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In this paper, a combined model is proposed to predict spare parts inventory in accordance with equipment characteristics and defect elimination records. Fourier series is employed to process the periodicity of the data, autoregressive moving average (ARMA) is used to deal with the linear autocorrelation of the data, and backpropagation (BP) neural network is used to settle the nonlinearity of the data. The prediction results, comparisons, and error analyses show that the combined model is accurate and meets the practical requirements. The combined model not only fully utilizes the information contained in the data but also provides a reasonable decision basis for the procurement of spare parts, making the inventory in a safe state and saving holding costs.

A large variety of high-value substation relay protection equipment occupies a considerable amount of inventory space and capital in electric power companies. To improve this problem, this study proposes an inventory prediction model based on the remaining useful life (RUL) of equipment. The model acquires the RUL data of equipment by using the support vector regression (SVR) algorithm, and then, by taking this data as the main factor and the environmental factors and human factors during the operation of equipment as secondary factors, the model can realize the prediction of relay protection equipment in the substation. At the same time, the nature of the enterprise and the requirements for safety inventory are considered. The comparison of calculation results and error analysis, as well as the calculation time, all indicate that the RUL-based inventory forecasting is the best one. This model not only has high prediction accuracy but also has strong stability and portability. The model can provide a strong decision basis for improving the inventory management of the enterprise, enhancing the resource allocation capability, and formulating the spare parts procurement plan under the condition that the spare parts inventory reaches the safety stock.

Crustal material eastward extrusion from the Tibetan Plateau is closely related to the strike-slip faults in the SE margin of the Tibetan Plateau. The left-lateral strike-slip Xianshuihe–Xiaojiang ...

High Dynamic Range (HDR) Imaging/Video is an important part of the microscopic analysis. In this paper, common methods for obtaining a well-exposed image/video are briefly reviewed, then an alternative method to generate high- quality HDR video in real-time is proposed and compared using general objective metrics for its correct interpretation. The primary application of this implemen- tation is for real-time of non-high speed microscopic inspection systems. Several highly reflective samples are evaluated and compared between this state-of-the-art algorithm and other common methods. Results have shown the success of the de- scribed method. This publication can serve as a baseline for further evaluation and inspection in the field of HDR Microscopy.

Quantification of tidal flat morphological changes at varying timescales is critical from a management point of view. High-resolution tidal flat morphology data, including those for mudflats and salt-marshes, are rare due to monitoring difficulty by traditional methods. Recent advances in Terrestrial Laser Scanner (TLS) technology allow rapid acquisition of high-resolution and large-scale morphological data, but it remains problematic for its application on salt-marshes due to the presence of dense vegetation. In this study, we applied a TLS system to retrieve high-accuracy digital elevation models in a tidal flat of the Yangtze Estuary by using a robust and accurate Progressive Morphological filter (PM) to separate ground and non-ground points. Validations against GPS-supported RTK measurements suggested remarkable performance. In this case the average estimation error was about 0.3 cm, while the Root Mean Square Error (RMSE) was 2.0 cm. We conducted three TLS surveys on the same field including salt-marshes and mudflats at the time points 5 days before, 3 days after, and 45 days after a typhoon event. The retrieved data showed that the mudflats suffered from profound erosion while the salt-marshes slightly accreted during the typhoon period. The average elevation change of the total area was about − 4 cm (− 0.28 cm per day). However, both the mudflats and salt-marshes deposited in the post-typhoon period and the accretion over salt-marshes occurred at a higher rate than that during the typhoon. The elevation of the total area increased by 15.9 cm (0.37 cm per day), suggesting fast recovery under calm conditions. Quantification of the erosion and deposition rates was aided by the high quality TLS data. This study shows the effectiveness of TLS in quantifying morphological changes of tidal flats at an event (and post-event) timescale. The data and analysis also provide sound evidence on vegetation impact in stimulating salt-marsh development and restoration, shedding lights on bio-morphological interactions.

