Evaluation of four supervised learning methods for benthic habitat mapping using backscatter from multi-beam sonar

An understanding of the distribution and extent of marine habitats is essential for the implementation of ecosystem-based management strategies. Historically this had been difficult in marine environments until the advancement of acoustic sensors. This study demonstrates the applicability of supervised learning techniques for benthic habitat characterization using angular backscatter response data. With the advancement of multibeam echo-sounder (MBES) technology, full coverage datasets of physical structure over vast regions of the seafloor are now achievable. Supervised learning methods typically applied to terrestrial remote sensing provide a cost-effective approach for habitat characterization in marine systems. However the comparison of the relative performance of different classifiers using acoustic data is limited. Characterization of acoustic backscatter data from MBES using four different supervised learning methods to generate benthic habitat maps is presented. Maximum Likelihood Classifier (MLC), Quick, Unbiased, Efficient Statistical Tree (QUEST), Random Forest (RF) and Support Vector Machine (SVM) were evaluated to classify angular backscatter response into habitat classes using training data acquired from underwater video observations. Results for biota classifications indicated that SVM and RF produced the highest accuracies, followed by QUEST and MLC, respectively. The most important backscatter data were from the moderate incidence angles between 30° and 50°. This study presents initial results for understanding how acoustic backscatter from MBES can be optimized for the characterization of marine benthic biological habitats. © 2012 by the authors.

Habitat Map for Lizard Island reef, Australia derived from a photo-transect survey field data collected in December 2011 and September/October 2012

An object based image analysis approach (OBIA) was used to create a habitat map of the Lizard Reef. Briefly, georeferenced dive and snorkel photo-transect surveys were conducted at different locations surrounding Lizard Island, Australia. For the surveys, a snorkeler or diver swam over the bottom at a depth of 1-2m in the lagoon, One Tree Beach and Research Station areas, and 7m depth in Watson's Bay, while taking photos of the benthos at a set height using a standard digital camera and towing a surface float GPS which was logging its track every five seconds. The camera lens provided a 1.0 m x 1.0 m footprint, at 0.5 m height above the benthos. Horizontal distance between photos was estimated by fin kicks, and corresponded to a surface distance of approximately 2.0 - 4.0 m. Approximation of coordinates of each benthic photo was done based on the photo timestamp and GPS coordinate time stamp, using GPS Photo Link Software (www.geospatialexperts.com). Coordinates of each photo were interpolated by finding the gps coordinates that were logged at a set time before and after the photo was captured. Dominant benthic or substrate cover type was assigned to each photo by placing 24 points random over each image using the Coral Point Count excel program (Kohler and Gill, 2006). Each point was then assigned a dominant cover type using a benthic cover type classification scheme containing nine first-level categories - seagrass high (>=70%), seagrass moderate (40-70%), seagrass low (<= 30%), coral, reef matrix, algae, rubble, rock and sand. Benthic cover composition summaries of each photo were generated automatically in CPCe. The resulting benthic cover data for each photo was linked to GPS coordinates, saved as an ArcMap point shapefile, and projected to Universal Transverse Mercator WGS84 Zone 56 South. The OBIA class assignment followed a hierarchical assignment based on membership rules with levels for "reef", "geomorphic zone" and "benthic community" (above).

Habitat map of Danajon Bank, Philippines, derived from a high-spatial-resolution multi-spectral satellite image and georeferenced point intercept transect and spot-check survey field data, using an object-based image classification method

A mosaic of two WorldView-2 high resolution multispectral images (Acquisition dates: October 2010 and April 2012), in conjunction with field survey data, was used to create a habitat map of the Danajon Bank, Philippines (10°15'0'' N, 124°08'0'' E) using an object-based approach. To create the habitat map, we conducted benthic cover (seafloor) field surveys using two methods. Firstly, we undertook georeferenced point intercept transects (English et al., 1997). For ten sites we recorded habitat cover types at 1 m intervals on 10 m long transects (n= 2,070 points). Second, we conducted geo-referenced spot check surveys, by placing a viewing bucket in the water to estimate the percent cover benthic cover types (n = 2,357 points). Survey locations were chosen to cover a diverse and representative subset of habitats found in the Danajon Bank. The combination of methods was a compromise between the higher accuracy of point intercept transects and the larger sample area achievable through spot check surveys (Roelfsema and Phinn, 2008, doi:10.1117/12.804806). Object-based image analysis, using the field data as calibration data, was used to classify the image mosaic at each of the reef, geomorphic and benthic community levels. The benthic community level segregated the image into a total of 17 pure and mixed benthic classes.

