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Hurricanes Ian and Nicole caused devastating destruction across Florida in September and November 2022, leaving widespread damage in their wakes. This study focuses on the assessment of barrier islands' shorelines, encompassing natural sand dunes and dune vegetation as well as armored dunes with man-made infrastructure such as seawalls. High-resolution satellite imagery from Planet was used to assess the impacts of these hurricanes on the beach shorelines of Volusia, Flagler, and St. Johns Counties on the Florida Central East Coast. Shorefront vegetation was classified into two classes. Normalized Difference Vegetation Index (NDVI) values were calculated before the hurricanes, one month after Hurricane Ian, one month after Hurricane Nicole, and one-year post landfall. LiDAR (Light Detection and Ranging) was incorporated to calculate vertical changes in the shorelines before and after the hurricanes. The results suggest that natural sand dunes were more resilient as they experienced less impact to vegetation and elevation and more substantial recovery than armored dunes. Moreover, the close timeframe of the storm events suggests a compound effect on the weakened dune systems. This study highlights the importance of understanding natural dune resilience to facilitate future adaptive management efforts because armored dunes may have long-term detrimental effects on hurricane-prone barrier islands. [ABSTRACT FROM AUTHOR]

LIght Detection And Ranging (lidar) data have been widely used in the areas of ecological studies due to lidar's ability to provide information on the vertical structure of vegetation in wildlife habitats. The overall objective of this project was to map the vegetation on No Name Key, Florida where endangered wildlife species reside using publicly available remote sensing data such as lidar data and high resolution aerial images (including National Agricultural Imagery Program (NAIP) images). The methods involved the use of 4 different classification algorithms (Support Vector Machine, Random Forest, Maximum Likelihood, and Mahalanobis Distance), different classification settings (default and custom settings), and normalization (original and normalized input bands) on 2 different input stacked images, NAIP image alone and NAIP combined with lidar data. A majority filter was applied to each classification output before performing the accuracy assessment. The result of performing the image classifications showed the following: across all inputs and classification algorithms, the highest overall accuracy (OA) and kappa coefficient (к) were achieved by the Random Forest classification on the NAIP-lidar stacked image with an applied majority filter and original input bands. The result also showed the airborne data combined with the lidar data resulted in a higher classification accuracy than the airborne data alone; and when normalization was applied to all the input bands or layers, the classification accuracies were not increased in most cases compared to when original bands were used in the classification. In most cases, the application of the majority filter increased the accuracy of the classification results as opposed to when no majority filter was applied. Instead of using default values, when the new parameter values (i.e., custom settings) for the penalty parameter (C) and the gamma (ɤ) were used, the accuracies of the Support Vector Machine (SVM) classified images were slightly increased compared to using the default values for the 2 parameters. With increased availability of public lidar data, combining the aerial image with lidar data would enhance the accuracy of vegetation mapping, which would lead to more effective and accurate wildlife management. [ABSTRACT FROM AUTHOR]

Since the days of film-based cameras tied to balloons, remote sensing of the earth has been a continuing source for technological development. Those early balloons carrying simple cameras soon gave way to motorized aircraft with metric cameras capable of making detailed measurements on the earth's surface. Then, since the mid 1960's, space-based platforms and digital imaging sensors have been the main source of earth-wide data collection. Within the past 20 years, the space-based technology has been miniaturized and deployed on helicopters, piloted aircraft and unmanned aerial vehicles (UAVs), as well as piloted and unpiloted autonomous surface vehicles (UAS) for aquatic and marine measurements. While not exhaustive, this presentation highlights several of most recent innovations in: Interferometric Synthetic Aperture Radar (IfSAR) sensors, Aerial Digital Photogrammetry, Aerial Light Detection and Ranging (lidar), Topobathymetric lidar, and Time and Frequency Domain ElectroMagnetics, and their applications to the GeoSciences in Florida. [ABSTRACT FROM AUTHOR]

