@article{saffer_tateosian_saville_yang_ristaino_2024, title={Reconstructing historic and modern potato late blight outbreaks using text analytics}, volume={14}, ISSN={["2045-2322"]}, DOI={10.1038/s41598-024-52870-2}, abstractNote={Abstract In 1843, a hitherto unknown plant pathogen entered the US and spread to potato fields in the northeast. By 1845, the pathogen had reached Ireland leading to devastating famine. Questions arose immediately about the source of the outbreaks and how the disease should be managed. The pathogen, now known as Phytophthora infestans , still continues to threaten food security globally. A wealth of untapped knowledge exists in both archival and modern documents, but is not readily available because the details are hidden in descriptive text. In this work, we (1) used text analytics of unstructured historical reports (1843–1845) to map US late blight outbreaks; (2) characterized theories on the source of the pathogen and remedies for control; and (3) created modern late blight intensity maps using Twitter feeds. The disease spread from 5 to 17 states and provinces in the US and Canada between 1843 and 1845. Crop losses, Andean sources of the pathogen, possible causes and potential treatments were discussed. Modern disease discussion on Twitter included near-global coverage and local disease observations. Topic modeling revealed general disease information, published research, and outbreak locations. The tools described will help researchers explore and map unstructured text to track and visualize pandemics.}, number={1}, journal={SCIENTIFIC REPORTS}, author={Saffer, Ariel and Tateosian, Laura and Saville, Amanda C. and Yang, Yi-Peng and Ristaino, Jean B.}, year={2024}, month={Feb} }
 @article{white_petrasova_petras_tateosian_vukomanovic_mitasova_meentemeyer_2023, title={An open-source platform for geospatial participatory modeling in the cloud}, volume={167}, ISSN={["1873-6726"]}, url={http://dx.doi.org/10.1016/j.envsoft.2023.105767}, DOI={10.1016/j.envsoft.2023.105767}, abstractNote={Participatory modeling facilitates the co-production of knowledge and action by engaging stakeholders in research. However, the spatial dimensions of socio-environmental systems and decision-making are challenging to incorporate in participatory models, as developing interactive geospatial models requires specialized knowledge. Yet, many of society’s most pressing and complex socio-environmental problems require participatory modeling that is geospatial. Existing interactive online applications have broadened the audiences who can engage with geospatial models, but often do not provide a robust framework for interactive model development. Here, we develop an open-source platform, OpenPlains, to address barriers to participation in geospatial modeling by enabling researchers to develop interactive models that remove barriers to data aggregation and user engagement. OpenPlains consists of six new open-source libraries: OpenPlains, django-actina, grass-js-client, react-openplains, react-ol, and openplains-cli. We demonstrate OpenPlains through two web applications that work anywhere in the contiguous United States: a spatial–temporal watershed analysis application and an urban growth forecasting application.}, journal={ENVIRONMENTAL MODELLING & SOFTWARE}, publisher={Elsevier BV}, author={White, Corey T. and Petrasova, Anna and Petras, Vaclav and Tateosian, Laura G. and Vukomanovic, Jelena and Mitasova, Helena and Meentemeyer, Ross K.}, year={2023}, month={Sep} }
 @article{vivek nanda_baran_tateosian_nelson_hu_2023, title={Classification of tree forms in aerial LiDAR point clouds using CNN for 3D tree modelling}, volume={44}, ISSN={["1366-5901"]}, DOI={10.1080/01431161.2023.2282405}, abstractNote={ABSTRACT Three-dimensional models of trees that correspond to the real-world forms of the trees on the ground are used in urban planning, solar power estimation, and other disciplines. Previous studies have focused on generating 3D tree models from high-density point cloud data such as Terrestrial Laser Scanning (TLS) data, which is expensive and limited to small spatial extents. However, there has been limited exploration of inexpensive solutions to model trees over large spatial extents. The goal of this study is to use widely available discrete return Airborne Laser Scanning (ALS) data along with field-captured tree photographs and Google Street View (GSV) images to develop 3D equivalents of trees over larger spatial extents. To this end, we designed a process to assign representative 3D models for individual trees in discrete return ALS point clouds. This study demonstrates the use of a Convolutional Neural Network (CNN) model and 3D models generated with Structure from Motion (SfM) for the realistic modelling of deciduous non-overlapping trees from discrete return ALS data. We classified and labelled the crown