Quantitative experimental comparison of single-beam, sidescan, and multibeam benthic habitat maps

Map comparison is a relatively uncommon practice in acoustic seabed classification to date, contrary to the field of land remote sensing, where it has been developed extensively over recent decades. The aim here is to illustrate the benefits of map comparison in the underwater realm with a case study of three maps independently describing the seabed habitats of the Te Matuku Marine Reserve (Hauraki Gulf, New Zealand). The maps are obtained from a QTC View classification of a single-beam echosounder (SBES) dataset, manual segmentation of a sidescan sonar (SSS) mosaic, and automatic classification of a backscatter dataset from a multibeam echosounder (MBES). The maps are compared using pixel-to-pixel similarity measures derived from the literature in land remote sensing. All measures agree in presenting the MBES and SSS maps as the most similar, and the SBES and SSS maps as the least similar. The results are discussed with reference to the potential of MBES backscatter as an alternative to SSS mosaic for imagery segmentation and to the potential of joint SBES–SSS survey for improved habitat mapping. Other applications of map-similarity measures in acoustic classification of the seabed are suggested.

Benthic habitat mapping in the Olympic Coast National Marine Sanctuary: Classification of side scan sonar data from survey HMPR-108-2002-01: Version I

In September 2002, side scan sonar was used to image a portion of the sea floor in the northern OCNMS and was mosaiced at 1-meter pixel resolution using 100 kHz data collected at 300-meter range scale. Video from a remotely-operated vehicle (ROV), bathymetry data, sedimentary samples, and sonar mapping have been integrated to describe geological and biological aspects of habitat and polygon features have been created and attributed with a hierarchical deep-water marine benthic classification scheme (Greene et al. 1999). The data can be used with geographic information system (GIS) software for display, query, and analysis. Textural analysis of the sonar images provided a relatively automated method for delineating substrate into three broad classes representing soft, mixed sediment, and hard bottom. Microhabitat and presence of certain biologic attributes were also populated into the polygon features, but strictly limited to areas where video groundtruthing occurred. Further groundtruthing work in specific areas would improve confidence in the classified habitat map. (PDF contains 22 pages.)

Habitat Suitability Analysis of the Critically Endangered Florida Panther

The purpose of this study was to conduct a habitat suitability analysis of the critically endangered Florida panther (Felis concolor coryi) in Florida. We gathered land cover, population and road data from the Florida Geographic Data Library and performed map algebra using ESRI’s ArcGIS to compile a suitable habitat map. We found that there is 20381.7 km² of highly suitable habitat and 557124.4 km² of less desirable but usable habitat for the Florida panther. The highest concentration of highly suitable habitat is in Big Cypress National Park, with smaller patches in Tates Hell State Forest and along the southeast portion of the Panhandle. Due to extensive fragmentation, however, and without establishment of habitat linkages to the existing southern population, there is little chance of survival of additional panther populations in much of northern Florida.

Phylogenetics, taxon delimitation and phylogenetic diversity

Throughout the history of Linnean taxonomy, species have been described with varying degrees of justification. Many descriptions have been based on only a few ambiguous morphological characters. Moreover, species have been considered natural, well-defined units whereas higher taxa have been treated as disparate, non-existent creations. In the present thesis a few such cases were studied in detail. Often the species-level descriptions were based on only a few specimens and the variation previously thought to be interspecific was found to be intraspecific. In some cases morphological characters were sufficient to resolve the evolutionary relationships between the taxa, but generally more resolution was gained by the addition of molecular evidence. However, both morphological and molecular data were found to be deceptive in some cases. The DNA sequences of morphologically similar specimens were found to differ distinctly in some cases, whereas in other closely related species the morphology of specimens with identical DNA sequences differed substantially. This study counsels caution when evolutionary relationships are being studied utilizing only one source of evidence or a very limited number of characters (e.g. barcoding). Moreover, it emphasizes the importance of high quality data as well as the utilization of proper methods when making scientific inferences. Properly conducted analyses produce robust results that can be utilized in numerous interesting ways. The present thesis considered two such extensions of systematics. A novel hypothesis on the origin of bioluminescence in Elateriformia beetles is presented, tying it to the development of the clicking mechanism in the ancestors of these animals. An entirely different type of extension of systematics is the proposed high value of the white sand forests in maintaining the diversity of beetles in the Peruvian Amazon. White sand forests are under growing pressure from human activities that lead to deforestation. They were found to harbor an extremely diverse beetle fauna and many taxa were specialists living only in this unique habitat. In comparison to the predominant clay soil forests, considerably more elateroid beetles belonging to all studied taxonomic levels (species, genus, tribus, and subfamily) were collected in white sand forests. This evolutionary diversity is hypothesized to be due to a combination of factors: (1) the forest structure, which favors the fungus-plant interactions important for the elateroid beetles, (2) the old age of the forest type favoring survival of many evolutionary lineages and (3) the widespread distribution and fragmentation of the forests in the Miocene, favoring speciation.