Zhang, K.; Zhang, M.C.; Leatherman, S.B., and Leatherman, S.P., 2020. Rip current hazard analysis. In: Malvarez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 969–973. Coconut Creek (Florida), ISSN 0749-0208.The effect of rip currents on swimmers was analyzed based on the drag force acting on swimmers and the power they need to generate to overcome the drag force. The drag force and power increase quadratically and cubically, respectively, with increase of rip current and swimming speeds. An additional 50% increase in rip current speed above swimmer's speed results in a 125% increase in drag force, requiring a 238% increase in power by the swimmer to overcome the additional drag. Hence, even rip currents of low velocity can be dangerous and swimming against the current should be avoided.

The snake algorithm has been proposed to solve many remote sensing and computer vision problems such as object segmentation, surface reconstruction, and object tracking. This paper introduces a framework for 3-D building model construction from LIDAR data based on the snake algorithm. It consists of nonterrain object identification, building and tree separation, building topology extraction, and adjustment by the snake algorithm. The challenging task in applying the snake algorithm to building topology adjustment is to find the global minima of energy functions derived for 2-D building topology. The traditional snake algorithm uses dynamic programming for computing the global minima of energy functions which is limited to snake problems with 1-D topology (i.e., a contour) and cannot handle problems with 2-D topology. In this paper, we have extended the dynamic programming method to address the snake problems with a 2-D planar topology using a novel graph reduction technique. Given a planar snake, a set of reduction operations is defined and used to simplify the graph of the planar snake into a set of isolated vertices while retaining the minimal energy of the graph. Another challenging task for 3-D building model reconstruction is how to enforce different kinds of geometric constraints during building topology refinement. This framework proposed two energy functions, deviation and direction energy functions, to enforce multiple geometric constraints on 2-D topology refinement naturally and efficiently. To examine the effectiveness of the framework, the framework has been applied on different data sets to construct 3-D building models from airborne LIDAR data. The results demonstrate that the proposed snake algorithm successfully found the global optima in polynomial time for all of the building topologies and generated satisfactory 3-D models for most of the buildings in the study areas.

Airborne Light Detection and Ranging (LIDAR) technology has become the primary method to derive high-resolution Digital Terrain Models (DTMs), which are essential for studying Earth's surface processes, such as flooding and landslides. The critical step in generating a DTM is to separate ground and non-ground measurements in a voluminous point LIDAR dataset, using a filter, because the DTM is created by interpolating ground points. As one of widely used filtering methods, the progressive morphological (PM) filter has the advantages of classifying the LIDAR data at the point level, a linear computational complexity, and preserving the geometric shapes of terrain features. The filter works well in an urban setting with a gentle slope and a mixture of vegetation and buildings. However, the PM filter often removes ground measurements incorrectly at the topographic high area, along with large sizes of non-ground objects, because it uses a constant threshold slope, resulting in "cut-off" errors. A novel cluster analysis method was developed in this study and incorporated into the PM filter to prevent the removal of the ground measurements at topographic highs. Furthermore, to obtain the optimal filtering results for an area with undulating terrain, a trend analysis method was developed to adaptively estimate the slope-related thresholds of the PM filter based on changes of topographic slopes and the characteristics of non-terrain objects. The comparison of the PM and generalized adaptive PM (GAPM) filters for selected study areas indicates that the GAPM filter preserves the most "cut-off" points removed incorrectly by the PM filter. The application of the GAPM filter to seven ISPRS benchmark datasets shows that the GAPM filter reduces the filtering error by 20% on average, compared with the method used by the popular commercial software TerraScan. The combination of the cluster method, adaptive trend analysis, and the PM filter allows users without much experience in processing LIDAR data to effectively and efficiently identify ground measurements for the complex terrains in a large LIDAR data set. The GAPM filter is highly automatic and requires little human input. Therefore, it can significantly reduce the effort of manually processing voluminous LIDAR measurements.

