Mapping of Eelgrass and Other SAV Using Remote Sensing and ...

Mapping of Eelgrass and Other SAV Using Remote Sensing and GIS Chris Mueller NRS 509 November 30, 2004 Of the 58 species of seagrass that grow worldwide, Zostera marina, commonly called eelgrass, is by far the most common along the eastern coast of the US. Its range once extended almost continuously from Nova Scotia down to South Carolina on the East coast and from Alaska to the Gulf of California on the West coast. Its ability to grow is usually limited by the availability of light, and it is therefore confined to water less than approximately 2 meters deep. Eelgrass is a highly productive marine subaquatic vegetation (SAV) that provides important benefits to ecosystems in which it grows. These benefits include improving sediment stability, serving as a food source for various organisms, reduction of shoreline erosion due to lessening of wave energy, and providing refuge habitat for juveniles of some commercially important finfish species. In the 1930’s, North Atlantic populations were nearly decimated by a virulent outbreak of a marine slime mold. In the decades following World War II, public and scientific awareness of the importance of this habitat allowed eelgrass to recover much of its former range. However, anthropogenic impacts such as increased fertilizer use and a steady increase in coastal development have degraded near shore water quality by increasing turbidity and eutrophication. In turn, these factors slowed and eventually reversed the recovery process of eelgrass. Studies have estimated that since the 1970’s, between 45 and 70% of the eelgrass habitat that recovered after the wasting disease outbreak has been lost again. In the past, field surveys have been the predominant method used to determine the existence and extent of eelgrass habitats. This method can be very accurate, however it is also very labor intensive and time consuming and the quality and accuracy of the data can vary depending on the survey methods employed. Aerial photography has also been used to map eelgrass, however the photos are often very expensive to obtain, which could prove problematic for an application such as this, where the extent and shape of a seagrass bed can change from year to year. This literature review will give an overview of the technologies used to map eelgrass and other subaquatic vegetation as well as elucidating some of the difficulties associated with this endeavor. To do this comprehensively, it is necessary to look beyond eelgrass in particular, and focus attention on the mapping of seagrass habitats in general. The environment plays a critical role in the ability of remote sensing technology to accurately describe SAV habitats. Factors such as bottom type, water column clarity, water depth, and the presence or absence of habitat with similar reflective characteristics to that of the SAV can all result in the misclassification of pixels in an image. This is true for the majority of the commonly employed technologies, including Landsat and SPOT imagery and multispectral images taken from aircraft (such as the digital images taken by a Compact Airborne Spectrographic Imager). These issues are in addition to the normal difficulties encountered when using these remote sensors such as atmospheric distortions and cloud cover. Aerial photography has been the most widely used method of mapping SAV habitats for many years. The photographs can be manually interpreted and can result in an incredibly accurate delineation of the habitat, usually with more than 90% accuracy. The largest drawbacks to this method are the labor intensive process of interpreting and digitizing the images, the difficulty of correcting the image for distortion (this can be very

difficult if the image does not contain any land), and the relatively high cost of obtaining the photographs in the first place. Despite these difficulties, the images produced by the aforementioned technologies have many important advantages over the labor and time intensive process of field surveying. They can cover relatively large areas in one image, they can be manipulated in various ways to illuminate different aspects of the environment, and perhaps most importantly, they can be easily integrated into a GIS and combined with other data to create a remarkably accurate picture of the location, size and even the density of SAV habitat. One quite new technology that avoids many of the problems associated with remote sensing has recently come out of Japan (Komatsu et. al, 2003). A team used multi-beam sonar to map an SAV bed, producing some startling results and showing a great deal of promise for the technique. The scientists were able to map an area of over 17,000m2 in just under an hour, and the resulting data was easily processed to create a three dimensional visualization of the seagrass bed as well as providing estimates of both the biomass and coverage area of the bed. This technique does not have the misclassification problems associated with other remote sensing technologies, however it can “image” only a small fraction of the area covered by one aerial photograph or satellite image and the costs of equipment, labor and boat time could prove to be substantial for a large area survey. The particular characteristics of the seagrass habitat can also affect the effectiveness of remote sensing. Studies repeatedly find that satellite and aerial images are most accurate when the bed is in shallow water (