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(1997). Cover Mapping and measurement of tropical coastal environments with hyperspectral and high spatial resolution data. International Journal of Remote Sensing: Vol. 18, No. 2, pp. 237-242.

The Saint John River is located in Florida and is a vital resource to the local community. The river system is managed by the Saint John River Water Management District (SJRWMD). The river supports a considerable growth of submerged underwater vegetation (SAV) and this vegetation is a good indicator of ecosystem health and provides feeding and nursery grounds for many animals. In addition the SAV adds dissolved oxygen to the river. It is important to note that the vegetated areas support almost three times the invertebrates as bare areas and SAV improves the habitat quality for invertebrates in both the sediment and water column. It is therefore very important as a management tool to be able to detect and map the location and extent of the SAV. However the river system is classed as a dark water river and it is very difficult to see through the water column. A pilot project using airborne hyperspectral methodology was conducted in 2003 to determine the effectiveness of using this method to map the SAV. The results were very encouraging and subsequent operational surveys have been conducted in 2006, 2008 and 2009. This paper will discuss the methodology used and will provide samples from the recent surveys.

There is increasing use in today's coastal science community of airborne hyperspectral surveys. A growing knowledge base exists of what hyperspectral surveys can provide. However there is also a notable lack of understanding of what issues must be dealt with to plan and successfully complete a coastal hyperspectral survey. This paper will focus on how to effectively plan a coastal hyperspectral survey and will cover a background to the technology as well as physical factors that will affect a survey. How to minimize these impacts and how to deal with them when and if they occur will be covered. Examples will be drawn from actual project work and will be used in the presentation.

Trends in coral cover are widely used to indi- cate the health of coral reefs but are costly to obtain from field survey over large areas. In situ studies of reflected spectra at the coral surface show that living and recently dead colonies can be distinguished. Here, we investigate whether such spectral differences can be detected using an airborne remote sensing instrument. The Compact Airborne Spectrographic Imager (Itres Research Ltd, Canada) was flown in two configurations: 10 spectral bands with 1-m 2 pixels and 6 spectral bands with 0.25-m 2 pixels. First, we show that an instrument with 10 spectral bands possesses adequate spectral res- olution to distinguish living Porites, living Pocillopora spp., partially dead Porites, recently dead Porites (total colony mortality within 6 months), old dead (>6 months) Porites, Halimeda spp., and coralline red algae when there is no water column to confuse spectra. All substrata were distinguished using fourth-order spectral derivatives around 538 nm and 562 nm. Then, at a shallow site (Tivaru) at Rangiroa Atoll, Tuamotu Archipelago (French Polynesia), we show that live and dead coral can be distinguished from the air to a depth of at least 4 m using first- and fourth-order spectral derivatives between 562-580 nm. However, partially dead and recently dead Poritescolonies could not be distinguished from an airborne platform. Spectral dif- ferences among substrata are then exploited to predict the cover of reef substrata in ten 25-m 2 plots at nearby Motu Nuhi (max depth 8 m). The actual cover in these plots was determined in situ using quadrats with a 0.01- m 2 grid. Considerable disparity occurred between field and image-based measures of substrate cover within individual 25-m 2 quadrats. At this small scale, disparity, measured as the absolute difference in cover between field and remote-sensing methods, reached 25% in some substrata but was always less than 10% for living coral (99% of which consisted of Porites spp.). At the scale of the reef (all ten 25-m 2 quadrats), however, disparities in percent cover between imagery and field data were less than 10% for all substrata and extremely low for some classes (e.g.