Wozencraft, J.; Dunkin, L.; Reif, M., and Eisemann, E., 2018. A spatial index approach to coastal monitoring: A Florida case study. In: Almar, R.; Almeida, L.P.; Trung Viet, N., and Sall, M. (eds.), Tropical Coastal and Estuarine Dynamics. Journal of Coastal Research, Special Issue No. 81, pp. 67–75. Coconut Creek (Florida), ISSN 0749-0208. Light Detection and Ranging (lidar) topography and bathymetry datasets and high-resolution aerial imagery have much to offer, but are typically very large, and efforts to extract information are often ad-hoc, leaving the full potential of high resolution airborne data unrealized. By developing methods for extracting and presenting consistent parameters and metrics applicable across coastal regions in the United States, this crucial information will become more readily available. Here, it is demonstrated how numerous geomorphological, navigation, and structural parameters are extracted from lidar topographic and bathymetric datasets. In addition, environmental parameters are extracted from hyperspectral imagery. Indices are developed from the extracted parameters to provide an evaluation of coastal engineering projects such as dredging and structures condition, as well as environmental projects including mitigation and restoration. A dashboard developed from the indices offers a clear and comprehensive presentation of coastal resource data products. Coastal condition as it relates to geomorphology, navigation infrastructure, and environmental considerations are presented using 'stop-light' symbology, providing a streamlined and easily interpreted illustration for decision making. The indices provide academia, industry, and government with repeatable, comprehensive coastal assessments that are regionally comparable allowing an integrated approach to management and planning in the coastal zone. [ABSTRACT FROM AUTHOR]

Publicly available LiDAR (Light Detection and Ranging) data provide a potential windfall for archaeologists, permitting the creation of detailed topographic site maps with little more than an internet-connected computer and appropriate software. The quality of these LiDAR data for site mapping is variable, however, and may need to be supplemented with data obtained from conventional mapping techniques. We share insights from recent mapping of the Fort Center site (8GL13) in southern Florida. Specifically, we suggest a method-based on trial and error-for integrating LiDAR and total station survey data. We compare the results of our work with previous efforts at mapping the site based solely on conventional archaeological survey methods, as well as with results based on LiDAR data alone. We conclude that our combination of LDAR data, corrected by conventional survey data, produces the most accurate map. [ABSTRACT FROM AUTHOR]

Abstract: Sea turtles nesting beaches are found near-globally, and the ability to characterize beaches by topographic and bathymetric features has remained largely out of reach. Twenty-one beaches and their offshore areas in southern Florida used by three sea turtle species (Caretta caretta, Chelonia mydas, and Dermochelys coriacea) were compared using topographic measures derived from LiDAR data. Variables such as slope, aspect, rugosity, and topographic and bathymetric position indices (TPI and BPI) were extracted from the LiDAR surface raster to characterize beaches used by sea turtles; stepwise multiple regression was used to determine which variables are most strongly associated with turtle nesting density. The three species exhibited tolerances for similar ranges of values in measured variables; beaches with values outside these tolerances were not used for nesting. Beach nesting density can be successfully modeled for all three species, but different topographic measures were important in each model. This work demonstrates the potential of high spatial resolution topographic datasets to successfully characterize coastal habitat for ecological applications. [Copyright &y& Elsevier]

By analyzing a digital elevation model (DEM) derived from airborne light detection and ranging (LIDAR) data and airborne height finder measurements, this study demonstrates that a 1.5 m sea-level rise by 2100 would cause inundation of large areas of Miami-Dade County, southern Broward County, and Everglades National Park. Inundation processes are non-linear: inundation is gradual before reaching a threshold, and speeds up rapidly afterwards due to the regional topography. Accelerated sea-level rise will cause the threshold to be reached sooner by amplifying the non-linear inundation, and must be considered in policy-making. Comparison of inundated areas extracted from 30 m LIDAR and USGS DEMs indicates that the vertical accuracy of a DEM has a great effect on delineation of inundation areas. For a 1.5 m sea-level rise, the inundated area delineated by USGS DEM for Broward County is 1.65 times greater than that indicated by the LIDAR DEM. [ABSTRACT FROM AUTHOR]

