The NOAA National Estuarine Research Reserve System (NERRS) Program has selected several NERRS sites for evaluation of airborne and satellite sensors for monitoring and mapping emergent wetlands and submerged aquatic vegetation. As part of this Remote Sensing Application Assessment Project (RESAAP), our team is investigating the cost-effectiveness of several remote sensing techniques, including airborne hyperspectral, airborne digital multispectral, high-resolution (e.g. IKONOS) and medium resolution (e.g. Landsat/TM) satellite imagery for observing health related properties of wetlands and estuaries. Wetland losses, biomass changes, invasive species and riparian buffers are being studied and mapped.

         A particularly relevant result is a unique method for remotely sensing wetland changes using biomass as an indicator. To detect biomass changes we use the Modified Soil Adjusted Vegetation Index (MSAVI) with red and near-infrared reflectances derived from Landsat/TM images. This biomass algorithm is applied to a time series of Landsat/TM images and used with selected thresholds to detect wetland changes. To minimize natural variations between images in the time series (e.g. atmospheric, annual, seasonal, etc.) we assume that the relative distribution of biomass in each sub-basin will remain essentially constant over time. Wetland pixels whose MSAVI deviation from the sub-basin mean changes from its previous deviation by more than a selected threshold value are considered as having changed. Threshold selection determines whether many small changes or only the more significant ones are detected. To minimize data costs, only changed sites “flagged” by Landsat/TM are studied in more detail with high-resolution systems, such as IKONOS or airborne scanners.