Brief description
This dataset is a vector shapefile mapping the deep submerged aquatic vegetation on the bottom of the coral atoll lagoons in the Coral Sea within the Australian EEZ. This mapped vegetation predominantly corresponds to erect macroalgae, erect calcifying algae and filamentous algae (Tol, et al., 2023), with an average algae benthic cover of approximately 30 - 40%. This corresponds to only vegetation occurring on the soft sediment of the lagoons. This dataset was mapped from contrast enhanced Sentinel 2 composite imagery (Lawrey and Hammerton, 2022). Most of the mapped atoll lagoon areas were 30 - 60 m deep. Mapping at such depths from satellite imagery is difficult and ambiguous due to there only being a single colour band (Blue B2) that provides useful information about the benthic features at this depth. Additionally satellite sensor noise, cloud artefacts, water clarity changes, uncorrected sun glint, and detector brightness shifts all make distinguishing between high and low benthic cover at depth difficult. To compensate for some of these anomalies the benthic mapping was digitised manually based on visual cues. The most important element was to identify locations where there were clear transitions between sandy areas (with a high benthic reflectance) and vegetation areas (with a low reflectance). These contrast transitions can then act as a local reference for the image contrast between light and dark substrates. These transitions were often clearest around the many patch reefs in the lagoons which have a clear grazing halo of bare sand around their perimeter. These are often then further surrounded by an intensely dark halo, presumably from a high cover of algae. These concentric rings of light and dark substrate provided local references for the image brightness of low and high benthic cover. These cues also indicated where the hard coral substrate were. These were cut out from this dataset. Method: To map the vegetation in the Coral Sea, the primary data sources used were Sentinel-2 image composites optimized for the marine environment (Lawrey and Hammerton, 2022), high-resolution bathymetry data covering part of the region (Beaman, 2017), and drop camera survey results for validation (Tol et al., 2023). An additional set of Sentinel-2 images were collected for Ashmore Reef to help with the mapping of the vegetation in its lagoon (Lawrey and Hammerton, 2024). Most of the vegetation in the lagoonal floors of the atolls in the Coral Sea occur at a depth of 30 - 60 m. At these depths only the blue channel of the satellite imagery provides any useful visual information. Additionally the contrast between bright sand and dark vegetation is very small in the imagery for area at such depths. Artefacts in the imagery due to clouds, sun glint, waves, and sensor noise can easily obscure these small differences. To reduce the noise in the imagery a pixelwise statistical median composite was used, created from 4-10 of the clearest Sentinel-2 images of each scene manually selected from 2016-2021. Cloud masking and sun glint correction were applied before image composition (see Lawrey and Hammerton, 2022 for full details). To allow the deep benthic features to be seen the blue channel of the image composites was greatly contrast enhanced to show the very faint differences in brightness due to changes in the benthos. The amount of contrast enhancement, and thus the maximum depth that could be analysed was limited by the visual anomalies in the imagery and the magnified variations in brightness across the images. The atoll lagoonal areas were classified manually and hand digitised as bare, vegetation or reef based on the estimated benthic reflectance. Lighter benthic regions were assumed to be bare sand, while darker regions assumed to be vegetation or reef features. Determining the benthic reflectance at such depth from satellite imagery is potentially ambiguous as areas might appear dark because they are deep, covered in vegetation or reef, affected by coloured dissolved organic matter in the water column absorbing light, or there is a tonal shift from different satellite sensors across the image swath. These factors make image interpretation challenging. To resolve some of these confounding factors the mapping was done using visual cues to identify reference points across the scene to help compensate for tonal and contrast shifts due to depth, water clarity changes and the satellite sensor. These visual cues identify features where there is a high confidence in the benthic cover (sand or vegetation) and these act as local references for classifying the rest of the area between these reference locations. As most areas of the coral atoll lagoons are gently sloping, rapid changes in visual brightness are typically caused by changes in benthic reflectance, rather than changes in depth. We use this to find the edges of vegetation regions. We employed the following multi-step process to map and verify the oceanic vegetation: 1. Identifying Visual Cues: We identified a set of potential visual cues to detect likely vegetated areas. These cues relied on distinguishing probable patches of sand to estimate local depth and water conditions and observing transitions between light and dark regions to identify vegetation boundaries. 2. Manually mapping: The vegetation boundaries were manually hand digitised based on visual cues in the satellite imagery for Flinders and Holmes Reefs. 3. Benthic Reflectance Estimation: We developed benthic reflectance estimates for the North Flinders and Holmes Reefs regions using both high-resolution and accuracy bathymetry (Beaman, 2017) and satellite imagery (see Lawrey, 2024a for details). 