Coastal Remote Sensing

Located at the land–water interface, coastal areas are affected by both land and ocean processes and sources of primary and secondary productivity and biodiversity, which is crucial to support life on our planet. Coastal water resources, one of the most productive ecosystems in nature, perform a number of vital ecosystem functions including biological, physical, and chemical modifications of the water column, sediment, and submerged and emergent vegetation. Besides providing food and shelter to numerous commercially and ecologically important organisms, they also make significant contribution to human welfare by providing economic, recreational, and cultural services. Consequently, there is a need for accurate, cost-effective, frequent, and synoptic monitoring methods for studying these complex environments. Remote sensing from airborne and space-borne platform satisfies the aforementioned criteria and offers large-scale data acquisition at regular temporal frequency to monitor these coastal environments. Valuable water resources such as submerged aquatic vegetation (SAV) and emergent wetland vegetation can be mapped, and their biophysical properties and phenology can be studied using satellite remote sensing data. Similarly, traditional water quality measures typically include optically active constituents in water such as chlorophyll-a (chl-a), cyanobacteria, total suspended solids (TSS), light attenuation, and colored dissolved organic matter (CDOM), of which all are currently derived from satellite ocean color technology. Coastal wetlands are threatened by development pressures, oil, and gas exploration activities, storm damage, and climate change-induced sea-level rise. Quite a few remote sensing research papers on wetland mapping deal with developing new algorithms to monitor the biophysical characteristics of the vegetation including canopy chlorophyll content, green biomass, vegetation fraction, and leaf area index (Mishra et al. 2012; Mishra and Ghosh 2013, 2014). Similarly, SAV includes seagrass species that are a vital component of coastal ecological processes including providing nursery and foraging habitats for fishes, protect them from predators, provide food for waterfowl and mammals, absorb wave energy and nutrients, produce oxygen and improve water clarity, and help settle suspended sediment in water by stabilizing bottom sediments (Findlay et al. 2006). Proximal and satellite-based remote sensing techniques have been used extensively to map benthic habitats using complex radiative transfer models (Mishra et al. 2005), underwater object detection models (Cho and Lu 2010), and traditional classification techniques (Maeder et al. 2002). Remote sensing is the only way to achieve quick, intensive, fairly accurate, and large-scale assessment of SAV distribution, composition, and abundance which is of particular interest to coastal environmental managers, scientists, developers, and recreationers because the information serves as an excellent indicator of aquatic environmental quality. Among water quality parameters, chl-a is one of the most frequently monitored quantities using remote sensing techniques. Often time, chl-a is used as a proxy to assess the water ecosystem productivity and its trophic condition. Spectral channels in the blue– green part of the electromagnetic spectrum are heavily affected by the presence of other GIScience & Remote Sensing, 2014 Vol. 51, No. 2, 115–119, http://dx.doi.org/10.1080/15481603.2014.895579