Fingolimod (FTY720), an immunomodulator, is approved as an oral treatment for patients with relapsing forms of multiple sclerosis. Its effects are largely attributed to its mechanism of selectively retaining lymphocytes in the lymph nodes to reduce autoreactive T-cell recruitment in the CNS. In this study, we investigated the therapeutic effect of FTY720 on an animal model of CNS inflammation induced by intracerebral ventricle LPS injection. We found that FTY720 treatment significantly prevented LPS-induced neutrophil recruitment in the CNS by inhibiting leukocyte recruitment in cerebral microvessels. Furthermore, FTY720 also inhibited the expressions of adhesion molecules on the cerebral endothelium, but did not affect the expression levels of pro-inflammatory cytokines (TNF-α and IL-6) and chemokines (CXCL1 and CXCL2) in the CNS parenchyma. The inhibition of endothelial activation was accompanied by reduced phosphorylation of signaling molecules, including serine/threonine-specific protein kinase (Akt), STAT6, and nuclear factor-κB. This FTY720-attenuated inhibition of leukocyte recruitment and endothelial activation was reversed by blocking the functions of sphingosine kinase 2 or sphingosine-1-phosphate receptor 1. Our study demonstrated, for the first time, that FTY720 directly inhibits the phosphorylation of multiple signaling molecules in endothelial cells, thereby effectively blocking leukocyte recruitment in the CNS.

The operational forecast demands and constraints of the National Hurricane Center require that a storm surge model in research mode be tested against a benchmark model such as Sea, Lake, and Overland Surges from Hurricanes (SLOSH) for accuracy, computation time, and numerical stability before the model is used for operational forecasts. Additionally, the simulated results must be in a geographic information system format to facilitate the usage of computed storm surge for various applications. This paper presents results from a demonstration project to explore the pathway for the transition of the Coastal and Estuarine Storm Tide (CEST) model to an operational forecast model by testing CEST over SLOSH basins in Florida. The performance and stability of CEST were examined by conducting simulations for Hurricane Andrew (1992) and more than 100 000 synthetic hurricanes for nine SLOSH basins covering the Florida coast and Lake Okeechobee. The results show that CEST produces peak surge heights similar to those from SLOSH. Additionally, CEST has proven to be numerically stable against all synthetic hurricanes and the computation time of CEST is comparable to that of SLOSH. Therefore, CEST has the potential to be used for operational forecasts of storm surge. The potential of producing more detailed real-time surge inundation forecasts was also investigated through the simulations of Andrew's surge on various grids with different cell sizes. The results indicate that CEST can produce 48-h forecasts using a single processor in about 40 min over a grid generated by reducing the cell edge size of the SLOSH grid by 4 times.

Two linear methods, including the simple linear addition and linear addition by expansion, and numerical simulations were employed to estimate storm surges and associated flooding caused by Hurricane Andrew for scenarios of sea level rise (SLR) from 0.15 m to 1.05 m with an interval of 0.15 m. The interaction between storm surge and SLR is almost linear at the open Atlantic Ocean outside Biscayne Bay, with slight reduction in peak storm surge heights as sea level rises. The nonlinear interaction between storm surges and SLR is weak in Biscayne Bay, leading to small differences in peak storm surge heights estimated by three methods. Therefore, it is appropriate to estimate elevated storm surges caused by SLR in these areas by adding the SLR magnitude to storm surge heights. However, the magnitude and extent of inundation at the mainland area by Biscayne Bay estimated by numerical simulations are, respectively, 22–24 % and 16–30 % larger on average than those generated by the linear addition by expansion and the simple linear addition methods, indicating a strong nonlinear interaction between storm surge and SLR. The population and property affected by the storm surge inundation estimated by numerical simulations differ up to 50–140 % from that estimated by two linear addition methods. Therefore, it is inappropriate to estimate the exacerbated magnitude and extent of storm surge flooding and affected population and property caused by SLR by using the linear addition methods. The strong nonlinear interaction between surge flooding and SLR at a specific location occurs at the initial stage of SLR when the water depth under an elevated sea level is less than 0.7 m, while the interaction becomes linear as the depth exceeds 0.7 m.