shapes of deciduous trees in a study area into four classes based on GSV images of trees. We delineated and segmented non-overlapping deciduous trees from ALS data and reduced them to 2D images using voxel point counts. Next, we trained a CNN architecture to match the 2D images to the corresponding classes observed from GSV images. For each class, we created a representative 3D tree model using field-captured circumnavigational photos of trees and SfM. To demonstrate 3D visualization using the 3D tree models, we created a 3D visualization of the trees surrounding a parking lot. The trained CNN model from this study can be used to classify non-overlapping deciduous trees from discrete return ALS data and subsequently visualize near-realistic 3D tree models of trees.}, number={22}, journal={INTERNATIONAL JOURNAL OF REMOTE SENSING}, author={Vivek Nanda, Vishnu Mahesh and Baran, Perver and Tateosian, Laura and Nelson, Stacy A. C. and Hu, Jianxin}, year={2023}, month={Nov}, pages={7156–7186} }
 @article{schrum_jameson_tateosian_blank_wegmann_nelson_2023, title={Curvature Weighted Decimation: A Novel, Curvature-Based Approach to Improved Lidar Point Decimation of Terrain Surfaces}, volume={3}, ISSN={2673-7418}, url={http://dx.doi.org/10.3390/geomatics3010015}, DOI={10.3390/geomatics3010015}, abstractNote={Increased availability of QL1/QL2 Lidar terrain data has resulted in large datasets, often including large quantities of redundant points. Because of these large memory requirements, practitioners often use decimation to reduce the number of points used to create models. This paper introduces a novel approach to improve decimation, thereby reducing the total count of ground points in a Lidar dataset while retaining more accuracy than Random Decimation. This reduction improves efficiency of downstream processes while maintaining output quality nearer to the undecimated dataset. Points are selected for retention based on their discrete curvature values computed from the mesh geometry of the TIN model of the points. Points with higher curvature values are preferred for retention in the resulting point cloud. We call this technique Curvature Weighted Decimation (CWD). We implement CWD in a new free, open-source software tool, CogoDN, which is also introduced in this paper. We evaluate the effectiveness of CWD against Random Decimation by comparing the resulting introduced error values for the two kinds of decimation over multiple decimation percentages, multiple statistical types, and multiple terrain types. The results show that CWD reduces introduced error values over Random Decimation when 15 to 50% of the points are retained.}, number={1}, journal={Geomatics}, publisher={MDPI AG}, author={Schrum, Paul T., Jr. and Jameson, Carter D. and Tateosian, Laura G. and Blank, Gary B. and Wegmann, Karl W. and Nelson, Stacy A. C.}, year={2023}, month={Mar}, pages={266–289} }
 @article{montgomery_walden-schreiner_saffer_jones_seliger_worm_tateosian_shukunobe_kumar_meentemeyer_2023, title={Forecasting global spread of invasive pests and pathogens through international trade}, volume={14}, ISSN={["2150-8925"]}, url={http://dx.doi.org/10.1002/ecs2.4740}, DOI={10.1002/ecs2.4740}, abstractNote={Abstract Non‐native plant pests and pathogens threaten biodiversity, ecosystem function, food security, and economic livelihoods. As new invasive populations establish, often as an unintended consequence of international trade, they can become additional sources of introductions, accelerating global spread through bridgehead effects. While the study of non‐native pest spread has used computational models to provide insights into drivers and dynamics of biological invasions and inform management, efforts have focused on local or regional scales and are challenged by complex transmission networks arising from bridgehead population establishment. This paper presents a flexible spatiotemporal stochastic network model called PoPS (Pest or Pathogen Spread) Global that couples international trade networks with core drivers of biological invasions—climate suitability, host availability, and propagule pressure—quantified through open, globally available databases to forecast the spread of non‐native plant pests. The modular design of the framework makes it adaptable for various pests capable of dispersing via human‐mediated pathways, supports proactive responses to emerging pests when limited data are available, and enables forecasts at different spatial and temporal resolutions. We demonstrate the framework using a case study of the invasive planthopper spotted lanternfly ( Lycorma delicatula ). The model was calibrated with historical, known spotted lanternfly introductions to identify potential bridgehead populations that may contribute to global spread. This global view of phytosanitary pandemics provides crucial information for anticipating biological invasions, quantifying transport pathways risk levels, and allocating resources to safeguard plant health, agriculture, and natural resources.}, number={12}, journal={ECOSPHERE}, author={Montgomery, Kellyn and Walden-Schreiner, Chelsey and Saffer, Ariel and Jones, Chris and Seliger, Benjamin J. and Worm, Thom and Tateosian, Laura and Shukunobe, Makiko and Kumar, Sunil and Meentemeyer, Ross K.}, year={2023}, month={Dec} }
