Relevant bibliographies by topics / Geospatial Reasoning

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Geospatial Reasoning'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 February 2022

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Journal articles on the topic "Geospatial Reasoning"

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Van Dyke Parunak, H., Sven A. Brueckner, Robert Matthews, and John Sauter. "Swarming methods for geospatial reasoning." International Journal of Geographical Information Science 20, no. 9 (October 2006): 945–64. http://dx.doi.org/10.1080/13658810600830525.

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Erskine, Michael A., Dawn G. Gregg, Jahangir Karimi, and Judy E. Scott. "Geospatial Reasoning Ability: Definition, Measurement and Validation." International Journal of Human-Computer Interaction 31, no. 6 (April 15, 2015): 402–12. http://dx.doi.org/10.1080/10447318.2015.1034551.

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Bodzin, Alec M., Qiong Fu, Violet Kulo, and Tamara Peffer. "Examining the Effect of Enactment of a Geospatial Curriculum on Students’ Geospatial Thinking and Reasoning." Journal of Science Education and Technology 23, no. 4 (March 8, 2014): 562–74. http://dx.doi.org/10.1007/s10956-014-9488-6.

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Smart, Philip D., Alia I. Abdelmoty, and Baher El-Geresy. "Spatial Reasoning with Place Information on the Semantic Web." International Journal on Artificial Intelligence Tools 23, no. 05 (October 2014): 1450011. http://dx.doi.org/10.1142/s0218213014500110.

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Geographical referencing of data and resources on the Web has become prevalent. Discovering and linking this information poses eminent research challenges to the geospatial semantic web, with regards to the representation and manipulation of information on geographic places. Towards addressing these challenges, this work explores the potential of the current semantic web languages and tools. In particular, an integrated logical framework of rules and ontologies, using current W3C standards, is assessed for modeling geospatial ontologies of place and for encoding both symbolic and geometric references to place locations. Spatial reasoning is incorporated in the framework to facilitate the deduction of implicit spatial relations and for expressing spatial integrity constraints. The logical framework is extended with geo-computation engines that offer more effective manipulation of geometric information. Example data sets mined from web resources are used to demonstrate and evaluate the framework, offering insights to its potentials and limitations.
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Chen, Jianhua, Weihong Wang, and Junwen Li. "A geospatial case-based reasoning model for oil-gas reservoir evaluation." Transactions in GIS 22, no. 2 (March 6, 2018): 373–93. http://dx.doi.org/10.1111/tgis.12316.

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Akinyemi, Felicia O. "Incorporating Geographic Information Science in the BSc Environ-mental Science Program in Botswana." Proceedings of the ICA 1 (May 16, 2018): 1–8. http://dx.doi.org/10.5194/ica-proc-1-3-2018.

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Critical human capacity in Geographic Information Science (GISc) is developed at the Botswana International University of Science and Technology, a specialized, research university. Strategies employed include GISc courses offered each semester to students from various programs, the conduct of field-based projects, enrolment in online courses, geo-spatial initiatives with external partners, and final year research projects utilizing geospatial technologies. A review is made of available GISc courses embedded in the Bachelor of Science Environmental Science program. GISc courses are incorporated in three Bachelor degree programs as distinct courses. Geospatial technologies are employed in several other courses. Student researches apply GIS and Remote Sensing methods to environmental and geological themes. The overarching goals are to equip students in various disciplines to utilize geospatial technologies, and enhance their spatial thinking and reasoning skills.
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Wen, Tzai-Hung, and Hao-Yu Liao. "Understanding the Process of Geospatial Reasoning: Evidences from an Eye-Tracking Experiment." Abstracts of the ICA 1 (July 15, 2019): 1. http://dx.doi.org/10.5194/ica-abs-1-400-2019.

