Accuracy Assessment and Monitoring for NOAA Florida Keys Mapping AA ROI-1 (Hawk Channel Near American Shoal)

This report describes the methodologies, analyses, and results for an independent accuracy assessment of a thematic benthic habitat map produced by NOAA for the Florida Keys. It is an analysis of four regional accuracy assessments. Over the course of the Florida Keys mapping project, NOAA amended part of the classification scheme. The original scheme for mapping benthic cover was a tiered approach where certain benthic cover categories were given priority over others (e.g. coral was most important). Recently, this was modified to a dominant benthic cover scheme where the habitat is characterized by the single most dominant cover type and all habitats are characterized for percent cover of coral. The data and data analyses from Walker and Foster (2009 and 2010) were used to evaluate the accuracy of the reclassified map for Regions Of Interest (ROI) 1 and 2. New data were collected for ROIs 3 and 4 as part of this report. All four regions were combined and analyzed to determine total map accuracy. Data were collected in January 2009 at ROI 1 (eastern Lower Keys), in June 2009 at ROI 2 (western Lower Keys), in September 2012 and February, March, and May 2013 at ROI 3 (back country), and in May 2013 at ROI 4 (Key Largo) (Figure 1). A total of 2029 sampling stations were visited, of which 1969 were used in the accuracy assessment. The sites were selected using a stratified random sampling protocol that equally distributed sampling points amongst the detailed structure categories. Most sites were sampled by deploying a weighted drop camera with the vessel drifting in idle and recording 30-120 seconds of dGPS-referenced video. The shallowest sites were sampled by snorkel, waverunner, or kayak, using a hand-held dGPS for navigation and a housed camera to record video. Each sampling station was given a Detailed Structure, Biological, and Coral Cover assignment in the field. These field classifications were reevaluated post-survey during a systematic review of video and photographic data, designed to ensure consistency within classifications. The efficacy of the benthic habitat map was assessed by a number of classification metrics derived from error matrices of the Major and Detailed levels of Geomorphological Structure and Biological Cover. The overall, producer’s, and user’s accuracies were computed directly from the error matrices. The analyses of the combined ROIs 1 – 4 gave an overall accuracy of the benthic habitat map of 90.4% and 84.6% at the Major and Detailed levels of Structure respectively, and 85.1% and 76.5% at the Major and Detailed levels of cover. The known map proportions, i.e. relative areas of mapped classes, were used to remove the bias introduced to the producer’s and user’s accuracies by differential sampling intensity (points per unit area). The overall accuracy at the Major and Detailed levels of Structure changed to 92.3% and 85.9%. The overall accuracy at the Major and Detailed levels of cover changed to 84.3% and 79%. The overall accuracies were also adjusted to the number of map categories using the Tau coefficient. Tau is a measure of the improvement of the classification scheme over a random assignment of polygons to categories, bounded between -1 (0% overall accuracy for 2 map categories) and 1 (100% accuracy for any number of categories). The Tau coefficients were 0.807 ± 0.026 and 0.829 ± 0.018 at the Major and Detailed levels of Structure, and 0.814 ± 0.020 and 0.745 ± 0.020 at the Major and Detailed levels of cover. Percent coral cover was classified for every polygon, thus coral cover was evaluated separately. Total accuracy for Coral in all habitats for all ROIs was 89.6% and 93.4% after adjusting for map marginal proportions. This calculation, however, was not realistic because it evaluated coral cover in non-coral habitat which inflated the number of correct sites. To account for this, coral cover was also evaluated at only those sites found to be Coral Reef and Hardbottom habitats. Total map accuracy for mapping coral cover on Coral Reef and Hardbottom habitats was 79.8%, and 82.7% after adjusting for habitat proportions. The accuracy varied greatly between the two coral categories present. User’s and Producer’s accuracies for Coral 0% - \u3c10% were near or equal to 90%. Conversely, Coral 10% - \u3c50% user’s and producer’s accuracies were 54.3% and 66.5% respectively. Adjusted producer’s accuracy was reduced to 55.2%. The adjustment for map proportions was very relevant here due to the large disparity of area between the two classes. The map contained 658.5 km² of Coral 0% - \u3c10% and 39.8 km² of Coral 10% -\u3c50%. Further 583 of AA points on Coral Reef and Hardbottom habitat were in Coral 0% - \u3c10% and 219 were in Coral 10% - \u3c50%. Interestingly, there were no mapped polygons of Coral 50% - \u3c90% and 90% - 100%. There was confusion between coral classes where 88 locations mapped as Coral 10% - \u3c50% were actually Coral 0% - \u3c10% and 60 locations mapped as Coral 0% - \u3c10% were found to be Coral 10% - \u3c50%. Confusion between 11 locations that were mapped as Coral 10% - \u3c50% were actually Coral 50% - \u3c90% and 1 location mapped as Coral 10% - \u3c50% was found to be Coral 90% - 100%. These sites were all located in the patch reefs of Hawk Channel. It is unknown if these sites met the minimum mapping unit criteria, but the field data indicated high coral cover at these locations. The relatively low adjusted producer’s accuracy for Coral 10% - \u3c50% (55.2%) suggests that not all higher coral cover areas were captured in the map. Furthermore the relatively low user’s accuracy (54.3%) indicates that the areas of Coral 10% - \u3c50% portrayed in the map are highly variable. Combining all the results into a total map accuracy assessment gave a sense of how the overall map portrays the seascape. However, it should be noted that large gaps in map coverage exist, especially between Marathon and Key Largo, a 137 km stretch. The results given in the appendices are more representative of their specific regions. ROIs 1 and 2 covered most of the lower Keys and their results are a good representation of map accuracy for that region. ROI 3 covered the Backcountry which had higher accuracies, presumably due to a reduced diversity of habitats and lack of coral cover. ROI 4 is a good representation of the upper Keys map accuracy. It is difficult to know which assessment best represents the middle Keys. The landscape is more similar to the upper Keys, but Hawk Channel becomes deeper and more turbid