4. Compared Analysis: The initial vegetation mapping from step 1 was compared against the benthic reflectance from step 3 to identify the most reliable visual cue techniques. This identified which were most robust against changes in depth and tonal shifts. 5. Coral Sea Mapping: Using the insights from the previous steps, we manually mapped the remaining Coral Sea region using only satellite imagery. 6. Validation: The final map was validated against the available drop camera survey data on Lihou and Tregrosse Reefs. We previously, separately mapped reefs (Lawrey, 2024c). This mapping was used ensure that reef areas were not interpreted as vegetation. Reef areas were determined by their granular visual texture, their elevated central region, and by the grazing halos around their base. Visual Cues for Benthic Cover Identification: The following is a summary of the key visual cues used to classify the areas as either vegetated or unvegetated. 1. Grazing Halos Around Patch Reefs: Grazing halos appear as pale rings of bare sand surrounding a textured dark, rounded feature (patch reef), see Figure 40 for examples. These occur because herbivorous fish forage and clear the surrounding sand of any algae. While grazing halos are well studied in shallow reef systems, (DiFiore et al., 2019) they are not well studied at the depths seen in the Coral Sea atoll lagoons. In this mapping we, however, assume the grazing halos in the Coral Sea are caused by a similar mechanism and thus where we see them, they indicate a central reef structure surrounded by a sandy area that is largely devoid of algae. Based on a review of bathymetry transects of patch reefs in North Flinders reefs, the depths of these grazing halos tend to be very close in depth to the surrounding lagoon. This allows them to act as an excellent reference for the brightness of sand at the depth of the lagoon in the area near the reef. Frequently, dark halos of dense vegetation surround these grazing halos, serving as a brightness reference for high-density vegetation. 2. Atoll Plains: On the atoll plains, particularly on the western side of Tregrosse Reefs platform there are large patches of dark substrate that have pale patches, unrelated to the presence of reefs. In this case, local tonal references were identified at locations where there was a clear step change in brightness and the shape and texture of the dark areas matched typical patterns of algae seen in other regions. Validation: Since this dataset was manually mapped from noisy and ambiguous imagery, validating this visual mapping approach was essential. The first form of validation was comparing the mapped vegetation boundaries with the benthic reflectance of Flinders reef. This comparison showed a very strong alignment between the manual visual mapping and benthic reflectance (Lawrey, 2024a), with the main deviations occurring around reef edges where the digitised vegetation did not capture all the details. It also deviated in areas where the benthic features were harder to see due to lower water clarity caused by coloured dissolved organic matter increasing the water column light absorption. No significant adjustments were needed to the visual cue approach following this comparison. However, it highlighted the importance of identifying the local visual cues to compensate for varying depths, satellite sensor brightness shifts and changes in the water clarity. The final validation involved comparing vegetation maps of Holmes, Tregrosse, and Lihou Reefs against the results of a drop camera survey conducted by JCU in December 2022 (Tol et al., 2023). The locations of the validation sites are shown in Figure 42. From this survey, 237 locations overlap the atoll lagoons. Figure 42 compares the vegetation density estimated from satellite mapping with the benthic cover assessed through the drop camera survey. This demonstrates a strong relationship between the mapped vegetation density and the benthic cover measured by drop cameras. The data show considerable variability, possibly due to fine-scale vegetation patchiness not captured by the satellite-based mapping. The drop camera results represent very small survey patches (less than 1 m across), while the satellite mapping represents patches around 400 m across. Areas identified as having high benthic vegetation in satellite mapping showed 15-70% (average 40%) algal benthic cover. In contrast, lagoonal regions mapped as sand (outside the identified vegetation but not on reefs) had significantly lower algal benthic cover, ranging from 0-20% with an average of 4%. Limitations: This dataset was mapped at a scale of 1:400k, with our goal being to limit the maximum boundary error to 400 m. Where the imagery was clear the mapped boundary accuracy is likely to be significantly better than this threshold. The spacing of the digitised polygon vertices was adjusted to reflect the level of uncertainty in the boundary. Where visibility was good the digitisation spacing was 100 - 200 m. In high uncertainty areas the digitised distance was increased to 500 - 1000 m. The likely boundary error is approximately equal to the vertex spacing. Many of the large areas of vegetation were littered with hundreds of small patches of lower or no vegetation. These areas were cut out as holes in the digitisation where the holes were a feature larger than 200 - 300 m in size. The vegetation areas were categorised into three levels of vegetation density (Low, Medium and High) based on how dark the substrate appeared, relative to the nearby reference indicators (dark halos around reefs, and clear patches of bare sand). In practice the accuracy of this categorisation is probably quite low, as areas where only cut into these different