GAPs: Geospatial Abduction Problems

2004

SUMMARY Location is fundamental to geospatial information. Arguably, it is the most basic notion to be specified in ontologies of the geospatial domain. Existing theories of location provide a useful basis for such ontologies, but are not constructive and therefore not directly applicable in computational settings. This paper introduces the elements of a computational theory of spatial location. The theory is being developed as a corner stone for a geospatial domain ontology in support of semantic interoperability.

The geographical location of Internet IP addresses has an importance both for academic research and commercial applications. Thus, both commercial and academic databases and tools are available for mapping IP addresses to geographic locations.

2006

Spurred by the recent escalation of terrorist attacks and their increasingly devastating outcomes, defense intelligence in the context of homeland security has been drawn into the spotlight. The challenge, at both national and global levels, of managing information in order to offensively resist attack or defensively keep citizens safe from further harm has never been greater. In meeting this challenge, the tools and strategies used by relevant defensive powers are a key factor in the success or failure of all activities, ranging from small-scale homeland security administration through to large-scale all-inclusive war. In all areas within this wide scope, the adoption of positioning technologies has played an important role. Of special significance are the global positioning system (GPS), second generation (2G) and beyond mobile telephone networks (including wireless data networks), radio-frequency identification (RFID) and geographic information systems (GIS). Since most positioning technology has been developed or released for use within the commercial sector however, concerns beyond technological feasibility are raised when applications are harnessed solely for defense. The integration between commercial and military sectors; and public and private needs must be considered, and, primarily, this involves ensuring that the enforcement of homeland security does not compromise citizen rights.

2012

A system and method for estimating a geolocation of a non-cooperative target using any reasonable target location estimate. Collectors may acquire actual signal measurements including a direction of arrival (DOA), a target range, a time difference of arrival (TDOA), a range rate, a range sum, and/or a frequency difference of arrival (FDOA). A processing device may receive the actual signal measurements and navigational data regarding the collectors. Then, the processing device may calculate an estimated target location as a solution to a nonlinear optimization problem where an objective function to be minimized is a weighted sum-of-squares of differences between the actual signal measurements and calculated values corresponding to signal measurements that theoretically should be produced for a particular target location. The algorithm used to solve this problem may be a globally convergent algorithm, such as a Levenberg-Marquardt algorithm.

Cartography and Geographic Information Science, 2015

When locations of individual-level health data are released in the form of published maps, the identity of these individuals could be identified through reverse geocoding. Spatial data can, therefore, not be released unless the locations have been modified, for example, using aggregation or geographic masking. Geographic masking techniques apply translation or perturbations to decrease the likelihood of re-identification of individuals through reverse geocoding. The current study proposes a new geographic masking technique referred to as "location swapping." Location swapping replaces an original location with a masked location selected from all possible locations with similar geographic characteristics within a specified neighborhood. Strengths and weaknesses of location swapping will be discussed relative to existing geographic masking techniques. The approach will be illustrated using several example data sets and a custom toolset developed for ArcGIS to automate the location swapping algorithm.

Proceedings of the 30th International Conference on Advances in Geographic Information Systems

Given trajectories with gaps, we investigate methods to tighten spatial bounds on areas (e.g., nodes in a spatial network) where possible rendezvous activity could have occurred. The problem is important for reducing manual effort to post-process possible rendezvous areas using satellite imagery and has many societal applications to improve public safety, security, and health. The problem of rendezvous detection is challenging due to the difficulty of interpreting missing data within a trajectory gap and the very high cost of detecting gaps in such a large volume of location data. Most recent literature presents formal models, namely space-time prism, to track an object's rendezvous patterns within trajectory gaps on a spatial network. However, the bounds derived from the space-time prism are rather loose, resulting in unnecessarily extensive postprocessing manual effort. To address these limitations, we propose a Time Slicing-based Gap-Aware Rendezvous Detection (TGARD) algorithm to tighten the spatial bounds in spatial networks. We propose a Dual Convergence TGARD (DC-TGARD) algorithm to improve computational efficiency using a bi-directional pruning approach. Theoretical results show the proposed spatial bounds on the area of possible rendezvous are tighter than that from related work (space-time prism). Experimental results on synthetic and real-world spatial networks (e.g., road networks) show that the proposed DC-TGARD is more scalable than the TGARD algorithm.

Political Science Research and Methods, 2018

Improving geolocation accuracy in text data has long been a goal of automated text processing. We depart from the conventional method and introduce a two-stage supervised machine-learning algorithm that evaluates each location mention to be either correct or incorrect. We extract contextual information from texts, i.e., N-gram patterns for location words, mention frequency, and the context of sentences containing location words. We then estimate model parameters using a training data set and use this model to predict whether a location word in the test data set accurately represents the location of an event. We demonstrate these steps by constructing customized geolocation event data at the subnational level using news articles collected from around the world. The results show that the proposed algorithm outperforms existing geocoders even in a case added post hoc to test the generality of the developed algorithm.

The "crowd" has become a very important geospatial data provider. Subsumed under the term Volunteered Geographic Information (VGI), non-expert users have been providing a wealth of quantitative geospatial data online. With spatial reasoning being a basic form of human cognition, narratives expressing geospatial experiences, e.g., travel blogs, would provide an even bigger source of geospatial data. Textual narratives typically contain qualitative data in the form of objects and spatial relationships. The scope of this work is (i) to extract these relationships from user-generated texts, (ii) to quantify them and (iii) to reason about object locations based only on this qualitative data. We use information extraction methods to identify toponyms and spatial relationships and to formulate a quantitative approach based on distance and orientation features to represent the latter. Positional probability distributions for spatial relationships are determined by means of a greedy Expectation Maximization-based (EM) algorithm. These estimates are then used to "triangulate" the positions of unknown object locations. Experiments using a text corpus harvested from travel blog sites establish the considerable location estimation accuracy of the proposed approach.

Journal of Computer Science and Technology, 2009

This article proposes a graph-theoretic methodology for query approximation in Geographic Information Systems, enabling the relaxation of three kinds of query constraints: topological, semantic and structural. An approximate query is associated with a value corresponding to the degree of similarity with the original query. Such a value is computed for topological constraints on the basis of the topological distance between configurations, for semantic constraints using the information content approach, and for structural constraints revisiting the maximum weighted matching problem in bipartite graphs. Finally, the high correlation of our proposal with human judgment is demonstrated by an experiment.

2010

This paper investigates the root causes of insurgency and exploits a Geographic Information System (GIS) to model the effects of terrain and urban infrastructure on insurgent behavior. It develops a mathematical model that can predict the likelihood of an individual turning into an insurgent based on various contributory factors. Insurgency in Iraq and Afghanistan has been on the rise, primarily to fight the United States (U.S.)-led coalition forces. Insurgents often seek complex terrain and urban infrastructure to ambush U.S.-led coalition forces which are carrying out military missions in Iraq and Afghanistan. Using examples from Iraq we model spatial and temporal trends in insurgent activities with a GIS, which may help understand the overall insurgency and behavior of insurgents who carry out attacks against U.S-led coalition forces.