Development of GIS Maps for Southeast Florida Coral Reefs

The present report outlines the results of an integrated mapping project undertaken to provide habitat maps of the shallow Palm Beach County seafloor between the 6m and 35m contours. This study is a continuation of a similar mapping study undertaken in Broward County, and results were produced such that a seamless and fully compatible mapping product is now available for both counties. The study area stretched from 26.4429o (E. Linton Blvd) in the south to 26.9590o (Jupiter Inlet) in the north. Compatibility with other, in particular NOAA, mapping products was also assured. Data types used in this mapping effort included Laser Airborne Depth Sounder (LADS) bathymetry, and single-beam acoustic seafloor discrimination, as well as ecological assessments and groundtruthing. The method used for acoustic seafloor discrimination was based on the first echo and its associated tail, and on the second echo returns of a 38 kHz and a 420 kHz signal. The survey system employed was an at-source-logging Biosonic transducers and Biosonics recording software. Data analysis used QTC Impact software and a suite of in-house custom-developed algorithms that allowed development of an acoustically-based biomass model for gorgonians, algae and barrel sponges (Xestospongia muta). A series of controlled experiments and field verifications verified that it was possible to acoustically distinguish between different scattering classes correlated to different seafloor types and different biomasses of scattering organisms. Two sets of mapping products were produced. In Phase I, polygons were produced by visual interpretation of LADS bathymetry and input of the acoustic ground discrimination. Phase I maps were based on original habitat definitions by the NOAA biogeography program as previously adapted for the Broward County habitat mapping program. The final map showed a well-developed linear reef complex, which is a continuation of the outer reef of Broward County. Also, the middle reef of Broward County was observed in the southern part of Palm Beach County as a linear reef feature. In the northern area of Palm Beach County, a series of hardground ridges, likely a drowned headland, had no equivalent to any structures observed in the other counties. The majority of the area was covered by sand. Distinctions between linear reef, spur and groove, and colonized pavement were based on benthic cover as suggested by acoustic seafloor discrimination and geomorphology. The outer linear reef was subdivided into four habitats: aggregated patch reef, spur and groove, linear reef and deep colonized pavement. The area east of the outer linear reef consisted of a patchy environment with large patches of reef interspersed amongst the deep sand. These were more prevalent close to the reef and tapered off eastward, becoming more sandy. The spur and groove, linear reef, and deep colonized pavement comprised the outer reef and were separated mainly based on geomorphology. The outer reef was separated from the middle linear reef by a wide sand plane (deep sand). Underwater video drop cameras aided in the refinement of the mapping categories. Accuracy assessment of an independent grid of target points showed the Phase I map to have a Users Accuracy of between 85% and 93% and a Producers Accuracy of 89%. These accuracies compare to NOAA published map accuracies. In Phase II, remote ground discrimination based on 38 and 420 kHz acoustic signals was used to map spatial complexity as well as biomass of indicator taxa (gorgonians, macroalgae, barrel sponges). Biomass models of Phase II had accuracies of 79.6% for gorgonians, 61.7% for macroalgae, and 86.1% for barrel sponges (Xestospongia muta). The biomass model derived from the 420 kHz signals agreed with spatial complexity derived from the 38 kHz E1/E2 parameter. The maps show distinct areas of higher biomass alternating with areas of lower biomass within the same habitats. Biomass frequently, but not always, correlated with acoustically derived spatial complexity, which agreed with diving observations and demonstrates the validity of the acoustic ground discrimination. In conclusion, maps of the Palm Beach County’s submarine habitats, with regards to geomorphological zonation and distribution of benthic biomass of certain indicator groups (gorgonians, algae barrel sponges), were produced that were satisfactorily accurate

Development of GIS Maps for Southeast Florida Coral Reefs