 @article{tateosian_saffer_walden-schreiner_shukunobe_2023, title={Plant pest invasions, as seen through news and social media}, volume={100}, ISSN={["1873-7587"]}, DOI={10.1016/j.compenvurbsys.2022.101922}, abstractNote={Invasion by exotic pests into new geographic areas can cause major disturbances in forest and agricultural systems. Early response can greatly improve containment efforts, underscoring the importance of collecting up-to-date information about the locations where pest species are being observed. However, existing invasive species databases have limitations in both extent and rapidity. The spatial extent is limited by costs and there are delays between species establishment, official recording, and consolidation. Local online news outlets have the potential to provide supplemental spatial coverage worldwide and social media has the potential to provide direct observations and denser historical data for modeling. Gathering data from these online sources presents its own challenges and their potential contribution to historical tracking of pest invasions has not previously been tested. To this end, we examine the practical considerations for using three online aggregators, the Global Database of Events, Language and Tone (GDELT), Google News, and a commercial media listening platform, Brandwatch, to support pest biosurveillance. Using these tools, we investigate the presence and nature of cogent mentions of invasive species in these sources by conducting case studies of online news and Twitter excerpts regarding two invasive plant pests, Spotted Lanternfly and Tuta absoluta. Our results using past data demonstrate that online news and social media may provide valuable data streams to supplement official sources describing pest invasions.}, journal={COMPUTERS ENVIRONMENT AND URBAN SYSTEMS}, author={Tateosian, Laura G. and Saffer, Ariel and Walden-Schreiner, Chelsey and Shukunobe, Makiko}, year={2023}, month={Mar} }
 @article{huang_floyd_tateosian_hipp_2022, title={Exploring public values through Twitter data associated with urban parks pre- and post- COVID-19}, volume={227}, ISSN={["1872-6062"]}, DOI={10.1016/j.landurbplan.2022.104517}, abstractNote={Since school and business closures due to the evolving COVID-19 outbreak, urban parks have been a popular destination, offering spaces for daily fitness activities and an escape from the home environment. There is a need for evidence for parks and recreation departments and agencies to base decisions when adapting policies in response to the rapid change in demand and preferences during the pandemic. The application of social media data analytic techniques permits a qualitative and quantitative big-data approach to gain unobtrusive and prompt insights on how parks are valued. This study investigates how public values associated with NYC parks has shifted between pre- COVID (i.e., from March 2019 to February 2020) and post- COVID (i.e., from March 2020 to February 2021) through a social media microblogging platform –Twitter. A topic modeling technique for short text identified common traits of the changes in Twitter topics regarding impressions and values associated with the parks over two years. While the NYC lockdown resulted in much fewer social activities in parks, some parks continued to be valued for physical activity and nature contact during the pandemic. Concerns about people not keeping physical distance arose in parks where frequent human interactions and crowding seemed to cause a higher probability of the coronavirus transmission. This study demonstrates social media data could be used to capture park values and be specific per park. Results could inform park management during disruptions when use is altered and the needs of the public may be changing.}, journal={LANDSCAPE AND URBAN PLANNING}, author={Huang, Jing-Huei and Floyd, Myron F. and Tateosian, Laura G. and Hipp, J. Aaron}, year={2022}, month={Nov} }