The distribution of mangrove biomass and forest structure along Shark River estuary in the Florida Coastal Everglades (FCE) has been correlated with elevated total phosphorus concentration in soils thought to be associated with storm events. The passage of Hurricane Wilma across Shark River estuary in 2005 allowed us to quantify sediment deposition and nutrient inputs in FCE mangrove forests associated with this storm event and to evaluate whether these pulsing events are sufficient to regulate nutrient biogeochemistry in mangrove forests of south Florida. We sampled the spatial pattern of sediment deposits and their chemical properties in mangrove forests along FCE sites in December 2005 and October 2006. The thickness (0.5 to 4.5 cm) of hurricane sediment deposits decreased with distance inland at each site. Bulk density, organic matter content, total nitrogen (N) and phosphorus (P) concentrations, and inorganic and organic P pools of hurricane sediment deposits differed from surface (0–10 cm) mangrove soils at each site. Vertical accretion resulting from this hurricane event was eight to 17 times greater than the annual accretion rate (0.30 ± 0.03 cm year−1) averaged over the last 50 years. Total P inputs from storm-derived sediments were equivalent to twice the average surface soil nutrient P density (0.19 mg cm−3). In contrast, total N inputs contributed 0.8 times the average soil nutrient N density (2.8 mg cm−3). Allochthonous mineral inputs from Hurricane Wilma represent a significant source of sediment to soil vertical accretion rates and nutrient resources in mangroves of southwestern Everglades. The gradient in total P deposition to mangrove soils from west to east direction across the FCE associated with this storm event is particularly significant to forest development due to the P-limited condition of this carbonate ecosystem. This source of P may be an important adaptation of mangrove forests in the Caribbean region to projected impacts of sea-level rise.

Sea-level rise presents an imminent threat to freshwater-dependent ecosystems on small oceanic islands, which often harbor rare and endemic taxa. Conservation of these assemblages is complicated by feedbacks between sea level and recurring pulse disturbances (eg hurricanes, fire). Once sea level reaches a critical level, the transition from a landscape characterized by mesophytic upland forests and freshwater wetlands to one dominated by mangroves can occur suddenly, following a single storm-surge event. We document such a trajectory, unfolding today in the Florida Keys. With sea level projected to rise substantially during the next century, ex-situ actions may be needed to conserve individual species of special concern. However, within existing public conservation units, managers have a responsibility to conserve extant biodiversity. We propose a strategy that combines the identification and intensive management of the most defensible core sites within a broader reserve system, in which refugia for biota facing local extirpation may be sought.

The Coastal and Estuarine Storm Tide (CEST) model for the boundary-fitted curvilinear grid has been developed recently to simulate a hurricane-induced storm surge. A new wetting-drying algorithm was based on accumulated volume and was created for simulating overland flooding. To evaluate the capability of the CEST model, it was compared with the well-established storm surge model—Sea, Lake, and Overland Surge from Hurricane (SLOSH)—in model grid representation and surge inundation prediction. Two models were compared: first, by carrying out storm surge simulations for Hurricanes Andrew (1992), Hugo (1989), and Camille (1969) over SLOSH's coarse polar grids with cell sizes of 500–7000 m. Results show that the CEST model agreed better with field observations of storm surge flooding. The CEST model was further evaluated by applying it to a fine-resolution curvilinear grid, which has cell sizes of 100–200 m at the hurricane landfall area, along with a superior representation of coastal topography. Co...

Nutrient loading and eutrophication in coastal waters are the causes of water quality degradation and loss of marine biota, which has led to ecological imbalance. Understanding and modeling the level of eutrophication as a function of environmental parameters can be beneficial to coastal ecosystem management. The limitation of deterministic and empirical models in accurately predicting the level of algal blooms, and the nonlinear relationship between the water quality and environmental parameters and that of the level of chlorophyll a necessitate a new approach using machine learning and data-driven modeling. A multilayer perceptron-back propagation (MLP-BP) algorithm of artificial neural network (ANN) was used to predict the level of eutrophication (chlorophyll a) from water quality parameters monitored at two Florida Bay water quality monitoring stations (FLAB03 and FLAB14). Based on the correlation of monthly nutrients (total phosphate, nitrite, ammonium) and other water data (temperature, tur...