Benthic habitats of Buck Island Reef National Monument

NOAA’s Center for Coastal Monitoring and Assessment’s Biogeography Branch has mapped and characterized large portions of the coral reef ecosystems inside the U.S. coastal and territorial waters, including the U.S. Caribbean. The complementary protocols used in these efforts have enabled scientists and managers to quantitatively compare different marine ecosystems in tropical U.S. waters. The Biogeography Branch used these same general protocols to generate three seamless habitat maps of the Bank/Shelf (i.e., from 0 ≤50 meters) and the Bank/Shelf Escarpment (i.e., from 50 ≤1,000 meters and from 1,000 ≤ 1,830 meters) inside Buck Island Reef National Monument (BIRNM). While this mapping effort marks the fourth time that the shallow-water habitats of BIRNM have been mapped, it is the first time habitats deeper than 30 meters (m) have been characterized. Consequently, this habitat map provides information on the distribution of mesophotic and deep-water coral reef ecosystems and serves as a spatial baseline for monitoring change in the Monument. A benthic habitat map was developed for approximately 74.3 square kilometers or 98% of the BIRNM using a combination of semi-automated and manual classification methods. The remaining 2% was not mapped due to lack of imagery in the western part of the Monument at depths ranging from 1,000 to 1,400 meters. Habitats were interpreted from orthophotographs, LiDAR (Light Detection and Ranging) imagery and four different types of MBES (Multibeam Echosounder) imagery. Three minimum mapping units (MMUs) (100, 1,000 and 5,000 square meters) were used because of the wide range of depths present in the Monument. The majority of the area that was characterized was deeper than 30 m on the Bank/Shelf Escarpment. This escarpment area was dominated by uncolonized sand which transitioned to mud as depth increased. Bedrock was exposed in some areas of the escarpment, where steep slopes prevented sediment deposition. Mesophotic corals were seen in the underwater video, but were too sparsely distributed to be reliably mapped from the source imagery. Habitats on the Bank/Shelf were much more variable than those seen on the Bank/Shelf Escarpment. The majority of this shelf area was comprised of coral reef and hardbottom habitat dominated by various forms of turf, fleshy, coralline or filamentous algae. Even though algae was the dominant biological cover type, nearly a quarter (24.3%) of the Monument’s Bank/Shelf benthos hosted a cover of 10%-<50% live coral. In total, 198 unique combinations of habitat classes describing the geography, geology and biology of the sea-floor were identified from the three types of imagery listed above. No thematic accuracy assessment was conducted for areas deeper than about 50 meters, most of which was located in the Bank/Shelf Escarpment. The thematic accuracy of classes in waters shallower than approximately 50 meters ranged from 81.4% to 94.4%. These thematic accuracies are similar to those reported for other NOAA benthic habitat mapping efforts in St. John (>80%), the Main Eight Hawaiian Islands (>84.0%) and the Republic of Palau (>80.0%). These digital maps products can be used with confidence by scientists and resource managers for a multitude of different applications, including structuring monitoring programs, supporting management decisions, and establishing and managing marine conservation areas. The final deliverables for this project, including the benthic habitat maps, source imagery and in situ field data, are available to the public on a NOAA Biogeography Branch website (http://ccma.nos.noaa.gov/ecosystems/coralreef/stcroix.aspx) and through an interactive, web-based map application (http://ccma.nos.noaa.gov/explorer/biomapper/biomapper.html?id=BUIS). This report documents the process and methods used to create the shallow to deep-water benthic habitat maps for BIRNM. Chapter 1 provides a short introduction to BIRNM, including its history, marine life and ongoing research activities. Chapter 2 describes the benthic habitat classification scheme used to partition the different habitats into ecologically relevant groups. Chapter 3 explains the steps required to create a benthic habitat map using a combination of semi-automated and visual classification techniques. Chapter 4 details the steps used in the accuracy assessment and reports on the thematic accuracy of the final shallow-water map. Chapter 5 summarizes the type and abundance of each habitat class found inside BIRNM, how these habitats compare to past habitat maps and outlines how these new habitat maps may be used to inform future management activities.