 @article{ristaino_anderson_bebber_brauman_cunniffe_fedoroff_finegold_garrett_gilligan_jones_et al._2021, title={The persistent threat of emerging plant disease pandemics to global food security}, volume={118}, ISSN={["0027-8424"]}, url={https://doi.org/10.1073/pnas.2022239118}, DOI={10.1073/pnas.2022239118}, abstractNote={Plant disease outbreaks are increasing and threaten food security for the vulnerable in many areas of the world. Now a global human pandemic is threatening the health of millions on our planet. A stable, nutritious food supply will be needed to lift people out of poverty and improve health outcomes. Plant diseases, both endemic and recently emerging, are spreading and exacerbated by climate change, transmission with global food trade networks, pathogen spillover, and evolution of new pathogen lineages. In order to tackle these grand challenges, a new set of tools that include disease surveillance and improved detection technologies including pathogen sensors and predictive modeling and data analytics are needed to prevent future outbreaks. Herein, we describe an integrated research agenda that could help mitigate future plant disease pandemics.}, number={23}, journal={PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA}, publisher={Proceedings of the National Academy of Sciences}, author={Ristaino, Jean B. and Anderson, Pamela K. and Bebber, Daniel P. and Brauman, Kate A. and Cunniffe, Nik J. and Fedoroff, Nina V and Finegold, Cambria and Garrett, Karen A. and Gilligan, Christopher A. and Jones, Christopher M. and et al.}, year={2021}, month={Jun} }
 @article{yoshizumi_coffer_collins_gaines_gao_jones_mcgregor_mcquillan_perin_tomkins_et al._2020, title={A Review of Geospatial Content in IEEE Visualization Publications}, DOI={10.1109/VIS47514.2020.00017}, abstractNote={Geospatial analysis is crucial for addressing many of the world’s most pressing challenges. Given this, there is immense value in improving and expanding the visualization techniques used to communicate geospatial data. In this work, we explore this important intersection – between geospatial analytics and visualization – by examining a set of recent IEEE VIS Conference papers (a selection from 2017-2019) to assess the inclusion of geospatial data and geospatial analyses within these papers. After removing the papers with no geospatial data, we organize the remaining literature into geospatial data domain categories and provide insight into how these categories relate to VIS Conference paper types. We also contextualize our results by investigating the use of geospatial terms in IEEE Visualization publications over the last 30 years. Our work provides an understanding of the quantity and role of geospatial subject matter in recent IEEE VIS publications and supplies a foundation for future meta-analytical work around geospatial analytics and geovisualization that may shed light on opportunities for innovation.}, journal={2020 IEEE VISUALIZATION CONFERENCE - SHORT PAPERS (VIS 2020)}, author={Yoshizumi, Alexander and Coffer, Megan M. and Collins, Elyssa L. and Gaines, Mollie D. and Gao, Xiaojie and Jones, Kate and McGregor, Ian R. and McQuillan, Katie A. and Perin, Vinicius and Tomkins, Laura M. and et al.}, year={2020}, pages={51–55} }
 @inproceedings{yoshizumi_coffer_collins_gaines_gao_jones_mcgregor_mcquillan_perin_worm_et al._2020, title={A Review of Geospatial Content in IEEE Visualization Publications}, booktitle={Proceedings IEEE Visualization 2020}, author={Yoshizumi, A. and Coffer, M. and Collins, E. and Gaines, M. and Gao, X. and Jones, K. and McGregor, I. and McQuillan, K. and Perin, V. and Worm, T. and et al.}, year={2020}, month={Oct} }
 @inproceedings{vivek nanda_tateosian_baran_2020, title={GIS-Based Estimation of Seasonal Solar Energy Potential for Parking Lots and Roads}, booktitle={IEEE Greentech Conference Proceedings}, author={Vivek Nanda, V.M. and Tateosian, L. and Baran, P.}, year={2020} }
 @article{tateosian_glatz_shukunobe_2020, title={Story-telling maps generated from semantic representations of events}, volume={39}, ISSN={["1362-3001"]}, DOI={10.1080/0144929X.2019.1569162}, abstractNote={ABSTRACT Narratives enable readers to assimilate disparate facts. Accompanying maps can make the narratives even more accessible. As work in computer science has begun to generate stories from low-level event/activity data, there is a need for systems that complement these tools to generate maps illustrating spatial components of these stories. While traditional maps display static spatial relationships, story maps need to not only dynamically display relationships based on the flow of the story but also display character perceptions and intentions. In this work, we study cartographic illustrations of historical battles to design a map generation system for reports produced from a multiplayer battle game log. We then create a story and ask viewers to describe mapped events and rate their own descriptions relative to intended interpretations. Some viewers received training prior to seeing the story, which was shown to be effective, though training may have been unnecessary for certain map types. Self-rating correlated highly with expert ratings, revealing an efficient proxy for expert analysis of map interpretability, a shortcut for determining if training is needed for story-telling maps or other novel visualisation techniques. The study's semantic questions and feedback solicitation demonstrate a process for identifying user-centric improvements to story-telling map design.}, number={4}, journal={BEHAVIOUR & INFORMATION TECHNOLOGY}, author={Tateosian, Laura and Glatz, Michelle and Shukunobe, Makiko}, year={2020}, month={Apr}, pages={391–413} }