Accuracy of predicting storm surge inundation depends on the model grid resolution. The spatial resolutions of many storm surge models are on the order of hundreds of meters to kilometers, which are not sufficient to resolve irregular shorelines and small topographic features. In this paper, storm surge and inundation simulation for Hurricane Andrew of 1992 was carried out with the unstructured tidal, residual, intertidal mudflat (UnTRIM) hydrodynamic model. A high-resolution unstructured grid with cell sizes as small as 20 m was placed over the Key Biscayne Bay area near Miami to better represent irregular shorelines and small morphological features such as barrier islands, rivers, canals, and inlets. A series of experiments was conducted to test model performance with respect to model grid resolution, time step selection, open boundary condition specification, and tidal influence. Results show that the model simulated maximum surge heights and areas of inundation along the Biscayne Bay coast ve...

This paper presents a framework that applies a series of algorithms to automatically extract building footprints from airborne light detection and ranging (LIDAR) measurements. In the proposed framework, the ground and nonground LIDAR measurements are first separated using a progressive morphological filter. Then, building measurements are identified from nonground measurements using a region-growing algorithm based on the plane-fitting technique. Finally, raw footprints for segmented building measurements are derived by connecting boundary points, and the raw footprints are further simplified and adjusted to remove noise caused by irregularly spaced LIDAR measurements. Data sets from urbanized areas including large institutional, commercial, and small residential buildings were employed to test the proposed framework. A quantitative analysis showed that the total of omission and commission errors for extracted footprints for both institutional and residential areas was about 12%. The results demonstrated that the proposed framework identified building footprints well

We produced a landscape scale map of mean tree height in mangrove forests in Everglades National Park (ENP) using the elevation data from the Shuttle Radar Topography Mission (SRTM). The SRTM data was calibrated using airborne lidar data and a high resolution USGS digital elevation model (DEM). The resulting mangrove height map has a mean tree height error of 2.0 m (RMSE) over a pixel of 30 m. In addition, we used field data to derive a relationship between mean forest stand height and biomass in order to map the spatial distribution of standing biomass of mangroves for the entire National Park. The estimation showed that most of the mangrove standing biomass in the ENP resides in intermediate-height mangrove stands around 8 m. We estimated the total mangrove standing biomass in ENP to be 5.6 � 10 9 kg.

This paper compares three methods for removing non-ground measurements from airborne laser scanning data. These methods, including the elevation threshold with expanding window (ETEW), maximum local slope (MLS), and progressive morphological (PM) filters, analyze data points based on variations of local slope, and elevation. Low and high-relief data sets with various densities of trees, houses, and sand dunes were selected to test the filtering methods. The results show that all three methods can effectively remove most nonground points in both low-relief urban and high-relief forested areas. The PM filter generated the best result in coastal barrier island areas, whereas the other algorithms tended to remove the tops of steep sand dunes. Each method experienced various omission or commission errors, depending on the filtering parameters. Topographic slope is the most sensitive parameter for the three filtering methods.

Quantitative data on beach changes caused by coastal storms is critical to the understanding of coastal morphodynamics and mitigation of coastal erosion hazards. Recent advances in airborne LIDAR technology allow large-scale mapping of beach erosion, dune scarping, and overwash deposition with incredible detail. By comparing 40 km of beaches along the central Florida Atlantic coast surveyed before and after Hurricane Floyd in 1999, we found that most beaches experienced erosion; about −18 to +1 m3/m of sediment per unit shoreline length were removed or deposited. Beach erosion is not spatially uniform, and variations in magnitude occur three dimensionally. The high-density LIDAR data provided accurate information about shore changes both at small and large scales.

