI)from remote sensing measurements of multiple sensors is key to monitoring long-term changes in vegetation due to natural and anthropogenic influences. We developed a physically based approach for deriving LAI products from the AVHRR data that are of comparable quality to the MODIS LAI products. The data set is evaluated both by direct comparisons to ground data and indirectly through intercomparisons with similar data sets. This indirect validation showed satisfactory agreement with existing LAI products, importantly MODIS, at a range of spatial scales, and significant correlations with key climate variables in areas where temperature and precipitation limit plant growth. The data set successfully reproduced well documented spatio-temporal trends and inter-annual variations in vegetation activity in the northern latitudes and semi-arid tropics. Comparison with plot scale field measurements over homogeneous vegetation patches indicated a 7% underestimation when all major vegetation types are taken into account. These validation exercises though limited by the amount of field data, and thus less than comprehensive, indicated satisfactory agreement between the LAI product and field measurements. Overall, the inter-comparison with short-term LAI data sets, evaluation of long term trends with known variations in climate variables, and validation with field measurements together build confidence in the utility of this new 26 year LAI record for long term vegetation monitoring and modeling studies.


NASA Carbon Cycle & Ecosystems Active Awards Represented by this Poster:

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  • Award: In progress
     

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