The effectiveness of simulating surge inundation using the Eulerian-Lagrangian circulation (ELCIRC) model over multi-scale unstructured grids was examined in this study. The large domain model grid encompasses the western North Atlantic Ocean, the Gulf of Mexico, and the Caribbean Sea to appropriately account for remote and resonance effects during hurricane events and simplify the specification of the open boundary condition. The U.S. East and Gulf Coasts were divided into 12 overlapping basins with fine-resolution (up to 30 × 30 m) grids to model overland surge flooding. These overlapping basins have different fine-resolution grids near the coastal region, but have an identical coarse-resolution grid in the offshore region within the large model domain. Thus, the storm surge prediction can be conducted without reducing computation efficiency by executing multiple model runs with local fine-resolution grids where potential hurricane landfalls may occur. The capability of the multi-scale approach was examined by simulating storm surge caused by Hurricanes Andrew (1992) and Isabel (2003) along the South Florida coast and in the Chesapeake Bay. Comparisons between simulated and observed results suggest that multi-scale models proficiently simulated storm surges in the Biscayne Bay and the Chesapeake Bay during two hurricanes. A series of sensitivity tests demonstrated that the simulation of surge flooding was improved when LiDAR topographic data and special bottom drag coefficient values for mangrove forests were employed. The tests also showed that appropriate representation of linear hydrologic features is important for computing surge inundation in an urban area. [ABSTRACT FROM AUTHOR]

Abstract: During the summer of 2005, Hurricane Dennis overwashed the eastern portion of St. George Island, part of the northwest barrier island chain located along the Florida Panhandle. In this paper, LiDAR-based morphological changes of the barrier island are analyzed, along with the short-term post-storm recovery of secondary dunes. Results show that overwash from the storm surge removed nearly the entire foredune complex, and the initial breaching probably occurred where the complex was either low or discontinuous; in these locations, beach widening was less. In contrast, approximately 10m of beach widening occurred where foredunes were higher and continuous, implying that more sediment was available for seaward transport during storm conditions. The secondary dunes recovered at an average linear rate of 3–4cm per month in the presence of vegetation, although monthly averages varied from −1.5 to 1.4m3/m and total volume changes varied from −17.9 to 16.4m3/m for the duration of the study. Furthermore, vegetation deterred dune migration, thus favoring dune growth and reducing erosion due to wind. In contrast, the absence of vegetation inhibited dune growth. Insignificant changes in elevation occurred in areas of storm debris or lag deposit. Finally, distributions of topographic gradients and curvature calculated numerically from pre- and post-storm LiDAR data are introduced as a potential tool in determining the relative post-storm recovery of the dune field. [Copyright &y& Elsevier]

Measuring individual trees can provide valuable information about forests, and airborne light detection and ranging (LiDAR) sensors have been used recently to identify individual trees and measure structural tree parameters. Past results, however, have been mixed because of reliance on interpolated (image) versions of the LiDAR measurements and search methods that do not adapt to variations in canopies. In this work, an adaptive clustering method is developed using airborne LiDAR data acquired over two distinctly different managed pine forests in North-Central Florida, USA. A crucial issue in isolating individual trees is determining the appropriate size of the moving window (search radius) when locating seed points. The proposed approach works directly on the three-dimensional (3D) 'cloud' of LiDAR points and adapts to irregular canopies sizes. The region growing step yields collectively exhaustive sets in an initial segmentation of tree canopies. An agglomerative clustering step is then used to merge clusters that represent parts of whole canopies using locally varying height distribution. The overall tree detection accuracy achieved is 95.1% with no significant bias. The tree detection enables subsequent estimation of tree height and vertical crown length to an accuracy better than 0.8 and 1.5 m, respectively. [ABSTRACT FROM AUTHOR]