This paper examines the feasibility of using LIDAR surveys to update existing historical shoreline data sets by comparing contour shorelines and the high water line (HWL) at eight study locations in North and South Carolina. The analysis was based on airborne LIDAR topography and orthoimagery collected simultaneously during June 2000. The popular method of digitizing the wet-dry line from orthoimagery was used to measure the HWL. Contour shorelines were derived by using the previous high tide (HW), the mean high water datum (MHW), and the mean higher high water datum (MHHW) of nearby tide gauges. A method was developed to quantitatively compare the positions of the HWL and the contour shorelines in a GIS. The mean high water and mean higher high water contour shoreline positions were the best match to the high water line at 7 of 8 locations, and differed by less than 5.4 meters from the digitized high water line positions. This difference is well within the errors associated with past methods for measuring shoreline position. Therefore, it is deemed practical to use LIDAR data to estimate the HWL.

Recent advances in airborne light detection and ranging (LIDAR) technology allow rapid and inexpensive measurements of topography over large areas. This technology is becoming a primary method for generating high-resolution digital terrain models (DTMs) that are essential to numerous applications such as flood modeling and landslide prediction. Airborne LIDAR systems usually return a three-dimensional cloud of point measurements from reflective objects scanned by the laser beneath the flight path. In order to generate a DTM, measurements from nonground features such as buildings, vehicles, and vegetation have to be classified and removed. In this paper, a progressive morphological filter was developed to detect nonground LIDAR measurements. By gradually increasing the window size of the filter and using elevation difference thresholds, the measurements of vehicles, vegetation, and buildings are removed, while ground data are preserved. Datasets from mountainous and flat urbanized areas were selected to test the progressive morphological filter. The results show that the filter can remove most of the nonground points effectively.

In a few hours or days, scores of meters of beach width can be lost due to a severe storm. However, newly available shoreline data from the U.S. East Coast show that beaches recover after storms to positions consistent with their long‐term (100+ yr) trend. Even the largest storms, such as the Ash Wednesday Storm of 1962, considered to be the most damaging in the twentieth century, appear to have had little effect on the long‐term trend. The gradual recession of beaches along the U.S. East Coast is mainly controlled by other factors such as sea‐level rise and variations of sediment supply. Therefore, it follows that barrier beaches in a coastal plain setting would not experience long‐term erosion in response to storm impact if the sea were to stop rising and sediment supply did not change.

High quality DEM (Digital Elevation Model) is indispensable for a smart city nowadays. A large quantity of useful spatial information can be extracted from the big data acquired by surveying, imaging, and even mobile device with GPS system. This information is critical to many applications such as urban management, emergency event planning, and social location services. The extraction of non-ground features such as buildings, constructions and vegetation can be used to generate accurate boundary shape and three dimensional models. These outcomes can be utilized to provide useful information for the location service for mobile social networks. The DEM can be generated by surveying the area. LIDAR (Light Detection and Ranging) is a widely used remote sensing technology to survey the urban area. High resolution three dimensional data can be acquired from the LIDAR survey. How to separate the terrain surface and non-terrain features from three dimensional spatial data is the most challenging task for generating high quality DEM. In this paper, a multi-pass morphological filter is proposed to generate better DEMs on complex urban areas that have difficulties to use large filtering window sizes. Multi-pass filtering will use relatively small filtering window sizes in multiple rounds to avoid the cut-off problem commonly present when large window sizes are used in filtering. A priority boundary interpolation method is proposed and dedicated to interpolate the intermediate filtering result between each pass. A second pass of the morphological filter will use filtering window sizes in descending order to remove the remaining areas from large non-ground objects that cannot be removed with small window sizes. The filtering results demonstrate that the proposed method is able to effectively use relatively small filtering windows to filter large non-ground objects on complex terrains and avoid the cut-off problem.

It has been speculated that future global warming will change the frequency and severity of tropical and extratropical storms. The U.S. east coast is heavily impacted by such storms, so it is important to determine their natural temporal variability for the last century during which global warming has been relatively small. Storm surge data obtained from hourly tide gauge records provide a unique quantitative measure of storm duration and intensity, unlike qualitative estimates based on eyewitness reports or meteorological hindcasts. To demonstrate the potential of storm surge data for climate analysis, the authors have evaluated 10 very long records of water level anomalies. An analysis of the hourly tide gauge records along the U.S. east coast shows a considerable interdecadal variation but no discernible long-term trend in the number and intensity of moderate and severe coastal storms during this century. However, sea level rise over the last century has exacerbated the damage to fixed structu...

