Name: trajectory data analyses for pedestrian space-time activity study
Uploaded: 2013-02-25T12:03:00
Description: Watch this Scientific Journal Video about Trajectory Data Analyses for Pedestrian Space-time Activity Study at JoVE.com

यह काम NIH अनुदान 1R03AI090465 द्वारा वित्त पोषित है.

1. डेटा प्राप्त करने <ol><li> प्रक्षेपवक्र डेटा Handheld जीपीएस यूनिट, जीपीएस सक्षम स्मार्ट फोन ट्रैकिंग अनुप्रयोगों, के रूप में के रूप में अच्छी तरह से हमारे अध्ययन में कार्यरत एक, एक वाणिज्यिक बच्चे ट्रैकर डिव...

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	<li>Stoddard, S. T., Morrison, A. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+role+of+human+movement+in+the+transmission+of+vector-borne+pathogens.">The role of human movement in the transmission of vector-borne pathogens.</a> PLoS Negl. Trop. Dis. 3 (7), e10 (2009).</li><li>Morens, D. M., Folkers, G. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+challenge+of+emerging+and+re-emerging+infectious+diseases.">The challenge of emerging and re-emerging infectious diseases.</a> Nature. 430, 242-249 (2004).</li><li>Viboud, C., Bjornstad, O. N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Synchrony,+waves,+and+spatial+hierarchies+in+the+spread+of+influenza.">Synchrony, waves, and spatial hierarchies in the spread of influenza.</a> Science. 312, 447-451 (2006).</li><li>Shoval, N., Isaacson, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Application+of+tracking+technologies+to+the+study+of+pedestrian+spatial+behaviour.">The Application of tracking technologies to the study of pedestrian spatial behaviour.</a> The Professional Geographer. 58 (2), 172-183 (2006).</li><li>Yu, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Spatio-temporal+GIS+design+for+exploring+interactions+of+human+activities.">Spatio-temporal GIS design for exploring interactions of human activities.</a> Cartography and Geographic Information Science. 33 (1), 3-19 (2006).</li><li>Kwan, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Interactive+geovisualization+of+activity-travel+patterns+using+three-dimensional+geographical+information+systems:+a+methodological+exploration+with+a+large+data+set.">Interactive geovisualization of activity-travel patterns using three-dimensional geographical information systems: a methodological exploration with a large data set.</a> Transportation Research Part C. 8, 185-203 (2000).</li><li>Dem&#353;ar, U., Virrantaus, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Space-time+density+of+trajectories:+exploring+spatio-temporal+patterns+in+movement+data.">Space-time density of trajectories: exploring spatio-temporal patterns in movement data.</a> International Journal of Geographical Information Science. 24 (10), 1527-1542 (2010).</li><li>Kraak, M., Koussoulakous, A., Fisher, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> A visualization environment for the space-time cube. , 189-200 (2004).</li><li>MacEachren, A. M., Polsky, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Visualizing+spatial+relationships+among+health,+environmental,+and+demographic+statistics:+interface+design+issues.">Visualizing spatial relationships among health, environmental, and demographic statistics: interface design issues.</a> , 880-887 (1997).</li><li>Levory, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Display+of+surfaces+from+volume+data.">Display of surfaces from volume data.</a> IEEE Computer Graphics and Application. 8 (5), 29-37 (1998).</li><li>Drebin, R. A., Carpenter, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Volume+Rendering.">Volume Rendering.</a> Computer Graphics. , (1998).</li><li>Lee, W., Krumm, J., Zheng, Y., Zhou, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Trajectory+preprocessing.">Trajectory preprocessing.</a> Computing with Spatial Trajectories. , 3-34 (2011).</li><li>Han, B., Comaniciu, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sequential+kernel+density+approximation+and+its+application+to+real-time+visual+tracking.">Sequential kernel density approximation and its application to real-time visual tracking.</a> IEEE Transactions on Pattern Analysis and Machine Intelligence. , (2007).</li></ol>

हम ArcGIS के ऐड - इन तंत्र का इस्तेमाल करने के लिए इंटरफ़ेस का विकास. सभी इंटरैक्टिव कार्यों का उपयोग लागू किया गया सी + +. सभी स्वत: प्रसंस्करण और विश्लेषण कार्यों अजगर का उपयोग कर विकसित किया गया. AGP...