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<p><strong>Abstract.</strong> People always need the help of maps when traveling or finding a restaurant. Maps carry geospatial information of a place with roads, landmarks, coordinate systems and so on. When people are reading maps, the first thing our brains do is to fit the map to the realistic environment, trying to integrate the 2-D maps into the 3-D world. In other words, we are managing to align the two different coordinate systems which the map and external realistic environment provide. However, when the direction of the map is not perfectly aligned with the external realistic environment, a person may need more time and effort to do the alignment. And if the map is near upside down, this task could become a challenge and possibly cause a person making a wrong judgment. This situation is called the alignment effect. Alignment effect is the extra time and effort required to rotate the mental representation of physical maps. When someone is doing map aligning, the ability of rotation is needed, either rotating the actual map or rotating the space in the mind. Mental rotation is one of the fundamental factors that could determine a person’s map aligning ability. Previous studies have highlighted the significance of mental rotation ability in map aligning and also confirmed the relationship between mental rotation ability and alignment effect. Measuring mental rotation ability could understand how and where people see on a map. Its significance is not just about designing a map, but also how people process geospatial information on a map. Therefore, the research question of the study is how we quantify people’s ability of mental rotation.</p><p>Eye tracking approach helps understand how people see or read things, and provide insights into people’s ways of reasoning and problem solving. We randomly choose the 12 college students (undergraduate and graduate) as participants in this study, all in the age of 18&amp;ndash;30, and studied in the same university. The sex ratio is balanced; among the 12 participants, there were 6 males and 6 females. All the participants were required to fill the questionnaires and experiment consents before the eye tracking experiment. Then, we are attempted to profile the geospatial reasoning process by measuring and recording participants’ gaze positions and eye movements. The eye-tracking experiment for each participant includes 6 tasks, including different degrees of rotation and quantities of key map elements with high degree of rotation. Each of the tasks contains two stimuli, the first stimuli would instruct the participants to find their own location and the destination, and the second stimuli would examine their abilities of map aligning. When doing map aligning, they would see a map and a street view from their location. The participants are required to decide which direction is the destination from his/her position. This stimulus remains 15 seconds. Then, a participant is requested to give his/her answer in 8 directions and cannot be able to look at the map and the street view. The participant will score one point if his/her answer is correct. Finally, we summarize the scores of these tasks for representing the his/her performance of mental rotation ability.</p><p>Our preliminary results showed participants with good mental rotation ability share similar patterns, implying that common rules of geospatial reasoning can be identified. Meanwhile, participants with poor mental rotation ability spent more time to search map information in difficult tasks. Therefore, we conclude that landmarks could be better clues than street names for map alignment and building a sense of direction, which implies that better map design (e.g. more landmarks) may be the key for improving map reading. In sum, we measured people’s map aligning performances and identify common rules of geospatial reasoning. This study lightens up the importance and value of eye-tracking approach in cartographic studies, and also brings a new perspective to understand the process of geospatial reasoning.</p>
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Jovanovik, Milos, Timo Homburg, and Mirko Spasić. "A GeoSPARQL Compliance Benchmark." ISPRS International Journal of Geo-Information 10, no. 7 (July 16, 2021): 487. http://dx.doi.org/10.3390/ijgi10070487.

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GeoSPARQL is an important standard for the geospatial linked data community, given that it defines a vocabulary for representing geospatial data in RDF, defines an extension to SPARQL for processing geospatial data, and provides support for both qualitative and quantitative spatial reasoning. However, what the community is missing is a comprehensive and objective way to measure the extent of GeoSPARQL support in GeoSPARQL-enabled RDF triplestores. To fill this gap, we developed the GeoSPARQL compliance benchmark. We propose a series of tests that check for the compliance of RDF triplestores with the GeoSPARQL standard, in order to test how many of the requirements outlined in the standard a tested system supports. This topic is of concern because the support of GeoSPARQL varies greatly between different triplestore implementations, and the extent of support is of great importance for different users. In order to showcase the benchmark and its applicability, we present a comparison of the benchmark results of several triplestores, providing an insight into their current GeoSPARQL support and the overall GeoSPARQL support in the geospatial linked data domain.
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Homburg, Timo. "Connecting Semantic Situation Descriptions with Data Quality Evaluations—Towards a Framework of Automatic Thematic Map Evaluation." Information 11, no. 11 (November 15, 2020): 532. http://dx.doi.org/10.3390/info11110532.

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A continuing question in the geospatial community is the evaluation of fitness for use of map data for a variety of use cases. While data quality metrics and dimensions have been discussed broadly in the geospatial community and have been modelled in semantic web vocabularies, an ontological connection between use cases and data quality expressions allowing reasoning approaches to determine the fitness for use of semantic web map data has not yet been approached. This publication introduces such an ontological model to represent and link situations with geospatial data quality metrics to evaluate thematic map contents. The ontology model constitutes the data storage element of a framework for use case based data quality assurance, which creates suggestions for data quality evaluations which are verified and improved upon by end-users. So-created requirement profiles are associated and shared to semantic web concepts and therefore contribute to a pool of linked data describing situation-based data quality assessments, which may be used by a variety of applications. The framework is tested using two test scenarios which are evaluated and discussed in a wider context.
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Du, Heshan, and Natasha Alechina. "Qualitative Spatial Logic over 2D Euclidean Spaces Is Not Finitely Axiomatisable." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 2776–83. http://dx.doi.org/10.1609/aaai.v33i01.33012776.