A numerical model for the prediction of storm surges over complex landscapes is assembled using state-of-the-art techniques. The model is based on the full nonlinear depth-averaged long wave equations solved via an explicit finite volume scheme. The interfacial fluxes are computed from slope limited reconstructions of the state variables using Osher’s approximate Riemann solver. The geometric source terms are treated in a simple manner that is well balanced and consistent with the numerical flux. The numerical solution technique has been chosen to enable the accurate simulation of flows over complex topography. Importantly, the scheme conserves both mass and momentum even when the flow involves wetting–drying fronts. This approach makes the model extremely robust in cases that involve bathymetries which include large spatial gradients and even discontinuities. Another important feature of the model is the use of a simple underlying Cartesian mesh with quad-tree-based static and dynamic refinement. This permits the simulation of highly unsteady flows over complex landscapes (including localized features such as canals) by locally increasing (or relaxing) grid resolution in a dynamic fashion. If it is deemed desirable, the numerical and physical boundaries can be aligned. This alignment is achieved by a cut-cell-type approach in combination with quad-tree-based mesh refinement. In this paper, we describe the model and then present a number of tests that have been carefully chosen to verify various aspects of the solution algorithm.

This paper presents a 3D traffic animation system that provides features of vehicle interaction and storm surge response to emulate realistic scenarios in a hurricane affected area. The proposed system constructs road objects based on a series of line segments. Vehicles on the roads are animated by keeping them coherent with the direction of the road segment and adjusting their speeds with respect to one another. The vehicle speed is controlled based upon a collision-circumventing policy and they automatically respond to flood water caused by a storm surge. The system can automatically plant lamp posts along the roads, which also respond to surge flooding. An implementation conducted with the 3D scenes on a couple of south Florida's surge-susceptible areas demonstrates the system's excellence in animating real traffic scenes and impacts of storm surge on coastal regions.

Airborne light detection and ranging (LIDAR) measurements derived before and after Hurricanes Katrina and Wilma (2005) were used to quantify the impact of hurricanes and lightning strikes on the mangrove forest at two sites in Everglades National Park (ENP). Analysis of LIDAR measurements covering 61 and 68 ha areas of mangrove forest at the Shark River and Broad River sites showed that the proportion of high tree canopy detected by the LIDAR after the 2005 hurricane season decreased significantly due to defoliation and breakage of branches and trunks, while the proportion of low canopy and the ground increased drastically. Tall mangrove forests distant from tidal creeks suffered more damage than lower mangrove forests adjacent to the tidal creeks. The hurricanes created numerous canopy gaps, and the number of gaps per square kilometer increased from about 400~500 to 4000 after Katrina and Wilma. The total area of gaps in the forest increased from about 1~2% of the total forest area to 12%. The relative contribution of hurricanes to mangrove forest disturbance in ENP is at least 2 times more than that from lightning strikes. However, hurricanes and lightning strikes disturb the mangrove forest in a related way. Most seedlings in lightning gaps survived the hurricane impact due to the protection of trees surrounding the gaps, and therefore provide an important resource for forest recovery after the hurricane. This research demonstrated that LIDAR is an effective remote sensing tool to quantify the effects of disturbances such as hurricanes and lightning strikes in the mangrove forest.

This paper illustrates branch breaking and flying effect animation for trees in our 3D interactive visualization system for hurricanes and storm surge flooding. The tree branch breaking and flying effect animation extends our current tree animation framework by estimating the destination quadrant, direction (angle) and traveling speed with which a branch breaks and flies across the terrain. These calculations thus assist in simulating the potential threats to property and human lives posed by the flying branches during a hurricane, and add to the realism and appeal of our system. We utilize 3D tree models created with 3DSmax and implement the animation effects via OpenGL and nVidia CG shader language.

