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Remote Sensing for Coastal Management
Nearshore Habitat MappingDetailed representations of nearshore habitats are essential components of marine resource conservation and adaptive management plans whose goals are environmental and economic sustainability. Coastal zone resource analysts use multibeam sonars and airborne multispectral systems to infer the distributions and extents of different habitat classes. The Project: Mapping Natural Resources in the San Diego Region's Nearshore Coastal ZoneThe beaches between Dana Point and Imperial Beach in southern California are valued for their environmental and economic significance; however, they are high wave energy marine environments that have been persistently eroding for many decades. Residents, local government, and state and federal agencies are concerned about the consequences of this natural process if left unmanaged. 
Beach nourishment practices, where offshore sand deposits are pumped onto eroding beaches, are used in other areas around the world that experience the same problem. This technique is a common short-term solution, but it requires periodic maintenance and an effective long-term adaptive management plan. The environmental ramifications of beach nourishment in the nearshore coastal zone are poorly understood, so monitoring activities are important components of a resource management plan that balances environmental sustainability (i.e., a diversity of marine habitats) and economic growth. The success of future conservation and management plans for nearshore habitats and other natural resources (i.e., beach sand) in the San Diego nearshore coastal zone will rely upon accurate baseline information to compare with future observations. In 2000, the California Coastal Conservancy and the San Diego Association of Governments (SANDAG) formed a partnership in cooperation with several other federal, state, and private groups to develop the Nearshore Program as a marine resource management and conservation tool. The Nearshore Program development process was broken into two distinct phases. The first phase adopted a habitat classification scheme, pooled existing data from within the study area, and identified critical areas in the study region that lacked habitat data. The second phase sought to fill these data gaps. Mapping underwater features at a habitat scale requires high resolution data in order to discriminate between tightly spaced habitat patches. Three different sensors were employed to achieve continuous data coverage in the vacant areas. The zone between the shoreline and the 10-meter water depth was mapped using a bathymetric LIDAR sensor and an airborne digital multispectral sensor, while the zone for water depths between 10 and approximately 36 meters was mapped using a multibeam sonar. Mapping the Seafloor with Airborne Multispectral SystemsAirborne multispectral sensors are capable of covering large areas in a short amount of time and collecting earth surface reflectance values in a number of spectral bands. Researchers used an imaging sensor that was configured to penetrate the water in order to differentiate bottom substrates. Extensive post-processing techniques were used to georeference the data and then to combine the individual multispectral images into a single image mosaic that covered the study area. Substrate and vegetation maps were then generated from this mosaic.
This is an example of airborne multispectral imagery along the shoreline in Encinitas, CA, in which different bottom substrates are visible.
This is a bottom substrate classification map of the same area as above. Note the dashed line that marks the boundary between the data derived from the airborne multispectral sensor and the data derived from the multibeam sonar. Mapping the Seafloor with Multibeam SonarMultibeam sonars are capable of quickly collecting hundreds of thousands of very precise depth soundings within the nearshore coastal zone and yield high-resolution bathymetric and backscatter data. A multibeam sonar and a variety of additional equipment was installed on the survey vessel to log position, heading, and orientation information, as well as sound velocity profile data. These data were all processed to produce bathymetric and backscatter maps with a 0.5-meter resolution. A substrate map was then digitized from an overlay of the bathymetric and backscatter maps using substrate types interpreted from the habitat classification system developed during Phase I of the project. Seafloor groundtruth data on various habitat types were also acquired to support the classification work.
This image displays multibeam sonar backscatter data merged with airborne multispectral imagery.
This is a classified map of nearshore habitats derived from the merged data shown above. Areas classified as Insufficient Penetration/No Seafloor Data indicate that the water column turbidity was possibly too high for the multispectral sensor to penetrate to the bottom of the water (possibly because of understory algae). The ResultComprehensive bathymetry, substrate, and vegetation data sets derived from multibeam sonar data and airborne multispectral imagery exist within the Nearshore Program's Internet-based geographic information system data dissemination system within the region between Dana Point and Imperial Beach. In April 2004, Fugro Pelagos also completed the LIDAR mapping for the project, and these bathymetric data will be included in the database at a later date. Resource managers must analyze the bathymetry, substrate, and vegetation data sets together in order to produce habitat maps in accordance with the Nearshore Program habitat classification system. These final maps can subsequently be used to monitor the regional effects of beach nourishment on nearshore habitats over time, as well as to perform potential environmental risk assessments. For More Information |