Airborne bathymetric lidar surveys taken in Florida before and after the severe 2004 and 2005 hurricane seasons show infilling of seventeen dredged nearshore borrow pits. During these seasons, groups of pits captured volumes that were the equivalent of up to four years of net longshore transport, even though only one of the seventeen pits studied was inside the presumed depth of closure. Unsurprisingly, dimensionless infilling increased strongly with the ratio of wave height to pit depth. For open coast pits with large alongshore lengths, cross-shore infilling appeared to dominate over longshore infilling but both processes may be of comparable importance in shorter pits. Infilling of three borrow pits adjacent to ebb shoals was found to be considerably larger than on open coasts. Bathymetric changes in borrow pits occurred at greater depths than on nearby undisturbed profiles. Crude estimates of the long term infilling rates from tropical cyclones indicate that annual infilling volumes may be equivalent to more than one quarter of the expected net longshore transport at some locations. However, the episodic nature of hurricanes means that infilling events will be highly irregular. [ABSTRACT FROM AUTHOR]

Reef fish assemblage relationships with in situ and lidar topographic measurements across the seascape were analyzed to evaluate the possibility of using lidar metrics as a proxy for prediction models. In situ topographic complexity (i.e., linear rugosity) was measured from 346 point-count fish surveys spanning the reef seascape. Lidar topographic measurements (i.e., surface rugosity, elevation, and volume) were obtained from a high-resolution lidar bathymetric dataset of each survey's footprint. The survey sites were characterized by an independently derived benthic habitat map. Reef fish abundance and species richness appeared to increase with increasing topographic complexity. Although significant, the relationship was weak. Habitat characterization showed that these relationships changed across the seascape. The relationship between topographic complexity and species richness was more pronounced in shallow habitats, whereas, topographic complexity related more closely to abundance in offshore habitats. In situ rugosity measurement yielded the best explanation of fish assemblage structure parameters, but the weaker lidar metric correlations followed similar trends. Accordingly, lidar-measured topographic complexity may be a useful metric for reef fish distributional models. Such predictive models could have many scientific and management applications including: estimating fish stocks, viewing data trends across the seascape, and designing marine protected areas. However, better understanding of the appropriate spatial scale, measurement scale, and fish operational scale is needed, as well as more research on the dynamics of how reef fishes relate to topographic complexity and other ecological factors influencing distributions across the seascape. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Coral reefs represent one of the most irregular substrates in the marine environment. This roughness or topographic complexity is an important structural characteristic of reef habitats that affects a number of ecological and environmental attributes, including species diversity and water circulation. Little is known about the range of topographic complexity exhibited within a reef or between different reef systems. The objective of this study was to quantify topographic complexity for a 5-km x 5-km reefscape along the northern Florida Keys reef tract, over spatial scales ranging from meters to hundreds of meters. The underlying dataset was a 1-m spatial resolution, digital elevation model constructed from lidar measurements. Topographic complexity was quantified using a fractal algorithm, which provided a multi-scale characterization of reef roughness. The computed fractal dimensions (D) are a measure of substrate irregularity and are bounded between values of 2 and 3. Spatial patterns in D were positively correlated with known reef zonation in the area. Landward regions of the study site contain relatively smooth (D ≈ 2.35) flat-topped patch reefs, which give way to rougher (D ≈ 2.5), deep, knoll-shaped patch reefs. The seaward boundary contains a mixture of substrate features, including discontinuous shelf-edge reefs, and exhibits a corresponding range of roughness values (2.28 ≤ D ≤ 2.61). [ABSTRACT FROM AUTHOR]

Time-frequency techniques to characterize cuspate patterns in light detection and ranging (lidar) data are introduced using examples from the Atlantic coast of Florida, United States. These techniques permit the efficient study of beach face landforms over many kilometers of coastline at multiple spatial scales. From a lidar image, a beach-parallel spatial series is generated. Here, this series is the shore-normal position of a specific elevation (contour line). Well-established time-frequency analysis techniques, wavelet transforms, and S-Transforms, are then applied to the spatial series. These methods yield results entirely compatible with the traditional method of estimating the spacing of cuspate features. In addition, confidence intervals are readily established for the spatial extent and wavelengths of cuspate landforms simultaneously at multiple scales. Examples show this method is useful for capturing transitions in cuspate shapes. With the advent of land-based time-lapse lidar, such techniques should be particularly useful for characterizing the evolution of cuspate landforms and testing models for beach face dynamics. [ABSTRACT FROM AUTHOR]