Energy-minimizing active contour models (snakes) have been proposed for solving many computer vision problems such as object segmentation, surface reconstruction, and object tracking. Dynamic programming which allows natural enforcement of constraints is an effective method for computing the global minima of energy functions. However, this method is only limited to snake problems with one dimensional (ID) topology (i.e., a contour) and cannot handle problems with two-dimensional (2D) topology. In this paper, we have extended the dynamic programming method to address the snake problems with 2D topology using a novel graph reduction algorithm. Given a 2D snake with first order energy terms, a set of reduction operations are defined and used to simplify the graph of the 2D snake into one single vertex while retaining the minimal energy of the snake. The proposed algorithm has a polynomial-time complexity bound and the optimality of the solution for a reducible 2D snake is guaranteed. However, not all types of 2D snakes can be reduced into one single vertex using the proposed algorithm. The reduction of general planar snakes is an NP-complete problem. The proposed method has been applied to optimize 2D building topology extracted from airborne LIDAR data to examine the effectiveness of the algorithm. The results demonstrate that the proposed approach successfully found the global optima for over 98% of building topology in a polynomial time.

This paper describes an implementation of vertex weighting for real-time animation of 3D trees as a result of wind force and direction. This method improves over similar techniques because it incorporates individual branch animation on 3D models, whereas previous works perform animations on the model as a whole or use planar billboards to visualize the tree. Our tree animation is used in an interactive system that visualizes the effects caused by a hurricane's impact on a virtual city. The system uses models created with 3D Studio Max and the animations are implemented in OpenGL and the nVidia Cg shader language

We present a damage pattern mining framework for hurricane data on residential houses using aerial photographs with 1:3000 based scale. The vertical photographs are normally collected for an overview of a disaster area or for more detailed assessment. Damage on roof, especially for shingles torn off, is expected to be discovered in a more efficient and automatic way instead of going through the high-resolution aerial photograph for numerous details. The discovered damage patterns can then be used for hurricane damage assessment and impacts on different geographical areas. Our methodology is: (1) applying a novel and effective segmentation method on each residential house on the aerial photograph of one community, (2) using the segmentation results to obtain a set of indexing parameters for each house representing the damage level of roof cladding as well as the patterns of damage, (3) using these parameters to select several templates representing the damage patterns so that users can issue query-by-example (QBE) queries. The proposed segmentation method is an unsupervised simultaneous partition and class parameter estimation algorithm that considers the problem of segmentation as a joint estimation of the partition and class parameter variables. By utilizing this segmentation method, the indexing parameters can be obtained automatically. The QBE capability can assist in finding similar damage patterns on the roof of the residential houses in different locations in the image databases. Experiments based on the aerial photographs of Hurricane Andrew in 1992 are conducted and analyzed to show the effectiveness of the proposed hurricane damage pattern mining framework.

This paper describes an approach to develop a high performance animation environment for storm surge. The system provides the capability to simulate the storm surge effects in the physical world by (1) modeling a region using the airborne light detection and ranging (LIDAR) data, USGS orthophotos, RLG road data and photos; (2) animating the storm impact by using the features of this model; and (3) providing the capability for users to explore the animation environment. We present our system by modeling the dataset collected from Ft. Lauderdale, a region in South Florida, USA.

Theoretical analysis is made for thin-film-based, 200- and 100-GHz narrow bandpass filters with respect to the intensity response as well as to the chromatic dispersion. The results indicate that the narrower the passband, the higher the chromatic dispersion. The maximum chromatic dispersion appears at the edges of the 0.5-dB passband, owing to the fast change of the group delay in the region. The deviation of chromatic dispersion induced by manufacturing error is simulated. Effective-medium approximation layers are added to simulate the contribution of surface roughness and the mixture interfaces to the passband ripple as well as the chromatic dispersion. The simulations are compared with the experimental results. The measured chromatic dispersion matches the general trend of the theoretical calculation. The imperfect surface and layer mismatch induce additional ripples across the 0.5-dB passband. The maximum chromatic dispersion within a 0.5-dB passband is 20.7 and 54.9 ps/nm for 200- and 100-GHZ narrow bandpass filters, respectively.