<p> Aerial photography is an important layer in Geographic Information Systems (GISs), and generally provides the base layer from which many other digital map layers are derived. Capturing these photos from a traditional full-sized airplane is a complex and expensive process. The recent development of Unmanned Aerial Vehicles (UAVs) and associated technology are providing an alternative to the traditional aerial mapping process. UAVs produced by popular commercial vendors are effective at capturing photos, but are highly expensive to acquire, and equally expensive to maintain.</p><p> This research project demonstrates the development and successful implementation of a relatively inexpensive ($2000) unmanned aerial vehicle capable of acquiring high-resolution digital aerial photography. The UAV was developed using open source technology and commercially available components. The methods outlined encompass the platform selection, component inventory, design, construction, configuration, implementation, and testing of the UAV, as well as an analysis of the photography produced by the process. This approach can be used by others to implement similar UAV projects.</p>

<p> Three-dimensional mapping and modeling can contribute to knowledge about the real world. Techniques are largely driven by available technology and typically involve expensive equipment and expert skill. Recent advances have led to low-cost remotely sensed data collection and generation of 3D terrain models using Uninhabited Aerial Vehicles (UAV) and Structure from Motion (SfM) processing software. This research presents a low-cost alternative to 3D mapping by pairing UAV collection methods with three SfM processing techniques. Surface models are generated from the same image set captured from a low-cost UAV coupled with a digital camera. Accuracy of resulting models identifies strengths and weaknesses of each technique. Analysis of different slope ranges investigates the divide at which surfaces generated become less reliable. This research provides a deeper understanding of the strengths and limitations of emerging technologies used together in a fresh approach to photogrammetry.</p>

<p> As an alternative to spherical harmonics in modeling the gravity field of the Earth, we built a multiresolution gravity model by employing spherical regularization wavelets in solving the inverse problem, <i>i.e.</i> downward propagation of the gravity signal to the Earth's surface. Scale discrete Tikhonov spherical regularization scaling function and wavelet packets were used to decompose and reconstruct the signal. We recovered the local gravity anomaly using only localized gravity measurements at the observing satellite's altitude of 300 km. When the upward continued gravity anomaly to the satellite altitude with a resolution 0.5&deg; was used as simulated measurement inputs, our model could recover the local surface gravity anomaly at a spatial resolution of 1&deg; with an RMS error between 1 and 10 mGal, depending on the topography of the gravity field. Our study of the effect of varying the data volume and altering the maximum degree of Legendre polynomials on the accuracy of the recovered gravity solution suggests that the short wavelength signals and the regions with high magnitude gravity gradients respond more strongly to such changes. When tested with simulated SGG measurements, <i> i.e.</i> the second order radial derivative of the gravity anomaly, at an altitude of 300 km with a 0.7&deg; spatial resolution as input data, our model could obtain the gravity anomaly with an RMS error of 1 ~ 7 mGal at a surface resolution of 0.7&deg; (&lt; 80 km). The study of the impact of measurement noise on the recovered gravity anomaly implies that the solutions from SGG measurements are less susceptible to measurement errors than those recovered from the upward continued gravity anomaly, indicating that the SGG type mission such as GOCE would be an ideal choice for implementing our model. Our simulation results demonstrate the model's potential in determining the local gravity field at a finer scale than could be achieved through spherical harmonics, <i>i.e.</i> less than 100 km, with excellent performance in edge detection.</p>

<p> The Participatory GIS literature (PGIS) focuses on how community based organizations (CBOs) use geographic information. With its large population and history of community development the City of Long Beach is a perfect case study to explore this. For this research, I used a mixed methodology: conceptualization, interviews and surveys.</p><p> I conducted interviews covering five distinct subject areas to learn that connected organizations are more likely to use maps and geographic information. I then conducted a survey with 29 questions to find how this is the case. One idea is that there is a process of organization. Another is the possibility of predicting map usage using development level and organization type. Finally, this research proposes that new research qualitatively trace usage using a broad population.</p>

<p> Geomorphologic methods document poorly exposed tectonically active structures in the first study to determine quantified ages for Quaternary Age fluvial terraces at Santa Cruz Creek. GPS surveys of three flights of terrace surfaces and a stream gradient profile reveal deformation at the Baseline/Los Alamos fault zone and Little Pine fault. Optically Stimulated Luminescence (OSL) dating was employed to determine ages for the terraces. The formation age of Terrace 1 is 19.3 ka with an incision rate of 1.63 to 1.82 mm/yr, Terrace 2 was dated at 32.9 ka with incision rate of2.02 to 1.82 mm/yr. Based on incision rates an estimated age of 44.0-47.0 ka was calculated for Terrace 3. Offsets in T-2 and T-3 were used to calculate a short term faulting rates of .91 mm/yr and a long term faulting rate of 0.67 to 0. 73 mm/yr for the Baseline/Los Alamos fault.</p>

