Open Geospatial Tools for Movement Data Exploration

Since the movement data exist, there have been approaches to collect and analyze them to get insights. This kind of data is often heterogeneous, multiscale and multi-temporal. Those interested in spatio-temporal patterns of movement data do not gain insights from textual descriptions. Therefore, visualization is required. As spatio-temporal movement data can be complex because size and characteristics, it is even challenging to create an overview of it. Plotting all the data on the screen will not be the solution as it likely will result into cluttered images where no data exploration is possible. To ensure that users will receive the information they are interested in, it is important to provide a graphical data representation environment where exploration to gain insights are possible not only in the overall level but at sub-levels as well. A dashboard would be a solution the representation of heterogeneous spatio- temporal data. It provides an overview and helps to unravel the complexity of data by splitting data in multiple data representation views. The adaptability of dashboard will help to reveal the information which cannot be seen in the overview.

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Visual Analytics for Characterizing Mobility Aspects of Urban Context

Urban Informatics - The Urban Book Series ◽

10.1007/978-981-15-8983-6_40 ◽

2021 ◽

pp. 727-755

Author(s):

Gennady Andrienko ◽

Natalia Andrienko ◽

Fabian Patterson ◽

Siming Chen ◽

Robert Weibel ◽

...

Keyword(s):

Visual Analytics ◽

Research Topic ◽

Data Exploration ◽

Spatiotemporal Data ◽

Multiple Perspectives ◽

Numerous Application ◽

Urban Context ◽

Spatial Objects ◽

Movement Data ◽

Spatial Locations

AbstractVisual analytics science develops principles and methods for efficient human–computer collaboration in solving complex problems. Visual and interactive techniques are used to create conditions in which human analysts can effectively utilize their unique capabilities: the power of seeing, interpreting, linking, and reasoning. Visual analytics research deals with various types of data and analysis tasks from numerous application domains. A prominent research topic is analysis of spatiotemporal data, which may describe events occurring at different spatial locations, changes of attribute values associated with places or spatial objects, or movements of people, vehicles, or other objects. Such kinds of data are abundant in urban applications. Movement data are a quintessential type of spatiotemporal data because they can be considered from multiple perspectives as trajectories, as spatial events, and as changes of space-related attribute values. By example of movement data, we demonstrate the utilization of visual analytics techniques and approaches in data exploration and analysis.

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Using Tongue, Lip, and Jaw Movement Data to Improve Diagnostic Accuracy of ALS

10.1044/cred-dsa-bts-004 ◽

2014 ◽

Vol 1 (1) ◽

pp. 1

Author(s):

Jordan Green

Keyword(s):

Diagnostic Accuracy ◽

Jaw Movement ◽

Movement Data

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Age Differences in Eye Movements During Reading: Degenerative Problems or Compensatory Strategy?

European Psychologist ◽

10.1027/1016-9040/a000344 ◽

2019 ◽

Vol 24 (4) ◽

pp. 297-311

Author(s):

José David Moreno ◽

José A. León ◽

Lorena A. M. Arnal ◽

Juan Botella

Keyword(s):

Eye Movements ◽

Eye Movement ◽

Meta Analysis ◽

Age Groups ◽

Behavioral Changes ◽

Aging Effects ◽

Movement Data ◽

Sentence Reading ◽

The Difference ◽

Eye Movements During Reading

Abstract. We report the results of a meta-analysis of 22 experiments comparing the eye movement data obtained from young ( Mage = 21 years) and old ( Mage = 73 years) readers. The data included six eye movement measures (mean gaze duration, mean fixation duration, total sentence reading time, mean number of fixations, mean number of regressions, and mean length of progressive saccade eye movements). Estimates were obtained of the typified mean difference, d, between the age groups in all six measures. The results showed positive combined effect size estimates in favor of the young adult group (between 0.54 and 3.66 in all measures), although the difference for the mean number of fixations was not significant. Young adults make in a systematic way, shorter gazes, fewer regressions, and shorter saccadic movements during reading than older adults, and they also read faster. The meta-analysis results confirm statistically the most common patterns observed in previous research; therefore, eye movements seem to be a useful tool to measure behavioral changes due to the aging process. Moreover, these results do not allow us to discard either of the two main hypotheses assessed for explaining the observed aging effects, namely neural degenerative problems and the adoption of compensatory strategies.

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Do Successor Effects in Reading Reflect Parafoveal Processing? Evidence From Corpus-Based and Experimental Eye Movement Data

PsycEXTRA Dataset ◽

10.1037/e528942014-650 ◽

2014 ◽

Author(s):

Bernhard Angele ◽

Elizabeth R. Schotter ◽

Timothy Slattery ◽

Tara L. Chaloukian ◽

Klinton Bicknell ◽

...

Keyword(s):

Eye Movement ◽

Parafoveal Processing ◽

Movement Data

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Fire Risk Analysis Using Geospatial Approach and Mitigation Measures for South-West Delhi

International Journal of Emerging Research in Management and Technology ◽

10.23956/ijermt.v6i8.128 ◽

2018 ◽

Vol 6 (8) ◽

pp. 131

Author(s):

S. K. Tomar ◽

A. Kaur ◽

H. K. Dangi ◽

T. Ghawana ◽

K. Sarma

Keyword(s):

Risk Analysis ◽

Fire Risk ◽

Population Data ◽

Fire Service ◽

Capital City ◽

Mitigation Measures ◽

Fire Risk Analysis ◽

South West ◽

Geospatial Tools ◽

Fire Stations

One of the major challenge from unplanned growth in the cities is the fire incidents posing a serious threat to life and property. Delhi, the capital city of India, has seen unplanned growth of colonies resulting in a serious concern for the relevant agencies. This paper investigates the relation between potential causes of fire incidents during 2013-2016 in South-West Delhi Division of Delhi Fire Services as part of risk analysis using the data about fire stations & their jurisdictions, incidents of fire, water reservoirs available, landuse and population data along with the divisional & sub-divisional boundaries of South-West Delhi division under Delhi Fire Service. Statistical and Geospatial tools have been used together to perform the risk analysis. The analysis reveals that difference in actual occupancy and defined landuse as a part of unplanned growth of settlements is found to be the main reason behind the major fire incidents. The suggested mitigation measures focus on legal, policy, physical & technological aspects and highlight the need to bring the systemic changes with changing scenario of demographics and infrastructure to accommodate more aspects of ground reality.

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