Browsing by Subject "LIDAR"
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Item 3D Multi-Field Multi-Scale Features From Range Data In Spacecraft Proximity Operations(2012-07-16) Flewelling, Brien RoyA fundamental problem in spacecraft proximity operations is the determination of the 6 degree of freedom relative navigation solution between the observer reference frame and a reference frame tied to a proximal body. For the most unconstrained case, the proximal body may be uncontrolled, and the observer spacecraft has no a priori information on the body. A spacecraft in this scenario must simultaneously map the generally poorly known body being observed, and safely navigate relative to it. Simultaneous localization and mapping(SLAM)is a difficult problem which has been the focus of research in recent years. The most promising approaches extract local features in 2D or 3D measurements and track them in subsequent observations by means of matching a descriptor. These methods exist for both active sensors such as Light Detection and Ranging(LIDAR) or laser RADAR(LADAR), and passive sensors such as CCD and CMOS camera systems. This dissertation presents a method for fusing time of flight(ToF) range data inherent to scanning LIDAR systems with the passive light field measurements of optical systems, extracting features which exploit information from each sensor, and solving the unique SLAM problem inherent to spacecraft proximity operations. Scale Space analysis is extended to unstructured 3D point clouds by means of an approximation to the Laplace Beltrami operator which computes the scale space on a manifold embedded in 3D object space using Gaussian convolutions based on a geodesic distance weighting. The construction of the scale space is shown to be equivalent to both the application of the diffusion equation to the surface data, as well as the surface evolution process which results from mean curvature flow. Geometric features are localized in regions of high spatial curvature or large diffusion displacements at multiple scales. The extracted interest points are associated with a local multi-field descriptor constructed from measured data in the object space. Defining features in object space instead of image space is shown to bean important step making the simultaneous consideration of co-registered texture and the associated geometry possible. These descriptors known as Multi-Field Diffusion Flow Signatures encode the shape, and multi-texture information of local neighborhoods in textured range data. Multi-Field Diffusion Flow Signatures display utility in difficult space scenarios including high contrast and saturating lighting conditions, bland and repeating textures, as well as non-Lambertian surfaces. The effectiveness and utility of Multi-Field Multi-Scale(MFMS) Features described by Multi-Field Diffusion Flow Signatures is evaluated using real data from proximity operation experiments performed at the Land Air and Space Robotics(LASR) Laboratory at Texas A&M University.Item Environmental Processes, Social Perspectives and Economic Valuations of the Coast(2011-10-21) Williams, Amy M.Coastal ecosystems provide important resources for social, economic and environmental capital to global and local communities. Socially, coastal ecosystems provide a place for people to recreate and get in touch with nature. Economically, tourism, fisheries, and businesses are dependent upon coastal resources. Environmentally, coasts provide habitat for diverse species of flora and fauna, and protection for watersheds and anthropogenic structures. This research investigates three studies in order to provide information on social, economic and environmental issues in Matagorda, Texas. The first study uses LIDAR (Light Image Detection-and-Ranging) scanning, a remote sensing methodology that uses laser pulses to collect X, Y, and Z coordinates, to evaluate coastal changes after Hurricane Ike. Results suggest that landscape loss occurs immediately after the hurricane, but recovers and fluctuates throughout the year. Also, different areas of the dunes show unique changes during different times of the year. The second study uses questionnaire surveys to collect demographic, social perspectives and opinions and economic information about coastal users on Matagorda Peninsula. The questionnaire investigates the most important characteristics to beach users, opinions and perceptions about beach safety, activities, maintenance and presence of seaweed, information about their trip, cost of their trip and demographics. The results provide broader knowledge about the beach users in Matagorda and indicate that while direct costs of using the beach are minimal, the indirect and intrinsic costs are much higher which result in a greater overall use value. The third study investigates the use of the sargassum, a natural marine subsidy, as a fertilizer for dune plants. Beach raking provides a cleaner, more aesthetically pleasing experience for beach users but alters the natural design of the ecosystem by subsequently moving sand, nutrients, subsidies for habitat and fauna from the fore-beach to the dunes. Results show that sargassum does have potential as a natural fertilizer as it did not negatively affect any of the species. The results could be used to alter management practices in order to capitalize on this natural resource while still providing a clean sandy beach for recreationalists. These three studies together provide ecological information about coastal functions and processes that can help in creating broad holistic science based management strategies.Item Exploring the relationships between vegetation measurements and temperature in residential areas by integrating LIDAR and remotely sensed imagery(Texas A&M University, 2006-10-30) Clemonds, Matthew APopulation growth and urban sprawl have contributed to the formation of significant urban heat island phenomena in Houston, Texas, the fourth largest city in the United States. The population growth in Houston was 25.8% between 1990 and 2000 nearly double the national average. The demand for information concerning the effects of urban and suburban development is growing. Houston is currently the only major US city lacking any kind of comprehensive city zoning ordinances. The Normalized Difference Vegetation Index (NDVI) has been used as a surrogate variable to estimate land surface temperatures at higher spatial resolutions, given the fact that a high-resolution remotely sensed NDVI can be created almost effortlessly and remotely sensed thermal data at higher resolutions is much more difficult to obtain. This has allowed researchers to study urban heat island dynamics at a micro-scale. However, this study suggests that a vegetation index alone might not be the best surrogate variable for providing information regarding the independent effects and level of contribution that tree canopy, grass, and low-lying plants have on surface temperatures in residential neighborhoods. This research combines LIDAR (Light Detection and Ranging) feature height data and high-resolution infrared aerial photos to measure the characteristics of the micro-structure of residential areas (residentialstructure), derives various descriptive vegetation measurement statistics, and correlates the spatial distribution of surface temperature to the type and amount of vegetation cover in residential areas. Regression analysis is used to quantify the independent influence that different residential-structures have on surface temperature. In regard to implementing changes at a neighborhood level, the descriptive statistics derived for residential-structure at a micro-scale may provide useful information to decision-makers and may reveal a guide for future developers concerned with mitigating the negative effects of urban heat island phenomena.Item Mapping surface fuels using LIDAR and multispectral data fusion for fire behavior modeling(2009-05-15) Mutlu, MugeFires have become intense and more frequent in the United States. Improving the accuracy of mapping fuel models is essential for fuel management decisions and explicit fire behavior prediction for real-time support of suppression tactics and logistics decisions. This study has two main objectives. The first objective is to develop the use of LIght Detection and Ranging (LIDAR) remote sensing to assess fuel models in East Texas accurately and effectively. More specific goals include: (1) developing LIDAR derived products and the methodology to use them for assessing fuel models; (2) investigating the use of several techniques for data fusion of LIDAR and multispectral imagery for assessing fuel models; (3) investigating the gain in fuels mapping accuracy with LIDAR as opposed to QuickBird imagery alone; and, (4) producing spatially explicit digital fuel maps. The second objective is to model fire behavior using FARSITE (Fire Area Simulator) and to investigate differences in modeling outputs using fuel model maps, which differ in accuracy, in east Texas. Estimates of fuel models were compared with in situ data collected over 62 plots. Supervised image classification methods provided better accuracy (90.10%) with the fusion of airborne LIDAR data and QuickBird data than with QuickBird imagery alone (76.52%). These two fuel model maps obtained from the first objective were used to see the differences in fire growth with fuel model maps of different accuracies. According to our results, LIDAR derived data provides accurate estimates of surface fuel parameters efficiently and accurately over extensive areas of forests. This study demonstrates the importance of using accurate maps of fuel models derived using new LIDAR remote sensing techniques.