 @article{kozik_tateosian_healey_enns_2019, title={Impressionism-Inspired Data Visualizations Are Both Functional and Liked}, volume={13}, ISSN={["1931-390X"]}, DOI={10.1037/aca0000175}, number={3}, journal={PSYCHOLOGY OF AESTHETICS CREATIVITY AND THE ARTS}, author={Kozik, Pavel and Tateosian, Laura G. and Healey, Christopher G. and Enns, James T.}, year={2019}, month={Aug}, pages={266–276} }
 @article{walden-schreiner_leung_tateosian_2018, title={Digital footprints: Incorporating crowdsourced geographic information for protected area management}, volume={90}, ISSN={["1873-7730"]}, url={https://doi.org/10.1016/j.apgeog.2017.11.004}, DOI={10.1016/j.apgeog.2017.11.004}, abstractNote={Biodiversity loss driven by anthropogenic pressures highlights the importance of conservation efforts in protected areas globally. Protected areas are also locations providing myriad ecosystem services, including recreation and tourism. Advancements in mobile and web technologies have expanded the capabilities and accessibility of crowdsourced spatial content increasingly leveraged for research. This study explores the use of crowdsourced geographic information to model, at varying temporal scales, spatial patterns of visitor use and identify factors contributing to distribution patterns in a dynamic landscape, Hawaii Volcanoes National Park (Hawaii, USA). Specifically, this study integrated geotagged photo metadata publicly shared on Flickr with raster data about infrastructure and natural environmental using MaxEnt modelling. Infrastructure designated for visitor use (i.e., roads, trails) contributed most to models of visitor distribution for all years and seasons. During the spring months, elevation was also a top contributing variable to the model. Crowdsourced data provided empirical assessments of covariates associated with visitor distributions, highlighting how changes in infrastructure and environmental factors may influence visitor use, and therefore resource pressures, to help researchers, managers, and planners with efforts to mitigate negative impacts.}, journal={APPLIED GEOGRAPHY}, publisher={Elsevier BV}, author={Walden-Schreiner, Chelsey and Leung, Yu-Fai and Tateosian, Laura}, year={2018}, month={Jan}, pages={44–54} }
 @inproceedings{tateosian_tabrizian_2017, title={Blending tools for a Smooth Introduction to 3D Geovisualization}, booktitle={Pedagogy of Data Visualization Workshop (PDVW)}, author={Tateosian, L. and Tabrizian, P.}, year={2017}, month={Oct} }
 @article{tateosian_glatz_shukunobe_chopra_2017, title={GazeGIS: A Gaze-Based Reading and Dynamic Geographic Information System}, ISBN={["978-3-319-47023-8"]}, ISSN={["1612-3786"]}, DOI={10.1007/978-3-319-47024-5_8}, abstractNote={Location is an important component of a narrative. Mapped place names provide vital geographical, economic, historical, political, and cultural context for the text. Online sources such as news articles, travel logs, and blogs frequently refer to geographic locations, but often these are not mapped. When a map is provided, the reader is still responsible for matching references in the text with map positions. As they read a place name within the text, readers must locate its map position, then find their place again in the text to resume reading, and repeat this for each toponym. We propose a gaze-based reading and dynamic geographic information system (GazeGIS) which uses eye tracking and geoparsing to enable a more cohesive reading experience by dynamically mapping locations just as they are encountered within the text. We developed a prototype GazeGIS application and demonstrated its application to several narrative passages. We conducted a study in which participants read text passages using the system and evaluated their experience. We also explored an application for intelligence analysis and discuss how experts in this domain envision its use. Layman and intelligence expert evaluations indicate a positive reception for this new reading paradigm. This could change the way we read online news and e-books, the way school children study political science and geography, the way officers study military history, the way intelligence analysts consume reports, and the way we plan our next vacation.}, journal={EYE TRACKING AND VISUALIZATION: FOUNDATIONS, TECHNIQUES, AND APPLICATIONS, ETVIS 2015}, author={Tateosian, Laura G. and Glatz, Michelle and Shukunobe, Makiko and Chopra, Pankaj}, year={2017}, pages={129–147} }
 @book{tateosian_2015, place={New York, NY}, title={Python for ArcGIS}, ISBN={9783319183985, 9783319183978}, DOI={10.1007/978-3-319-18398-5}, publisher={Springer}, author={Tateosian, L.}, year={2015} }