The present report outlines the results of an integrated mapping project undertaken to provide a habitat map of the shallow Broward County seafloor between the 0m and 35m contour. The study area stretched from Golden Beach in northern Dade County to just north of the Palm Beach County line. To produce this map and assure its compatibility with other, in particular NOAA, mapping products, a series of data were integrated. Data types included Laser Airborne Depth Sounder (LADS) bathymetry, multi- and single-beam bathymetry, acoustic seafloor discrimination, ecological assessments, and groundtruthing. The method used for acoustic seafloor discrimination was based on the first echo and its associated tail, and on the second echo returns of a 200 kHz signal. Two survey systems were employed: QTC View and Echoplus. A series of controlled experiments and field verifications indicated that it was possible to distinguish acoustically between different scattering classes that correlated to different seafloor types. For the production of the final map, information obtained from LADS bathymetry, NOAA classification and scattering classes obtained by QTC View and Echoplus was fused. The final map showed three well-developed linear reef complexes, a series of deep and shallow ridges believed to be old shorelines, a large sand area between the middle and outer reefs, and a considerable amount of colonized pavement. Due to the lack of distinct geomorphologic zones, the maps were based solely on habitat as defined by the NOAA biogeography program; however distinctions between areas such as linear reef, spur and groove, and colonized pavement were based on benthic cover (as seen by acoustic seafloor discrimination and biological transects) and geomorphology. The outer linear reef was subdivided into four habitats: aggregated patch reef, spur and groove, linear reef and deep colonized pavement. The area east of the outer linear reef consisted of a very patchy environment with large patches of reef interspersed amongst the deep sand. These were more prevalent close to the reef and tapered off eastward, becoming sandier. The spur and groove, linear reef, and deep colonized pavement comprised the outer reef and were separated mainly based on geomorphology. The outer reef was separated from the middle linear reef by a wide sandy plane (deep sand), which was characterized overall by a different scattering class in QTC View than the shallow sand found inshore. Acoustic ground discrimination identified patches of higher scatter and lower scatter amongst the outer, middle, and inner linear reefs suggesting distinct benthic cover between these structures. The eastern boundary of the middle reef was distinct and easily mapped whereas acoustic discrimination aided in determining the western boundary. The inner reef was the least distinct reef as it is not a mature reef. Much of this reef is patchy growth atop an inshore ridge and reef zonation is absent. Acoustic ground discrimination suggested that patches of higher versus lower scatter existed between and within the linear reefs, indicating that dense fauna is patchily distributed. Shoreward of the inner reef, another sand area or a mixture of sand and colonized pavements were found. Several nearshore ridges were mapped that could be classified as linear reef habitat, but were thought to be of non-reefal origin. Therefore these structures were mapped separately even though similar habitat comprises the inshore ridges, the inner linear reef, and the shallow colonized pavements. Excluded habitats such as submerged vegetation and large rubble zones were not detected sufficiently enough to be mapped during this effort. Groundtruthing by way of underwater video drop cameras and in situ biological assessments aided in the refinement of the mapping categories. Accuracy assessment of an independent grid of target points showed the map to have a users accuracy between 83% and 97% and a producers accuracy between 81% and 95%. These are acceptable accuracies and compare similarly to NOAA published map accuracies. In conclusion, the amalgamation of several mapping approaches and data products provided a representative map of Broward County submarine habitats that was accurate to a very satisfactory level. The results of this survey are a good example of how similar mapping products can be attained through different means. The method employed to map Broward County appears to have equally and accurately illustrated the benthic community as more traditional methods like photo interpretation. Similar methodology should be used in other areas where photo interpretation is not feasible due to either absence of data or the turbidity of the water