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Several qualitative spatial logics used in reasoning about geospatial data have a sound and complete axiomatisation over metric spaces. It has been open whether the same axiomatisation is also sound and complete for 2D Euclidean spaces. We answer this question negatively by showing that the axiomatisations presented in (Du et al. 2013; Du and Alechina 2016) are not complete for 2D Euclidean spaces and, moreover, the logics are not finitely axiomatisable.
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Dissertations / Theses on the topic "Geospatial Reasoning"

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Obrike, Stephen Ewomazino. "An evidential reasoning geospatial approach to transport corridor susceptibility zonation." Thesis, University of Newcastle upon Tyne, 2016. http://hdl.handle.net/10443/3276.

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Given the increased hazards faced by transport corridors such as climate induced extreme weather, it is essential that local spatial hot-spots of potential landslide susceptibility can be recognised. Traditionally, geotechnical survey and monitoring approaches have been used to recognise spatially landslide susceptibility zones. The increased availability of affordable very high resolution remotely-sensed datasets, such as airborne laser scanning (ALS) and multispectral aerial imagery, along with improved geospatial digital map data-sets, potentially allows the automated recognition of vulnerable earthwork slopes. However, the challenge remains to develop the analytical framework that allows such data to be integrated in an objective manner to recognise slopes potentially susceptible to failure. In this research, an evidential reasoning multi-source geospatial integration approach for the broad-scale recognition and prediction of landslide susceptibility in transport corridors has been developed. Airborne laser scanning and Ordnance Survey DTM data is used to derive slope stability parameters (slope gradient, aspect, terrain wetness index (TWI), stream power index (SPI) and curvature), while Compact Airborne Spectrographic Imager (CASI) imagery, and existing national scale digital map data-sets are used to characterise the spatial variability of land cover, land use and soil type. A novel approach to characterisation of soil moisture distribution within transport corridors is developed that incorporates the effects of the catchment contribution to local zones of moisture concentration in earthworks. In this approach, the land cover and soil type of the wider catchment are used to estimate the spatial contribution of precipitation contributing to surface runoff, which in turn is used to parameterise a weighted terrain accumulation flow model. The derived topographic and land use properties of the transport corridor are integrated within the evidential reasoning approach to characterise numeric measures of belief, disbelief and uncertainty regarding slope instability spatially within the transport corridor. Evidential reasoning was employed as it offers the ability to derive an objective weighting of the relative importance of each derived property to the final estimation of landslide susceptibility, whilst allowing the uncertainty of the properties to be taken into account. The developed framework was applied to railway transport earthworks located near Haltwhistle in northern England, UK. This section of the Carlisle-Newcastle rail line has a ii history of instability with the occurrence of numerous minor landslides in recent years. Results on spatial distribution of soil moisture indicate considerable contribution of the surrounding wider catchment topography to the localised zones of moisture accumulation. The degrees of belief and disbelief indicated the importance of slope with gradients between 250 to 350 and concave curvature. Permeable soils with variable intercalations accounted for over 80% of slope instability with 5.1% of the earthwork cuttings identified as relatively unstable in contrast to 47.5% for the earthwork embankment. The developed approach was found to have a goodness of fit of 88.5% with respect to the failed slopes used to parametrise the evidential reasoning model and an overall predictive capability of 77.75% based on independent validation dataset.
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Reed, Rajika E. "Using Geospatial Thinking and Reasoning Skills to Examine Vector Borne Disease Transmission through Web GIS in Undergraduate Students Studying Public Health." Thesis, Lehigh University, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10279465.

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Geospatial thinking and reasoning skills (GSTR) are currently not routinely integrated into public health curriculum for undergraduate students in institutions of higher education.  However, integrating GSTR skills into curriculum has been shown to increase spatial thinking skills which leads to better cognitive thinking and problem solving skills.  An Examining Vector Borne Disease Transmission (EVBDT) curriculum unit was developed using the geospatial curriculum approach to investigate malaria, dengue fever and zika disease patterns and spread in relation to the environment and to promote GSTR.  The purpose of this design based research study was to understand public health content learning and GSTR skill acquisition with undergraduate learners through use of the geospatial curriculum approach. The undergraduate students who participated in this study (n = 95) were enrolled in public health content classes at two separate institutions.  Data was collected for this study using a classroom observation instrument, pre-test and post-test measures for the Spatial Habits of the Mind (SHOM) survey, a pre-test, post-test 1 and delayed post-test 2 EVBDT assessment that included public health content and GSTR skill items, as well as a post implementation survey to understand students’ perceptions of GIS use in the curriculum.  Findings demonstrated significant mean differences showing growth in public health content learning and GSTR skills. Three GSTR subscales—inferences, relationships, and reasoning—resulted in significant gains.  Additionally, results revealed complete adherence to the design principles of the geospatial curriculum approach during implementation. The findings provide support that Web GIS with appropriate curriculum design can engage students and impact both learning outcomes and geospatial thinking and reasoning skills in public health education.

