Corner Inlet and Nooramunga Habitat Mapping Project – Part 2 : High resolution mapping and change detection analysis using 2011 Rapid Eye Satellite Image compared to 2009 ALOS Satellite Image

Building on a habitat mapping project completed in 2011, Deakin University was commissioned by Parks Victoria (PV) to apply the same methodology and ground-truth data to a second, more recent and higher resolution satellite image to create habitat maps for areas within the Corner Inlet and Nooramunga Marine and Coastal Park and Ramsar area. A ground-truth data set using in situ video and still photographs was used to develop and assess predictive models of benthic marine habitat distributions incorporating data from both RapidEye satellite imagery (corrected for atmospheric and water column effects by CSIRO) and LiDAR (Light Detection and Ranging) bathymetry. This report describes the results of the mapping effort as well as the methodology used to produce these habitat maps.

Overall accuracies of habitat classifications were good, with error rates similar to or better than the earlier classification (>73 % and kappa values > 0.58 for both study localities). The RapidEye classification failed to accurately detect Pyura and reef habitat classes at the Corner Inlet locality, possibly due to differences in spectral frequencies. For comparison, these categories were combined into a ‘non-seagrass’ category, similar to the one used at the Nooramunga locality in the original classification. Habitats predicted with highest accuracies differed from the earlier classification and were Posidonia in Corner Inlet (89%), and bare sediment (no-visible seagrass class) in Nooramunga (90%). In the Corner Inlet locality reef and Pyura habitat categories were not distinguishable in the repeated classification and so were combined with bare sediments. The majority of remaining classification errors were due to the misclassification of Zosteraceae as bare sediment and vice versa. Dominant habitats were the same as those from the 2011 classification with some differences in extent. For the Corner Inlet study locality the no-visible seagrass category remained the most extensive (9059 ha), followed by Posidonia (5,513 ha) and Zosteraceae (5,504 ha). In Nooramunga no-visible seagrass (6,294 ha), Zosteraceae (3,122 ha) and wet saltmarsh (1,562 ha) habitat classes were most dominant.

Change detection analyses between the 2009 and 2011 imagery were undertaken as part of this project, following the analyses presented in Monk et al. (2011) and incorporating error estimates from both classifications. These analyses indicated some shifts in classification between Posidonia and Zosteraceae as well as a general reduction in the area of Zosteraceae. Issues with classification of mixed beds were apparent, particularly in the main Posidonia bed at Nooramunga where a mosaic of Zosteraceae and Posidonia was seen that was not evident in the ALOS classification. Results of a reanalysis of the 1998-2009 change detection illustrating effects of binning of mixed beds is also provided as an appendix.

This work has been successful in providing baseline maps at an improved level of detail using a repeatable method meaning that any future changes in intertidal and shallow water marine habitats may be assessed in a consistent way with quantitative error assessments. In wider use, these maps should also allow improved conservation planning, advance fisheries and catchment management, and progress infrastructure planning to limit impacts on the Inlet environment.

Practical field use of eye-tracking devices for consumer research in the retail environment

Eye-tracking equipment is now affordable and portable, making it a practical instrument for consumer research. Engineered to best analyze gaze on a plane (e.g., a retail shelf), both portable eye-tracking glasses and computer monitor–mounted hardware can play key roles in analyzing merchandise displays to better understand what consumers view. Researchers and practitioners can use that information to improve the sales efficacy of displays. Eye-tracking hardware was nearly exclusively used to investigate the reading process but can now be used for a broader range of study, namely in retail settings. This article presents an approach to using glasses eye tracker (GET) and light eye tracker (LET) eye-tracking hardware for applied consumer research in the field. We outline equipment use, study construction, data extraction as well as benefits and limitations of the technology collected from several pilot studies.

The movements and submergence behaviour of male green turtles at Ascension Island

The movements and submergence behaviour of two male green turtles (Chelonia mydas) on their mating grounds at Ascension Island were investigated by satellite telemetry. During the mating season, males tended to conduct much shorter dives (typically <15 min) than those recorded previously for females during the internesting period at this rookery. This suggests that throughout the mating season males maintained relatively high activity levels, presumably associated with locating and mating with as many females as possible to maximise their reproductive output. At the end of their residence at the mating ground, the two males conducted longer dives (48 min and 21 min, respectively), suggesting that they rested before their migration away from the island. Although very few locations were obtained during this migration, those obtained showed that males migrate to South America, as has been shown previously for females from this population.