An automated technique was developed that uses only airborne lidar terrain data to derive the necessary parameters for calculation of effective aerodynamic surface roughness in urban areas. The technique provides parameters for geometric models that have been used over the past 40+ years by automatically deriving the relevant geometry, orientation, and spacing of buildings and trees. In its prototypical form, this technique subsequently calculates an effective surface roughness for 1-km2 parcels of land for each of five geometric models. The user can define several constraints to guide processing based on a priori knowledge of the urban area or lidar data characteristics. Any given wind direction (or range of directions) can be selected to simulate conditions of variable wind flow and the impact on effective surface roughness. The operation, capabilities, and limitations of the technique were demonstrated using lidar terrain data from Broward County, Florida. [ABSTRACT FROM AUTHOR]

A multispectral backscattering LiDAR (Light detection and range) system (hereafter Oculus) was integrated into a wave glider and used to estimate the scattering order (i.e., single vs multiple collisions) of LIDAR backscattering, the water inherent optical properties (IOPs), the biogeo-chemical characteristics of particulate scatterers (i.e., relative size, composition) and their motion) on shelf waters of South East Florida. Oculus has a dual-wavelength configuration (473 and 532 nm) and two detection geometries (off- and on-axis). Characteristics of scatterers were investigated based on two complementary LiDAR-derived proxies (the Structural Dissimilarity Index and the spectral slope of LiDAR backscattering). In March 2017, field measurements showed a covariation between direct and diffuse backscattering contributions during morning hours and away from shore. LiDAR attenuation coefficients explained up to 57% of IOPs variability. The analysis of LiDAR-derived proxies suggested higher turbidity and larger particulates near the coast [ABSTRACT FROM AUTHOR]

Differentiation of continental shelf morphology along the southeast Florida Atlantic coast was based on interpretation of airborne laser bathymetry. The 600-km2 shelf study area, which had a shoreline extent of about 160 km and extended up to 10 km offshore, displayed a diverse range of seafloor morphologies that were characteristic of four main alongshore reaches. Reach I (sand flats and karst topography) in the northern part of the study area is terminated southward by the Bahamas Fracture Zone, a major morphotectonic feature. Reach II (sand flats and coral reefs) is characterized by sand flats with diabathic channel fields leeward or shoreward of the Florida Reef Tract, the seaward margin of which occurs along the shelf break on the upper part of the continental slope. Reach III (sand flats, hardgrounds, and coral reefs) is characterized by extensive nearshore rock outcrops that are exposed as bare rock surfaces on the seafloor or are variously mantled by thin veneers of sand that are not thick enough to disguise the underlying rock structure. Reach IV (tidal sand flats and ridges, hardgrounds, and coral reefs) is dominated by tidal features that notably include fields of tidal sand ridges in the lee of the Florida Reef Tract. The barrier reef on the southeast Florida Atlantic coast, which transitions to Florida Keys shelf environments southward, grades northward to drowned karst topography that is overlain by sand sheets and sand waves. Tidal channels and associated bars, deltas, and shoals occur on the interface between Biscayne Bay and the Atlantic Ocean. This reconnaissance-level characterization of continental shelf environments into morphological reaches in a geographic information system platform provides a basis for quantifying spatial distribution patterns of discrete landform units. [ABSTRACT FROM AUTHOR]