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Chuprikova, Ekaterina Verfasser], Liqiu [Akademischer Betreuer] [Meng, Liqiu [Gutachter] Meng, Alan M. [Gutachter] MacEachren, and Jochen [Gutachter] Schiewe. "Visualizing Uncertainty in Reasoning : A Bayesian Network-enabled Visual Analytics Approach for Geospatial Data / Ekaterina Chuprikova ; Gutachter: Liqiu Meng, Alan M. MacEachren, Jochen Schiewe ; Betreuer: Liqiu Meng." München : Universitätsbibliothek der TU München, 2019. http://d-nb.info/1194162673/34.

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Pathak, Mahesh. "Conservation GIS: Ontology and spatial reasoning for commonsense knowledge." Master's thesis, 2011. http://hdl.handle.net/10362/5616.

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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.
Geographic information available from multiple sources are moving beyond their local context and widening the semantic difference. The major challenge emerged with ubiquity of geographic information, evolving geospatial technology and location-aware service is to deal with the semantic interoperability. Although the use of ontology aims at capturing shared conceptualization of geospatial information, human perception of world view is not adequately addressed in geospatial ontology. This study proposes ‘Conservation GIS Ontology’ that comprises spatial knowledge of non-expert conservationists in the context of Chitwan National Park, Nepal. The discussion is presented in four parts: exploration of commonsense spatial knowledge about conservation; development of conceptual ontology to conceptualize domain knowledge; formal representation of conceptualization in Web Ontology Language (OWL); and quality assessment of the ontology development tasks. Elicitation of commonsense spatial knowledge is performed with the notion of cognitive view of semantic. Emphasis is given to investigate the observation of wildlife movement and habitat change scenarios. Conceptualization is carried out by providing the foundation of the top-level ontology- ‘DOLCE’ and geospatial ontologies. Protégé 4.1 ontology editor is employed for ontology engineering tasks. Quality assessment is accomplished based on the intrinsic approach of ontology evaluation.(...)
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"Data Driven Inference in Populations of Agents." Doctoral diss., 2019. http://hdl.handle.net/2286/R.I.53476.

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abstract: In the artificial intelligence literature, three forms of reasoning are commonly employed to understand agent behavior: inductive, deductive, and abductive.  More recently, data-driven approaches leveraging ideas such as machine learning, data mining, and social network analysis have gained popularity. While data-driven variants of the aforementioned forms of reasoning have been applied separately, there is little work on how data-driven approaches across all three forms relate and lend themselves to practical applications. Given an agent behavior and the percept sequence, how one can identify a specific outcome such as the likeliest explanation? To address real-world problems, it is vital to understand the different types of reasonings which can lead to better data-driven inference.   This dissertation has laid the groundwork for studying these relationships and applying them to three real-world problems. In criminal modeling, inductive and deductive reasonings are applied to early prediction of violent criminal gang members. To address this problem the features derived from the co-arrestee social network as well as geographical and temporal features are leveraged. Then, a data-driven variant of geospatial abductive inference is studied in missing person problem to locate the missing person. Finally, induction and abduction reasonings are studied for identifying pathogenic accounts of a cascade in social networks.
Dissertation/Thesis
Doctoral Dissertation Computer Science 2019
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Book chapters on the topic "Geospatial Reasoning"

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Hitzler, Pascal. "Towards Reasoning Pragmatics." In GeoSpatial Semantics, 9–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10436-7_2.

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Chang, Chin–Lung, Yi–Hong Chang, Tyng–Ruey Chuang, Dong–Po Deng, and Andrea Wei–Ching Huang. "Narrative Geospatial Knowledge in Ethnographies: Representation and Reasoning." In GeoSpatial Semantics, 188–203. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10436-7_12.

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Koutsioumpas, Achilleas. "Abductive Reasoning in 2D Geospatial Problems." In Applications of Mathematics and Informatics in Science and Engineering, 333–47. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04720-1_21.