Bistability in a simple fluid network due to viscosity contrast

We study the existence of multiple equilibrium states in a simple fluid network using Newtonian fluids and laminar flow. We demonstrate theoretically the presence of hysteresis and bistability, and we confirm these predictions in an experiment using two miscible fluids of different viscosity--sucrose solution and water. Possible applications include bloodflow, microfluidics, and other network flows governed by similar principles

Interpretation of Single-Beam Acoustic Backscatter Using Lidar-Derived Topographic Complexity and Benthic Habitat Classifications in a Coral Reef Environment

Producing thematic coral reef benthic habitat maps from single-beam acoustic backscatter has been hindered by uncertainties in interpreting the acoustic energy parameters E1 (tail of 1st echo) and E2 (complete 2nd echo), typically limiting such maps to sediment classification schemes. In this study, acoustic interpretation was guided by high-resolution lidar (LIght Detection And Ranging) bathymetry. Each acoustic record, acquired from a BioSonics DT-X echosounder and multiplexed 38 and 418 kHz transducers, was paired with a spatially-coincident value of a lidar-derived proxy for topographic complexity, reef-volume (RV), and its membership to one of eight benthic habitat classes, delineated from lidar imagery, ground-truthing, and characterization of epibenthic biota. The discriminatory capabilities of the 38 and 418 kHz signals were generally similar. Individually, the E1 and E2 of both frequencies differentiated between levels of RV and most habitat classes, but could not unambiguously delineate habitats. Plotted in E1:E2 Cartesian space, both frequencies formed two main groupings: uncolonized sand habitats and colonized reefal habitats. E1 and E2 were significantly correlated at both frequencies: positively over sand habitats and negatively over reefal habitats, where the scattering influence of epibenthic biota strengthened the E1:E2 interdependence. However, sufficient independence existed between E1 and E2 to clearly delineate habitats using the multi-echo E1:E2 bottom ratio method. The point-by-point calibration provided by the lidar data was essential for resolving the uncertainties surrounding the factors informing the acoustic parameters in a large, survey-scale dataset. The findings of this study indicate that properly interpreted single-beam acoustic data can be used to thematically categorize coral reef benthic habitats