<table border="1"><tbody><tr><td> अभिकर्मक के नाम </td><td> कंपनी </td><td> सूचीपत्र संख्या </td><td> टिप्पणियां (वैकल्पिक) </td></tr><tr><td> WorldTracker GPRS </td><td> विश्व ट्रैकिंग </td><td></td><td></td></tr><tr><td> विश्लेषण को चलाने के लिए एक व्यक्तिगत कंप्यूटर </td><td></td><td></td><td></td></tr><tr><td> ArcGIS सॉफ्टवेयर </td><td> ESRI </td><td></td><td></td></tr><tr><td> प्रक्षेपवक्र विश्लेषक एक्सटेंशन </td><td></td><td></td><td></td></tr></tbody></table>

trajectory data analyses for pedestrian space-time activity study

It is well recognized that human movement in the spatial and temporal dimensions has direct influence on disease transmission1-3. An infectious disease typically spreads via contact between infected and susceptible individuals in their overlapped activity spaces. Therefore, daily mobility-activity information can be used as an indicator to measure exposures to risk factors of infection. However, a major difficulty and thus the reason for paucity of studies of infectious disease transmission at the micro scale arise from the lack of detailed individual mobility data. Previously in transportation and tourism research detailed space-time activity data often relied on the time-space diary technique, which requires subjects to actively record their activities in time and space. This is highly demanding for the participants and collaboration from the participants greatly affects the quality of data4.
Modern technologies such as GPS and mobile communications have made possible the automatic collection of trajectory data. The data collected, however, is not ideal for modeling human space-time activities, limited by the accuracies of existing devices. There is also no readily available tool for efficient processing of the data for human behavior study. We present here a suite of methods and an integrated ArcGIS desktop-based visual interface for the pre-processing and spatiotemporal analyses of trajectory data. We provide examples of how such processing may be used to model human space-time activities, especially with error-rich pedestrian trajectory data, that could be useful in public health studies such as infectious disease transmission modeling.
The procedure presented includes pre-processing, trajectory segmentation, activity space characterization, density estimation and visualization, and a few other exploratory analysis methods. Pre-processing is the cleaning of noisy raw trajectory data. We introduce an interactive visual pre-processing interface as well as an automatic module. Trajectory segmentation5 involves the identification of indoor and outdoor parts from pre-processed space-time tracks. Again, both interactive visual segmentation and automatic segmentation are supported. Segmented space-time tracks are then analyzed to derive characteristics of one's activity space such as activity radius etc. Density estimation and visualization are used to examine large amount of trajectory data to model hot spots and interactions. We demonstrate both density surface mapping6 and density volume rendering7. We also include a couple of other exploratory data analyses (EDA) and visualizations tools, such as Google Earth animation support and connection analysis. The suite of analytical as well as visual methods presented in this paper may be applied to any trajectory data for space-time activity studies.

प्रक्षेपवक्र डेटा Kean विश्वविद्यालय (न्यू जर्सी, संयुक्त राज्य अमरीका) से 2010 के वसंत में स्नातक छात्रों को स्वयं सेवा के द्वारा एकत्र की गई थी. उद्देश्य छात्रों को जो इन्फ्लूएंजा जो नहीं की तुलना में पकड?...

Watch this Scientific Journal Video about Trajectory Data Analyses for Pedestrian Space-time Activity Study at JoVE.com

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Spatiotemporal प्रसंस्करण विधियों की एक सूट है कि मॉडलिंग पैदल यात्री अंतरिक्ष समय गतिविधियों के प्रयोजन के लिए, एक जीपीएस डिवाइस का उपयोग कर एकत्र रूप में मानव प्रक्षेपवक्र डेटा का विश्लेषण करने के लिए प्रस्तुत कर रहे हैं.

प्रक्षेपवक्र पैदल गतिविधि अंतरिक्ष समय अध्ययन के लिए डाटा विश्लेषण

It is well recognized that human movement in the  spatial and temporal dimensions has direct influence on disease transmission1-3.  An infectious disease ...

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