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Phragmites australis (common reed) commonly found in the coastal wetlands can rapidly alter the ecology of these systems by outcompeting native plant species for resources. Identifying and mapping Phragmites can help resource managers to restore affected wetlands. In this work, we use probabilistic neural network with wavelet texture features for mapping regions with Phragmites in visible spectrum...
Plant species monitoring in wetland ecosystems is crucial for preservation of water quality and many other ecological functions. Difficulties associated with conducting field work (i.e., hazardous terrain) can affect the ability of resource managers to correctly identify wetland plant species in a timely fashion. Thus, in wetland sites where access can be difficult, differentiation of plant species...
Hyperspectral imagery provides detailed information about land-cover materials over a wide spectral range. Land-cover classification using hyperspectral data has been an active topic of research. Elevation data from light detection and ranging (LiDAR) can aid the classification process in discriminating complex classes. Fusion of hyperspectral and LiDAR data has been investigated in the past where...
Displaying the abundant information contained in a remotely sensed hyperspectral image is a challenging problem. Currently no approach can satisfactorily render the desired information at arbitrary levels of detail. This chapter discusses user studies on several approaches for representing the information contained in hyperspectral information. In particular, we compared four visualization methods:...
Geometrical modeling is a crucial aspect of simulations involving manufactured objects and is usually performed using free-form surfaces. However, to simulate the flow through or about a manufactured object or to simulate structural integrity, the free-form surfaces must be tessellated into triangulated surfaces. To concurrently visualize the simulation results and the quality of the surfaces, we...
The Navy Research Laboratory's Coastal Ocean Model (NCOM) is a realistic, large-scene simulation that runs daily and generates massive amounts of data. The data must be analyzed and/or reduced to provide pertinent information. This may be achieved through data mining by performing feature detection and/or region-of-interest detection. Data reduction using data mining techniques is not a new idea,...
This paper presents an advanced evenly-spaced streamline placement algorithm for fast, high-quality, and robust layout of flow lines. A fourth-order Runge-Kutta integrator with adaptive step size and error control is employed for rapid accurate streamline advection. Cubic Hermite polynomial interpolation with large sample-spacing is adopted to create fewer evenly-spaced samples along each streamline...
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