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Airborne LIDAR (Light Detecting and Ranging) is a relatively new technique that rapidly and accurately measures micro-topographic features. This study compares topography derived from LIDAR with subsurface karst structures mapped in 3-dimensions with ground penetrating radar (GPR). Over 500 km of LIDAR data were collected in 1995 by the NASA ATM instrument. The LIDAR data was processed and analyzed to identify closed depressions. A GPR survey was then conducted at a 200 by 600 m site to determine if the target features are associated with buried karst structures. The GPR survey resolved two major depressions in the top of a clay rich layer at ~10m depth. These features are interpreted as buried dolines and are associated spatially with subtle (< 1m) trough-like depressions in the topography resolved from the LIDAR data. This suggests that airborne LIDAR may be a useful tool for indirectly detecting subsurface features associated with sinkhole hazard.

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The situations and problems that police officers face are more complex in today’s society, due in part to the increase of technology and growing complexity of globalization. Accordingly, to solve these problems and deal with the complexities, law enforcement organizations develop and apply new techniques and methods such as geographic information systems (GIS). However, the successful implementation of a new technology does not just depend on providing perfect technical support, but effective and active interaction between the user and system. For this reason, research examining user acceptance of GIS technologies provides a valuable source to investors and designers to predict whether the results of the technology will meet user expectations; understanding the factors that influence user acceptance is vitally important to make the system more usable and preferable. This study attempts to explain Turkish National Police officers’ beliefs about and behaviors toward GIS applications by using the technology acceptance models. It contributes to the technology acceptance literature by testing the proposed model in a rarely studied organization: law enforcement. Regarding methodology, I distributed a survey questionnaire in Turkey; the unit of analysis was the law enforcement officers in the Turkish National Police (TNP). In order to analyze the data derived from the survey instrument, structural equation modeling (SEM), a multivariate statistical technique, was used to analyze the quantitative data by utilizing the AMOS 16.0 software. The analysis resulted in good model fit, and 6 of the 7 hypotheses were supported.

Indiana University-Purdue University Indianapolis (IUPUI) / The use of Global Positioning Systems (GPS) and/or accelerometers to identify trips and transportation modes such as walking, running, bicycling or motorized transportation has been an active goal in multiple disciplines such as Transportation Engineering, Computer Science, Informatics and Public Health. The purpose of this study was to review existing methods that determined trip and travel mode from raw Global Positioning System (GPS) and accelerometer data, and test a select group of these methods. The study had three specific aims: (1) Create a systematic review of existing literature that explored various methods for determining trip and travel mode from GPS and/or accelerometer data, (2) Collect a convenience sample of subjects who were assigned a GPS and accelerometer unit to wear while performing and logging travel bouts consisting of walking, running, bicycling and driving, (3) Replicate selected method designs extracted from the systematic review (aim 1) and use subject data (aim 2) to compare the methods. The results were be used to examine which methods are effective for various modes of travel.