 @book{hardin_mitasova_tateosian_overton_2014, place={New York, NY}, title={GIS-based Analysis of Coastal Lidar Time-Series}, ISBN={9781493918348 9781493918355}, DOI={10.1007/978-1-4939-1835-5}, abstractNote={This SpringerBrief presents the principles, methods, and workflows for processing and analyzing coastal LiDAR data time-series. Robust methods for computing high resolution digital elevation models (D}, publisher={Springer}, author={Hardin, E. and Mitasova, H. and Tateosian, L. and Overton, M.}, year={2014} }
 @article{tateosian_mitasova_thakur_hardin_russ_blundell_2014, title={Visualizations of coastal terrain time series}, volume={13}, ISSN={["1473-8724"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84906534191&partnerID=MN8TOARS}, DOI={10.1177/1473871613487086}, abstractNote={ In coastal regions, water, wind, gravitation, vegetation, and human activity continuously alter landscape surfaces. Visualizations are important for understanding coastal landscape evolution and its driving processes. Visualizing change in highly dynamic coastal terrain poses a formidable challenge; the combination of natural and anthropogenic forces leads to cycles of retreat and recovery and complex morphology of landforms. In recent years, repeated high-resolution laser terrain scans have generated a time series of point cloud data that represent landscapes at snapshots in time, including the impacts of major storms. In this article, we build on existing approaches for visualizing spatial–temporal data to create a collection of perceptual visualizations to support coastal terrain evolution analysis. We extract terrain features and track their migration; we derive temporal summary maps and heat graphs that quantify the pattern of elevation change and sediment redistribution and use the space–time cube concept to create visualizations of terrain evolution. The space–time cube approach allows us to represent shoreline evolution as an isosurface extracted from a voxel model created by stacking time series of digital elevation models. We illustrate our approach on a series of Light Detection and Ranging surveys of sandy North Carolina barrier islands. Our results reveal terrain changes of shoreline and dune ridge migration, dune breaches and overwash, the formation of new dune ridges, and the construction and destruction of homes, changes which are due to erosion and accretion, hurricanes, and human activities. These events are all visualized within their geographic and temporal contexts. }, number={3}, journal={INFORMATION VISUALIZATION}, author={Tateosian, Laura and Mitasova, Helena and Thakur, Sidharth and Hardin, Eric and Russ, Emily and Blundell, Bruce}, year={2014}, month={Jul}, pages={266–282} }
 @article{thakur_tateosian_mitasova_hardin_overton_2013, title={SUMMARY VISUALIZATIONS FOR COASTAL SPATIAL-TEMPORAL DYNAMICS}, volume={3}, ISSN={["2152-5099"]}, DOI={10.1615/int.j.uncertaintyquantification.2012003969}, abstractNote={Digital scans of dynamic terrains such as coastal regions are now being gathered at high spatial and temporal resolution. Although standard tools based on geographic information systems (GIS) are indispensable for analyzing geospatial data, they have limited support to display time-dependent changes in data and information such as statistical distributions and uncertainty in data. We present a set of techniques for visually summarizing the dynamics of coastal dunes. We visualize summary statistics of important data attributes and risk or vulnerability indices as functions of both spatial and temporal dimensions in our data and represent uncertainty in the data set. We apply standard techniques, the space time cube and clustering, in novel ways to the domain of geomorphology. We combine surface-mapping and imagery with summary visualizations to retain important geographical context in the visualizations and reduce clutter due to direct plotting of statistical data in displays of geospatial information. We also address some issues pertaining to visualization of summary statistics for geographical regions at varying scales. We demonstrate visualization tools on time series of elevation models from the Outer Banks of North Carolina and observe temporal-spatial trends therein.}, number={3}, journal={INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION}, author={Thakur, Sidharth and Tateosian, Laura and Mitasova, Helena and Hardin, Eric and Overton, Margery}, year={2013}, pages={241–253} }
 @article{supak_luo_tateosian_fang_harrell_harrelson_bailey_devine_2012, title={Who's Watching Your Food? A Flexible Framework for Public Health Monitoring1}, volume={16}, ISSN={1361-1682}, url={http://dx.doi.org/10.1111/j.1467-9671.2012.01309.x}, DOI={10.1111/j.1467-9671.2012.01309.x}, abstractNote={Abstract}, number={2}, journal={Transactions in GIS}, publisher={Wiley}, author={Supak, Stacy and Luo, Huan and Tateosian, Laura and Fang, Kunsheng and Harrell, Julia and Harrelson, Cris and Bailey, Andrew D. and Devine, Hugh}, year={2012}, month={Apr}, pages={89–104} }