categories at a large scale. It was very difficult to determine the extent of the vegetation in the lagoon of Ashmore Reef. The lagoon appears to have a low flushing rate and a high level of CDOM accumulates in the lagoon, reducing the visibility to the point were most of the benthos of most of the lagoon is not visible. To help map this reef the full series of Sentinel 2 images was carefully reviewed for tonal differences that indicate the areas of sand and vegetation. Even still only 20% of the boundary of the vegetation could be accurately determined, the rest of the mapped boundary is speculative. Change Log: - 2024-05-21 Eric Lawrey The digitisation of the boundaries were refined by an additional 15%. This included refining the positioning of the boundaries and cutting out holes corresponding to small patch reefs and small sandy areas within larger vegetation areas. This digitisation was done as part of the preparation for the diagram showing the example light and dark local substrate references. These changes resulted in minimal change to the validation results (<1%), but slight reduced the error associated with the digitisation detail. In this update the metadata description was improved based on the text developed for the NESP MaC 2.3 report. Format: - CS_NESP-MaC-2-3_AIMS_Oceanic-veg.shp: Shapefile corresponding to the mapped vegetation boundaries. - CS_JCU_Tol_Drop-cam-Dec-2022_Validation.csv: Join of the JCU drop camera data and the vegetation mapping to allow validation analysis. - metadata\Oceanic-veg_dataset-polygon.geojson: Low resolution boundary of the vegetation mapping used for setting the spatial extent in the metadata record. It is provided for completeness. Data dictionary: - Density: Estimated density of the benthic cover in three categories, Low, Medium and High. Sandy areas, or areas with very low cover were not digitised. Comparing this data to preliminary drop camera results indicates that Low and Medium correspond to an average of 30% benthic cover and High an average of 40% cover. - EdgeAcc_m: (Integer) Approximate accuracy of the feature boundary. Note that in this edition of the dataset only very few polygons were individually tagged with accuracy values. The spacing of the polygon vertices is a better local scale measure of the edge accuracy. - EdgeSrc (Edge Image Sources): (String, 255 characters) The source of the imagery used to digitise the feature or refine its boundary. - RB_Type_L3: Level 3 Reef Boundary Type classification. This classification is chosen to align with the NESP MaC 3.17 Reef Boundary mapping classification. All features are 'Ocean vegetated sediments'. - TypeConf: This is the confidence that the features mapped correspond to the type specified. Care was taken to exclude reefs substrate in the mapped areas, however due to the relative coarse scale of the dataset, some sandy areas and reef areas would be included in some of the polygons. - Area_km2: Area of the polygons in square kilometres. - NvclEco: Natural Values Common Language Ecosystem classification for this feature type. All features are 'Oceanic vegetated sediments'. - NvclEcoComp: Natural Values Common Language Ecosystem Complex classification. All features are 'Ocean coral reefs eAtlas Processing: No modifications were made to the data as part of publication. Location of the data: This dataset is filed in the eAtlas enduring data repository at: data\custodian\2022-2024-NESP-MaC-2\2.3_Improved-Aus-Marine-Park-knowledge\CS_NESP-MaC-2-3_AIMS_Oceanic-vegLineage
Maintenance and Update Frequency: asNeededNotes
CreditThe data collections described in this record are funded by the Australian Government Department of Climate Change, Energy, the Environment and Water (DCCEEW) through the NESP Marine and Coastal Hub. In addition to NESP (DCCEEW) funding, this project is matched by an equivalent amount of in-kind support and co-investment from project partners and collaborators.
This dataset was developed for inclusion into the Natural Values Ecosystem national habitat map used by Parks Australia.
Data time period: 2016-06-08 to 2021-09-15
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Shapefile (1MB) (Download data)
uri :
https://nextcloud.eatlas.org.au/apps/sharealias/a/CS_NESP-MaC-2-3_AIMS_Oceanic-veg
GIS files and Python scripts for downloading source data (Code repository)
uri :
https://github.com/eatlas/CS_NESP-MaC-2-3_AIMS_Oceanic-veg
Lawrey, E., & Hammerton, M. (2022). Coral Sea features satellite imagery and raw depth contours (Sentinel 2 and Landsat 8) 2015 – 2021 (AIMS) [Data set]. eAtlas. (Input data)
doi :
https://doi.org/10.26274/NH77-ZW79
Lawrey, E. (2024a). Estimating benthic reflectance of deep coral atoll lagoons from satellite imagery and bathymetry - Analysis code and case studies (NESP MaC 2.3, AIMS) [Data set]. eAtlas. (Input data)
doi :
https://doi.org/10.26274/s2a8-nw72
Lawrey, E., Hammerton, M. (2024). Marine satellite imagery test collections (AIMS) [Data set]. eAtlas. (Input data)
doi :
https://doi.org/10.26274/zq26-a956
Tol, S. J., Coles, R. G., Shepherd, L., Scott, A., Hoffmann, L., Leeson, P., Ekins, M., Clarke, M., Grech, A., Rasheed, M. A. and York, P. (2023). Benthic Habitat Mapping in the Central Coral Sea Marine Park: Preliminary voyage report for December 2022 survey. JCU Publication, Centre for Tropical Water & Aquatic Ecosystem Research Publication 23/16, Cairns, 86 pp. (Validation data)
Beaman, R. J. (2017). High-resolution depth model for the Great Barrier Reef - 30 m. [Dataset]. Geoscience Australia, Canberra. (Input dataset)
doi :
http://dx.doi.org/10.4225/25/5a207b36022d2
global : 7cb3ac61-dd39-448a-8b2f-2b9d64f153c6
- DOI : 10.26274/709G-AQ12
- global : 9b26bf43-3368-41a5-922e-0bf94529d0d2