Comparing the MRI Appearance of the Lymph Nodes and Spleen in Wild-Type and Immuno-Deficient Mouse Strains

The goal of this study was to investigate the normal MRI appearance of lymphoid organs in immuno-competent and immuno-deficient mice commonly used in research. Four mice from each of four different mouse strains (nude, NOG, C57BL/6, CB-17 SCID (SCID)) were imaged weekly for one month. Images were acquired with a 3D balanced steady state free precession (bSSFP) sequence. The volume of the lymph nodes and spleens were measured from MR images. In images of nude and SCID mice, lymph nodes sometimes contained a hyperintense region visible on MRI images. Volumes of the nodes were highly variable in nude mice. Nodes in SCID mice were smaller than in nude or C57Bl/6 mice (p<0.0001). Lymph node volumes changed slightly over time in all strains. The spleens of C57Bl/6 and nude mice were similar in size and appearance. Spleens of SCID and NOG mice were significantly smaller (p<0.0001) and abnormal in appearance. The MRI appearance of the normal lymph nodes and spleen varies considerably in the various mouse strains examined in this study. This is important to recognize in order to avoid the misinterpretation of MRI findings as abnormal when these strains are used in MRI imaging studies

Getting NuSTAR on target: predicting mast motion

The Nuclear Spectroscopic Telescope Array (NuSTAR) is the first focusing high energy (3-79 keV) X-ray observatory operating for four years from low Earth orbit. The X-ray detector arrays are located on the spacecraft bus with the optics modules mounted on a flexible mast of 10.14m length. The motion of the telescope optical axis on the detectors during each observation is measured by a laser metrology system and matches the pre-launch predictions of the thermal flexing of the mast as the spacecraft enters and exits the Earths shadow each orbit. However, an additional motion of the telescope field of view was discovered during observatory commissioning that is associated with the spacecraft attitude control system and an additional flexing of the mast correlated with the Solar aspect angle for the observation. We present the methodology developed to predict where any particular target coordinate will fall on the NuSTAR detectors based on the Solar aspect angle at the scheduled time of an observation. This may be applicable to future observatories that employ optics deployed on extendable masts. The automation of the prediction system has greatly improved observatory operations efficiency and the reliability of observation planning

Quantum Holographic Encoding in a Two-dimensional Electron Gas

The advent of bottom-up atomic manipulation heralded a new horizon for attainable information density, as it allowed a bit of information to be represented by a single atom. The discrete spacing between atoms in condensed matter has thus set a rigid limit on the maximum possible information density. While modern technologies are still far from this scale, all theoretical downscaling of devices terminates at this spatial limit. Here, however, we break this barrier with electronic quantum encoding scaled to subatomic densities. We use atomic manipulation to first construct open nanostructures--"molecular holograms"--which in turn concentrate information into a medium free of lattice constraints: the quantum states of a two-dimensional degenerate Fermi gas of electrons. The information embedded in the holograms is transcoded at even smaller length scales into an atomically uniform area of a copper surface, where it is densely projected into both two spatial degrees of freedom and a third holographic dimension mapped to energy. In analogy to optical volume holography, this requires precise amplitude and phase engineering of electron wavefunctions to assemble pages of information volumetrically. This data is read out by mapping the energy-resolved electron density of states with a scanning tunnelling microscope. As the projection and readout are both extremely near-field, and because we use native quantum states rather than an external beam, we are not limited by lensing or collimation and can create electronically projected objects with features as small as ~0.3 nm. These techniques reach unprecedented densities exceeding 20 bits/nm2 and place tens of bits into a single fermionic state.Comment: Published online 25 January 2009 in Nature Nanotechnology; 12 page manuscript (including 4 figures) + 2 page supplement (including 1 figure); supplementary movie available at http://mota.stanford.ed