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Characterization of vegetation patterns in a Venice lagoon saltmarsh from drone-based hyperspectral remote sensing
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Abstract(s)
Coastal wetlands are unique and complex geomorphological systems that respond to a wide range of changing influences, and their responses remain poorly understood, emphasizing the need for and importance of this study. These ecosystems provide useful feedbacks to coastal systems, such as soil stabilization and coastal protection. They are very important carbon sinks. For carbon to be stored in the soils there must be biomass that is produced. This study focuses on the above ground biomass and the below ground biomass in the saltmarsh in order to evaluate the amount of organic matter that is stored in the soils. To obtain this, field campaigns were conducted to sample the above ground vegetation and core samples to analyse the amount of vegetation biomass and carbon stock in the soil. The marsh selected for this study is characterized by three different levels of elevation, high mid and low. We found that the middle marsh is the area that stores the highest amount of organic matter in the soil as compared to the lower and the higher marsh. In addition, we found that there is a linear positive correlation between the AGB and the BGB. Furthermore, the study concludes that it is possible to use vegetation indices retrieved from remote sensing to characterize the biomass. The NDVI (Normalized Difference Vegetation index) demonstrated to be a good proxy for the AGB only for low and mid-marsh vegetation species, while it saturates for high-marsh high-biomass vegetation. Studying the distribution of the NDVI ranges across the studied marsh, we found that it is mainly covered by dense vegetation, with AGB biomass larger than 400 g/m2.
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Above-ground biomass Below-ground biomass Bulk density Organic carbon Hyperspectral imaging Vegetation index NDVI