Nocturnal migration patterns of two Caribbean reef fishes, Haemulon sciurus and Lutjanus apodus [Poster]

In the Caribbean, many coral reef associated fishes have been observed making diel migrations, yet little is known about the detailed movement pathways and space use patterns of individual fish. Often these migrations occur along temporally or spatially consistent corridors that connect preferred resting and foraging habitats. Recent analysis of gut contents from Haemulids and Lutjanids, has provided evidence that these species forage in seagrass beds and other habitats near their coral reef refuges. Few studies have provided direct and spatially explicit evidence of nocturnal migrations and detailed day and night space use patterns for individual fish. This study integrated manual acoustic telemetry to track two common reef species, the bluestriped grunt (Haemulon sciurus) and schoolmaster snapper (Lutjanus apodus) throughout their daily home range. Space use patterns of these species were then examined using Geographical Information System (GIS) tools to link movement behavior to seascape structure derived in a benthic habitat map. This study represents a novel integration of spatial technologies to enhance our understanding of the movement ecology of adult H. sciurus and L. apodus.

Shallow-water benthic habitats of St. John, U.S. Virgin Islands

Coral reef ecosystems of the Virgin Islands Coral Reef National Monument, Virgin Islands National Park and the surrounding waters of St. John, U.S. Virgin Islands are a precious natural resource worthy of special protection and conservation. The mosaic of habitats including coral reefs, seagrasses and mangroves, are home to a diversity of marine organisms. These benthic habitats and their associated inhabitants provide many important ecosystem services to the community of St. John, such as fishing, tourism and shoreline protection. However, coral reef ecosystems throughout the U.S. Caribbean are under increasing pressure from environmental and anthropogenic stressors that threaten to destroy the natural heritage of these marine habitats. Mapping of benthic habitats is an integral component of any effective ecosystem-based management approach. Through the implementation of a multi-year interagency agreement, NOAA’s Center for Coastal Monitoring and Assessment - Biogeography Branch and the U.S. National Park Service (NPS) have completed benthic habitat mapping, field validation and accuracy assessment of maps for the nearshore marine environment of St. John. This work is an expansion of ongoing mapping and monitoring efforts conducted by NOAA and NPS in the U.S. Caribbean and replaces previous NOAA maps generated by Kendall et al. (2001) for the waters around St. John. The use of standardized protocols enables the condition of the coral reef ecosystems around St. John to be evaluated in context to the rest of the Virgin Island Territories and other U.S. coral ecosystems. The products from this effort provide an accurate assessment of the abundance and distribution of marine habitats surrounding St. John to support more effective management and conservation of ocean resources within the National Park system. This report documents the entire process of benthic habitat mapping in St. John. Chapter 1 provides a description of the benthic habitat classification scheme used to categorize the different habitats existing in the nearshore environment. Chapter 2 describes the steps required to create a benthic habitat map from visual interpretation of remotely sensed imagery. Chapter 3 details the process of accuracy assessment and reports on the thematic accuracy of the final maps. Finally, Chapter 4 is a summary of the basic map content and compares the new maps to a previous NOAA effort. Benthic habitat maps of the nearshore marine environment of St. John, U.S. Virgin Islands were created by visual interpretation of remotely sensed imagery. Overhead imagery, including color orthophotography and IKONOS satellite imagery, proved to be an excellent source from which to visually interpret the location, extent and attributes of marine habitats. NOAA scientists were able to accurately and reliably delineate the boundaries of features on digital imagery using a Geographic Information System (GIS) and fi eld investigations. The St. John habitat classification scheme defined benthic communities on the basis of four primary coral reef ecosystem attributes: 1) broad geographic zone, 2) geomorphological structure type, 3) dominant biological cover, and 4) degree of live coral cover. Every feature in the benthic habitat map was assigned a designation at each level of the scheme. The ability to apply any component of this scheme was dependent on being able to identify and delineate a given feature in remotely sensed imagery.