Automated, objective texture segmentation of multibeam echosounder data - Seafloor survey and substrate maps from James Island to Ozette Lake, Washington Outer Coast

Without knowledge of basic seafloor characteristics, the ability to address any number of critical marine and/or coastal management issues is diminished. For example, management and conservation of essential fish habitat (EFH), a requirement mandated by federally guided fishery management plans (FMPs), requires among other things a description of habitats for federally managed species. Although the list of attributes important to habitat are numerous, the ability to efficiently and effectively describe many, and especially at the scales required, does not exist with the tools currently available. However, several characteristics of seafloor morphology are readily obtainable at multiple scales and can serve as useful descriptors of habitat. Recent advancements in acoustic technology, such as multibeam echosounding (MBES), can provide remote indication of surficial sediment properties such as texture, hardness, or roughness, and further permit highly detailed renderings of seafloor morphology. With acoustic-based surveys providing a relatively efficient method for data acquisition, there exists a need for efficient and reproducible automated segmentation routines to process the data. Using MBES data collected by the Olympic Coast National Marine Sanctuary (OCNMS), and through a contracted seafloor survey, we expanded on the techniques of Cutter et al. (2003) to describe an objective repeatable process that uses parameterized local Fourier histogram (LFH) texture features to automate segmentation of surficial sediments from acoustic imagery using a maximum likelihood decision rule. Sonar signatures and classification performance were evaluated using video imagery obtained from a towed camera sled. Segmented raster images were converted to polygon features and attributed using a hierarchical deep-water marine benthic classification scheme (Greene et al. 1999) for use in a geographical information system (GIS). (PDF contains 41 pages.)

Comments on hydrographic and topographic LIDAR acquisition and merging with multibeam sounding data acquired in the Olympic Coast National Marine Sanctuary

In April 2005, a SHOALS 1000T LIDAR system was used as an efficient alternative for safely acquiring data to describe the existing conditions of nearshore bathymetry and the intertidal zone over an approximately 40.7 km2 (11.8 nm2) portion of hazardous coastline within the Olympic Coast National Marine Sanctuary (OCNMS). Data were logged from 1,593 km (860 nm) of track lines in just over 21 hours of flight time. Several islands and offshore rocks were also surveyed, and over 24,000 geo-referenced digital still photos were captured to assist with data cleaning and QA/QC. The 1 kHz bathymetry laser obtained a maximum water depth of 22.2 meters. Floating kelp beds, breaking surf lines and turbid water were all challenges to the survey. Although sea state was favorable for this time of the year, recent heavy rainfall and a persistent low-lying layer of fog reduced acquisition productivity. The existence of a completed VDatum model covering this same geographic region permitted the LIDAR data to be vertically transformed and merged with existing shallow water multibeam data and referenced to the mean lower low water (MLLW) tidal datum. Analysis of a multibeam bathymetry-LIDAR difference surface containing over 44,000 samples indicated surface deviations from –24.3 to 8.48 meters, with a mean difference of –0.967 meters, and standard deviation of 1.762 meters. Errors in data cleaning and false detections due to interference from surf, kelp, and turbidity likely account for the larger surface separations, while the remaining general surface difference trend could partially be attributed to a more dense data set, and shoal-biased cleaning, binning and gridding associated with the multibeam data for maintaining conservative least depths important for charting dangers to navigation. (PDF contains 27 pages.)

Using ReefBase to create customized maps

One of the most popular sections of the ReefBase website is the online GIS that enables users to create an almost unlimited range of maps showing a wide variety of features. A new version of the GIS, offering an even larger array of facilities and data layers, is online as of early September. In this article, we will provide an introduction to the ReefBase GIS and also highlight some of the powerful but lesser used features of the system.

Benthic habitats of Fish Bay, Coral Bay and the St. Thomas East End Reserve

NOAA’s National Centers for Coastal Ocean Science 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 and qualitatively compare marine ecosystems in tropical U.S. waters. The Biogeography Branch used similar protocols to generate new benthic habitat maps for Fish Bay, Coral Bay and the St. Thomas East End Reserve (STEER). While this mapping effort marks the third time that some of these shallow-water habitats (≤40 m) have been mapped, it is the first time that nearly 100% of the seafloor has been characterized in each of these areas. It is also the first time that high resolution imagery describing seafloor depth has been collected in each of these areas. Consequently, these datasets provide new information describing the distribution of coral reef ecosystems and serve as a spatial baseline for monitoring change in the Fish Bay, Coral Bay and the STEER. Benthic habitat maps were developed for approximately 64.3 square kilometers of seafloor in and around Fish Bay, Coral Bay and the STEER. Twenty seven percent (17.5 square kilometers) of these habitat maps describe the seafloor inside the boundaries of the STEER, the Virgin Islands National Park and the Virgin Islands Coral Reef National Monument. The remaining 73% (46.8 square kilometers) describe the seafloor outside of these MPA boundaries. These habitat maps were developed using a combination of semi-automated and manual classification methods. Habitats were interpreted from aerial photographs and LiDAR (Light Detection and Ranging) imagery. In total, 155 distinct combinations of habitat classes describing the geology and biology of the seafloor were identified from the source imagery.

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.

Analysis of four decades of high elevation climate data

Four decades of instrumented climate records at D1 on Niwot Ridge suggest that high elevation data are an important - and even unique - part of the full climate picture. High elevation data provide information on changing lapse rates as well as model verification for global warming, which is predicted to occur earliest in high latitudes and at high elevations. The D1 records show climatic trends that arguably support global warming, assuming that greater planetary wave amplitude is verification of warming. Lapse rates reflect conditions of air mass stability, atmospheric moisture, and could [sic] cover, which contribute to feedback processes involving temperature, precipitation, and snowpack. The D1 record show a period, 1981-1985, when the lapse rate increased significantly, and this change was not detected by other data.

Ecological models and GIS maps of macroalgae, as bioindicator for ecological status of Hormozgan rocky shores

In this study a total of 75 species were identified, from which 17 species, 9 genes and 6 families; belonged to Green Algae, 18 species, 7 genes and 4 families; belonged to Brown Algae, and 40 species, 18 genes and 11 families; belonged to Red Algae. From total times spent for sampling, it was determined that at lengeh harbor with 6 species, had the lowest diversity of green algae. The species diversity of brown algae at Michael location with 10 species each; had the highest, and Tahooneh location with 5 species; had the lowest species diversity. Species diversity of red algae at Michael location with 28 species; had the highest, and Sayeh Khosh location with 13 species; had the lowest diversity. From all locations where sampling took place, the highest species diversity regarding Time and Space for all three groups of algae; were associated to Late February (20th. Feb. ), and late March(20th. March). Coverage data of macroalgae and Ecological Evaluation Index indicate a high level of eutrophication for the Saieh khosh, and Bostaneh, They are classified as zones with a bad and poor ecological status. It has been proved that concentrations of biogenic elements and phytoplankton blooming are higher in these zones. The best values of the estimated metrics at Tahooneh and Michaeil could be explained with the good ecological conditions in that zone and the absence of pollution sources close to that transect . The values of abundance of macroalgae and Ecological Evaluation Index indicate a moderate ecological conditions for the Koohin, Lengeh and Chirooieh.