NOAA/NERRS REMOTE SENSING APPLICATION PROJECT: USING BIOMASS TO MONITOR CHANGES IN WETLAND HABITAT

摘要

Population growth in coastal regions suggests continuing losses of wetland and adjacent habitats, as waste loads and competition for limited space and resources increase. Coastal wetlands and submersed habitats are being destroyed by erosion, dredge and fill, impoundments, toxic pollutants, eutrophication, excessive turbidity and sedimentation. Yet salt marsh grasses, mangroves, macroalgae and submersed grasses are essential as nourishment and animal habitat. Many marine finfish, shellfish and migratory birds depend on these coastal habitats for their survival. Continued loss of these wetlands may lead to the collapse of some coastal ecosystems and associated fisheries; therefore, documentation of the loss or degradation of coastal wetlands is needed for their conservation and effective management. Remote sensors have been used successfully for several decades to map physical and biological properties of the open ocean and large upland areas. However, coastal wetlands and estuaries require much finer spatial and temporal resolution and present a challenge to sensors currently deployed on satellites and aircraft. For example, many coastal ecosystem are patchy and have narrow, elongated shapes, such as mud flats, riparian/shoreline buffers, nonspecific wetland stands or wetlands existing along edges of bays and rivers. Therefore, they are difficult to detect with the 20-30 meter resolutions of moderate resolution satellites such as Landsat or SPOT. High-resolution satellites, like IKONOS, can detect small wetland sites but are lacking spectral bands, especially in the mid-infrared, needed to discriminate wetland types and forests from wooded wetlands. Also the limited coverage of high-resolution satellites necessitates the use of many images at high cost, if large coastal areas are to be surveyed. Data from airborne hyperspectral scanners are expensive and require highly specialized analysts. To overcome these problems new sensors and analysis methods are being developed. Spectral analysis techniques will benefit from new hyperspectral mappers being deployed on satellites. New image analysis approaches include multi-resolution segmentation, form and texture classification, contextual classification, (proximity, direction, adjacency, inclusion), fuzzy logic classification, neural network analysis, biomass change detection, etc. Also, small remotely-controlled helicopters are becoming available for field data collection. To help coastal managers and scientists choose the most appropriate imagery and analysis technique, 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 multi multi- spectral, high-resolution (e.g. IKONOS) and moderate resolution (e.g. Landsat TM) satellite imagery for observing health-related properties of wetlands and estuaries. (Table 1)