 @article{tateosian_mitasova_harmon_fogleman_weaver_harmon_2010, title={TanGeoMS: Tangible Geospatial Modeling System}, volume={16}, ISSN={["1941-0506"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-78149238565&partnerID=MN8TOARS}, DOI={10.1109/tvcg.2010.202}, abstractNote={We present TanGeoMS, a tangible geospatial modeling visualization system that couples a laser scanner, projector, and a flexible physical three-dimensional model with a standard geospatial information system (GIS) to create a tangible user interface for terrain data. TanGeoMS projects an image of real-world data onto a physical terrain model. Users can alter the topography of the model by modifying the clay surface or placing additional objects on the surface. The modified model is captured by an overhead laser scanner then imported into a GIS for analysis and simulation of real-world processes. The results are projected back onto the surface of the model providing feedback on the impact of the modifications on terrain parameters and simulated processes. Interaction with a physical model is highly intuitive, allowing users to base initial design decisions on geospatial data, test the impact of these decisions in GIS simulations, and use the feedback to improve their design. We demonstrate the system on three applications: investigating runoff management within a watershed, assessing the impact of storm surge on barrier islands, and exploring landscape rehabilitation in military training areas.}, number={6}, journal={IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS}, author={Tateosian, Laura G. and Mitasova, Helena and Harmon, Brendan A. and Fogleman, Brent and Weaver, Katherine and Harmon, Russel S.}, year={2010}, pages={1605–1612} }
 @inproceedings{tateosian_healey_enns_2007, title={Engaging viewers through nonphotorealistic visualizations}, ISBN={9781595936240}, url={http://dx.doi.org/10.1145/1274871.1274886}, DOI={10.1145/1274871.1274886}, abstractNote={Research in human visual cognition suggests that beautiful images can engage the visual system, encouraging it to linger in certain locations in an image and absorb subtle details. By developing aesthetically pleasing visualizations of data, we aim to engage viewers and promote prolonged inspection, which can lead to new discoveries within the data. We present three new visualization techniques that apply painterly rendering styles to vary interpretational complexity (IC), indication and detail (ID), and visual complexity (VC), image properties that are important to aesthetics. Knowledge of human visual perception and psychophysical models of aesthetics provide the theoretical basis for our designs. Computational geometry and nonphotorealistic algorithms are used to preprocess the data and render the visualizations. We demonstrate the techniques with visualizations of real weather and supernova data.}, booktitle={Proceedings of the 5th international symposium on Non-photorealistic animation and rendering - NPAR '07}, publisher={ACM Press}, author={Tateosian, Laura G. and Healey, Christopher G. and Enns, James T.}, year={2007} }
 @inproceedings{tateosian_dennis_healey_2006, title={Stevens dot patterns for 2D flow visualization}, ISBN={1595934294}, url={http://dx.doi.org/10.1145/1140491.1140511}, DOI={10.1145/1140491.1140511}, abstractNote={This paper describes a new technique to visualize 2D flow fields with a sparse collection of dots. A cognitive model proposed by Kent Stevens describes how spatially local configurations of dots are processed in parallel by the low-level visual system to perceive orientations throughout the image. We integrate this model into a visualization algorithm that converts a sparse grid of dots into patterns that capture flow orientations in an underlying flow field. We describe how our algorithm supports large flow fields that exceed the capabilities of a display device, and demonstrate how to include properties like direction and velocity in our visualizations. We conclude by applying our technique to 2D slices from a simulated supernova collapse.}, booktitle={Proceedings of the 3rd symposium on Applied perception in graphics and visualization  - APGV '06}, publisher={ACM Press}, author={Tateosian, Laura G. and Dennis, Brent M. and Healey, Christopher G.}, year={2006} }
 @article{rhyne_dennis_kocherlakota_sawant_tateosian_healey_2005, title={Designing a visualization framework for multidimensional data}, volume={25}, number={6}, journal={IEEE Computer Graphics and Applications}, author={Rhyne, T. M. and Dennis, B. and Kocherlakota, S. and Sawant, A. and Tateosian, L. and Healey, C. G.}, year={2005}, pages={15-} }