Abstract
Information of seagrass LAI is still lacking in most parts of the world due to the high cost of comprehensive mapping. In this paper, we described the use of remote sensing as the cost and time effective solution to perform continuous seagrass LAI mapping, and discussed the issues and difficulties encountered during the mapping. ASTER VNIR and ALOS AVNIR-2 were used to perform the mapping. We proposed at life-form seagrass classification scheme to accommodate the low accuracy of at species level mapping. We also developed sampling mapping unit consist of several factors affecting the distribution of seagrass LAI. The results showed that sensor, method, and environmental limitation contribute to the low accuracy of seagrass LAI mapping.
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