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Karmacharya, Ashish, Christophe Cruz, Frank Boochs, and Franck Marzani. "Use of Geospatial Analyses for Semantic Reasoning." In Knowledge-Based and Intelligent Information and Engineering Systems, 576–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15387-7_61.

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Sahli, Nabil, and Nafaa Jabeur. "Knowledge Discovery and Reasoning in Geospatial Applications." In Scientific Data Mining and Knowledge Discovery, 251–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02788-8_10.

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Whigham, P. A., R. I. McKay, and J. R. Davis. "Machine induction of geospatial knowledge." In Theories and Methods of Spatio-Temporal Reasoning in Geographic Space, 402–17. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/3-540-55966-3_24.

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Mau, Inga, Kathleen Stewart Hornsby, and Ian D. Bishop. "Modeling Geospatial Events and Impacts Through Qualitative Change." In Spatial Cognition V Reasoning, Action, Interaction, 156–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-75666-8_10.

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Koubarakis, Manolis, Manos Karpathiotakis, Kostis Kyzirakos, Charalampos Nikolaou, Stavros Vassos, George Garbis, Michael Sioutis, et al. "Building Virtual Earth Observatories Using Ontologies and Linked Geospatial Data." In Web Reasoning and Rule Systems, 229–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33203-6_21.

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Bry, François, Bernhard Lorenz, Hans Jürgen Ohlbach, and Mike Rosner. "A Geospatial World Model for the Semantic Web." In Principles and Practice of Semantic Web Reasoning, 145–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11552222_14.

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Zaharia, Raluca, Laurenţiu Vasiliu, and Costin Bădică. "Semi-automatic Composition of Geospatial Web Services Using JBoss Rules." In Rule Representation, Interchange and Reasoning on the Web, 166–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-88808-6_18.

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Conference papers on the topic "Geospatial Reasoning"

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Win, K. K., and Khin Haymar Saw Hla. "Geospatial Semantic Query by Integrating Geospatial Reasoning on the Geospatial Semantic Web." In 6th Asia-Pacific Symposium on Information and Telecommunication Techniques. IEEE, 2005. http://dx.doi.org/10.1109/apsitt.2005.203669.

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Wang, Ping, Li Guan, and Xiangnan Liu. "Heterogeneous data integration of vector data and imagery based on fuzzy reasoning in GIS." In Geoinformatics 2006: Geospatial Information Science, edited by Jianya Gong and Jingxiong Zhang. SPIE, 2006. http://dx.doi.org/10.1117/12.712742.

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Campalani, Piero, Dimitar Misev, Alan Beccati, and Peter Baumann. "Making Time Just Another Axis in Geospatial Services." In 2013 20th International Symposium on Temporal Representation and Reasoning (TIME). IEEE, 2013. http://dx.doi.org/10.1109/time.2013.24.

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"GEOSPATIAL SEMANTIC QUERY BASED ON CASE-BASED REASONING SYSTEM." In 8th International Conference on Enterprise Information Systems. SciTePress - Science and and Technology Publications, 2006. http://dx.doi.org/10.5220/0002469203560359.

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Douglas, Joel, Matthew Antone, James Coggins, Bradley J. Rhodes, Erik Sobel, Frank Stolle, Lori Vinciguerra, Majid Zandipour, and Yu Zhong. "Contextual object understanding through geospatial analysis and reasoning (COUGAR)." In SPIE Defense, Security, and Sensing, edited by Firooz A. Sadjadi and Abhijit Mahalanobis. SPIE, 2009. http://dx.doi.org/10.1117/12.823438.

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Alam, Ashraful, Ganesh Subbiah, Bhavani Thuraisingam, and Latifur Khan. "Reasoning with semantics-aware access control policies for geospatial web services." In the 3rd ACM workshop. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1180367.1180380.

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Park, No-Wook. "Evidential reasoning applied to GIS-based landslide susceptibility mapping with geospatial data." In IGARSS 2010 - 2010 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2010. http://dx.doi.org/10.1109/igarss.2010.5653966.

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Mora, Brice, Richard A. Fournier, Samuel Foucher, Goze B. Benie, and Kim Lowell. "Evidential Reasoning Applied to Mapping Regeneration of Forest Stand using Multisource Geospatial Data." In IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2008. http://dx.doi.org/10.1109/igarss.2008.4779482.

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Aasman, Jans. "Unification of geospatial reasoning, temporal logic, & social network analysis in event-based systems." In the second international conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1385989.1386007.

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