This study compares cirrus-cloud properties and, in particular, particle effective radius retrieved by a Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)-like method with two similar methods using Moderate-Resolution Imaging Spectroradiometer (MODIS), MODIS Airborne Simulator (MAS), and Geostationary Operational Environmental Satellite imagery. The CALIPSO-like method uses lidar measurements coupled with the split-window technique that uses the infrared spectral information contained at the 8.65-, 11.15-, and 12.05-μm bands to infer the microphysical properties of cirrus clouds. The two other methods, using passive remote sensing at visible and infrared wavelengths, are the operational MODIS cloud products (using 20 spectral bands from visible to infrared, referred to by its archival product identifier MOD06 for MODIS Terra) and MODIS retrievals performed by the Clouds and the Earth’s Radiant Energy System (CERES) team at Langley Research Center (LaRC) in support of CERES algorithms (using 0.65-, 3.75-, 10.8-, and 12.05-μm bands); the two algorithms will be referred to as the MOD06 and LaRC methods, respectively. The three techniques are compared at two different latitudes. The midlatitude ice-clouds study uses 16 days of observations at the Palaiseau ground-based site in France [Site Instrumental de Recherche par Télédétection Atmosphérique (SIRTA)], including a ground-based 532-nm lidar and the MODIS overpasses on the Terra platform. The tropical ice-clouds study uses 14 different flight legs of observations collected in Florida during the intensive field experiment known as the Cirrus Regional Study of Tropical Anvils and Cirrus Layers–Florida Area Cirrus Experiment (CRYSTAL-FACE), including the airborne cloud-physics lidar and the MAS. The comparison of the three methods gives consistent results for the particle effective radius and the optical thickness but discrepancies in cloud detection and altitudes. The study confirms the value of an active remote sensing method (CALIPSO like) for the study of subvisible ice clouds, in both the midlatitudes and Tropics. Nevertheless, this method is not reliable in optically very thick tropical ice clouds, because of their particular microphysical properties. [ABSTRACT FROM AUTHOR]

The shape and amplitude of the bathymetric lidar waveforms (the recorded time history of the reflected lidar pulses) contain information about the attenuation of the water and the bottom reflectivity in the survey area. This study considers the factors that affect the amplitude of the bottom return and examines the use of the amplitude of the bottom return to distinguishing between different bottom types. The amplitude of the bottom return was corrected for pulse stretching and retro-reflectance due to the bottom slope based on a simple lidar radiative transfer model before the examination. Within-flightline and between-flightline variations of the bottom return were considered, both of which are related to the attenuation of water, surface wave condition, and bottom reflectivity. The major concern of within-flightline variation is the effect of surface waves on the reliability of bottom return. Between-flightline variation concerns the effect of change in viewing orientation on the bottom return from the same bottom type. A data set of Egmont Key, Florida, assuming homogeneous water clarity, was chosen to investigate the latter two effects on the bottom return signals. The result shows that the presence of surface waves is the most impeding factor that complicates the use of bottom return signal, as it can exaggerate the value (not prominent in our data) and variance of the amplitude of bottom return. A map of sand, continuous seagrass, and discontinuous seagrass ranging from the depth of 0. 8 to 4. 3 m was produced correctly from a single lidar flightline with limited in-situ information, in this case, a nadir viewing videotape concurrent with lidar survey mission. Finally, suggestions are proposed for ways to improve the production of a bottom map using the lidar waveform data. [Copyright &y& Elsevier]

In December 2000 the US National Oceanic and Atmospheric Administration''s Fish Lidar (Light Detection And Ranging) system was operated from an airplane off the west coast of Florida. Schools of fish were located and their volume-backscattering coefficients, β(π), measured at the lidar wavelength of 532 nm. Concurrently, a 208 kHz echosounder was deployed from a small boat to measure the acoustic volume-backscattering coefficients, sv, of the same schools. Seven schools were characterized with both the lidar and the echosounder. The correlation between these seven pairs of β(π) and sv measurements was 0.994. A linear regression of β(π) versus sv had a negative y-intercept, which supports aerial observations of some degree of avoidance reaction of fish to the passing survey boat. The slope was slightly greater than unity, in agreement with previous calculations that the acoustic backscatter of similar fish is slightly greater than the lidar backscatter. The results of this study indicate that lidar is a suitable tool for surveying rapidly the distributions and abundances of epipelagic fish stocks in the shallow waters off the west coast of Florida. Aerial lidar surveys do not have the biases of fish-avoidance reaction potentially affecting acoustic and trawl surveys. [Copyright &y& Elsevier]