<p> This dissertation presents the results of a pedestrian field survey in the microregion around the Middle Neolithic Goseck rondel. Predictive models created in GIS were tested against archaeological material gathered through the survey. A previously unknown Stroke Ornamented Pottery site was located through this fieldwork. Predictive models for rondel sites were also created, and a satellite survey located two previously unknown rondel candidate sites. Spatial analyses were conducted in GIS to compare settlement structure diachronically through the Middle Neolithic. Included in these analyses was the creation of transportation networks for each of three Middle Neolithic cultures. This research begins to fill in the vast empty spaces between site points through analysis of embodied pathways that bind these places together. A set of spatial analyses were used to test if an archaeological site may have been subjected to a spatial taboo. This approach represents a new line of research into the archaeology of social memory.</p>

<p> This dissertation lies at the intersection of two current trends in technology, both of which are increasing with the spread of high speed internet: location-based services (geospatial technologies) and Free and Open Source Software (FOSS). Chapter one explores the nature of geospatial technology knowledge diffusion by investigating the spread of OSGeo-Live, a collection of pre-existing geospatial FOSS packaged specifically for demonstration and education purposes. The analysis examines the distribution of downloaders, contributors and translators then assesses the potential barriers to knowledge diffusion including economic, technical and socio-cultural factors. Chapter two describes a new online tool built with FOSS designed to bring traditional cartographic knowledge to a new medium, the internet, and a new audience, web developers and other non-traditional internet-based cartographers. The tool allows users to compare several base map options simultaneously, providing guidance on how to assess the appropriateness of a base map for a particular map composition. Chapter three uses geospatial FOSS software to conduct verification of a habitat fragmentation model with GPS tracking data. By demonstrating a common type of analysis for natural resource scientists, the methods provide an example for traditional types of geospatial analysis emphasizing repeatability, shareability, and usability by field science practitioners not just geospatial specialists. These studies represent an initial foray into understanding geospatial technology diffusion and modern geospatial technologies, specifically with geospatial free and open source software.</p>

<p> Basketball is a unique sport in which the use of space and time is greatly important for a team&rsquo;s success. Furthermore, the National Basketball Association (NBA) is undergoing drastic change in terms of the way teams approach spatial issues as well as the spatio-temporal technologies and analytics. Given these facts, Geographic Information Systems (GIS) provide the opportunity to develop new analytic and visual methodologies to perform spatial analysis for team performances and meet the league&rsquo;s changing needs. This project thus develops new approaches, methods, and toolsets using GIS to demonstrate its efficacy and potential for professional application in the NBA. The first application uses GIS to adapt Relative Motion analysis techniques to an existing play, seeking to represent the average motion characteristics entailed therein. The other application uses a tool developed to map, glean spatial statistics, and model the use and importance of floor spacing for teams in the NBA. </p>

<p> The spatial patterning of artifacts and features excavated from Tule Creek Village (CA-SNI-25), San Nicolas Island, CA provides an opportunity to analyze the intra-site correlations between artifact types, materials, and features, and allows for inferences to be made regarding the context and use of space at a late Holocene village. Excavations at East Locus at CA-SNI-25 have yielded evidence of trade with other islands as well as evidence suggesting complex ceremonial activity, such as dog and bird burials, large hearths, stacked stone features, and multiple pits which vary in size, shape and depositional content. The artifact assemblage, favorable geographic setting, and inferred ceremonial activity observed at East Locus in comparison to other late Holocene sites on San Nicolas suggest that CA-SNI-25 served as the primary center for social and economic interactions on the island during a time when the intensification of complex spheres of interaction are observed throughout the southern California Bight.</p><p> I use intra-site GIS and exploratory methods, such as spatial autocorrelation and hot-spot analysis to isolate distributions of formal artifacts and features and examine the organization of space in both ceremonial and utilitarian contexts. This provides a visual and interactive platform conducive to analyzing the abundant data collected during open area excavations at CA-SNI-25. The statistical analysis allows for inferences to be made regarding the manufacture and use of artifact types and toolkits in ceremonial and utilitarian contexts, as well as the import and use of exotic materials. Ultimately, spatial analysis using intra-site GIS reveals possible linkages of artifacts and features, as well as patterns of spatial and temporal variability in technology, subsistence, and behavior at a village on San Nicolas just prior to European contact.</p>

<p> Recent approaches to crater detection have been inspired by face detection's use of gray-scale texture features. Using gray-scale texture features for supervised machine learning crater detection algorithms provides better classification of craters in planetary images than previous methods. When using Haar features it is typical to generate thousands of numerical values from each candidate crater image. This magnitude of image features to extract and consider can spell disaster when the application is an entire planetary surface. One solution is to reduce the number of features extracted and considered in order to increase accuracy as well as speed. Feature subset selection provides the operational classifiers with a concise and denoised set of features by reducing irrelevant and redundant features. Feature subset selection is known to be NP-hard. To provide an efficient suboptimal solution, four genetic algorithms are proposed to use greedy selection, weighted random selection, and simulated annealing to distinguish discriminate features from indiscriminate features. Inspired by analysis regarding the relationship between subset size and accuracy, a squeezing algorithm is presented to shrink the genetic algorithm's chromosome cardinality during the genetic iterations. A significant increase in the classification performance of a Bayesian classifier in crater detection using image texture features is observed.</p>