Overview of Themes and Trends in Space-time GIS

Haoyun Wang

Final Paper for Seminar in Geospatial Information Science

Professor Richard Lathrop and Professor Lyna Wiggins

May 7, 2019

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Contents Introduction ................................................................................................................ 2

General Overview ...................................................................................................... 2

From Conventional GIS to Space-time GIS ................................................................................ 2

Space-time GIS Literature on Web of Science ........................................................................... 3

Applications of Space-time GIS .................................................................................................. 5

Main Themes ............................................................................................................................... 6

Conceptualization and Representation ........................................................................................ 7

Analysis and Visualization .......................................................................................................... 7

Discussion .................................................................................................................................. 10

References .................................................................................................................................. 10

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Introduction During the past two decades, the community of GIScience has witnessed a growing interest in

exploring spatiotemporal data and interpreting spatiotemporal patterns. These exercises are

achieved by the availability of large datasets over time and space and advances in integrated

GPS/GIS technologies to manage, integrate, model, and visualize complex data (Nara, 2017). By

incorporating the temporal dimension into the conventional GIS framework, researchers from

diverse disciplines have contributed to the development of space-time GIS. Researchers frequently

explore two themes: 1) conceptualization and representation 2) analysis and visualization. This

paper provides a review of evolving research themes and trends in the space-time literature.

General Overview

From Conventional GIS to Space-time GIS

Conventional GIS is a platform for spatial data management, analysis and visualization in order

to investigate patterns, relationships, and situations, and ultimately support decision-making.

However, time issues were not given much consideration traditionally. Time was just listed in the

attribute table or included as one line in the property descriptions of data to indicate data collection

date or publication date.

Waldo Tobler (1970) proposed the first law of geography nearly fifty years ago, stating that

everything is related to everything else, but near things are more related than distant things. If time

is considered, the law can be revised as follows: everything is related to everything else, but near

and recent things are more related than distant things. The revised version indicates the need to

consider time issues when analyzing processes and patterns. By integrating time into GIS, we can

better understand changes of geographic information in terms of morphology, topology, attributes,

and their patterns, processes, and trends (Nara, 2017).

Borrowed from Yuan’s definition (2010), space-time GIS is defined here as GIS capable of

incorporating temporal information and analytical functions to handle both spatial and temporal

data.

Nowadays, multiple sources provide data for space-time GIS, a phenomenon not available in

the past. We can now acquire abundant geospatial data in real time or near real time from Global

Positioning Systems (GPS), geosensor networks, location-aware devices, and social media sources

(May Yuan, 2016a). Accessing and interacting with high volumes of data is indispensable to

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advanced hardware and software technologies such as cyberinfrastructure and cloud computing

facilities.

Space-time GIS Literature on Web of Science

Space-time GIS has a rich literature that continues to grow rapidly. The existing literature on

Space-time GIS was retrieved by performing a literature search using Web of Science, an online

scientific citation indexing service. The service is based on the Web of Science Core Collection,

which is a comprehensive interdisciplinary bibliographic database with article references from

journals, books, and proceedings across science and technology, the arts and humanities, and the

social sciences (Nara, 2017). To retrieve the Space-time GIS literature, the following search

keyword was used considering that some scholars use the alternative term “space-time GIS”.

Search keyword = (“Space-time GIS” in “Topics”) OR (“Spatiotemporal GIS” in “Topics”)

The research results in 1272 publications containing “space-time GIS” or “spatiotemporal GIS”

in their titles, abstracts, and keywords. Among these publications, articles account for most of the

publications (76%), followed by proceeding papers (24%), book chapters (2%) and reviews (2%).

The general published Space-time GIS appeared from the early 1990s. The number of publications

has been increasing since the 2000s, reaching the peak with 131 publications in 2015, and remains

stable at a high level in recent years (see figure 1). It is apparent that this field has stirred scholars’

interests and will continue to be explored in the near future.

As a multidisciplinary field, space-time GIS research has attracted researchers from physical

geography, human geography, computer science, information system, environmental science,

architecture, urban planning, regional science, and many other related disciplines. In grouping

publications from 1990 to present by research areas, we can see the research diversity in space-

time GIS. Figure 2 lists the top 10 research areas of space-time GIS from 1990 to the present.

25.78% of publications (328 pieces) focus on environmental sciences ecology and 22.56% of

publications (287 pieces) are produced from the perspective of computer science. Geographers,

especially physical geographers, have made significant contributions to this field as well.

Table 1 lists the top 15 source titles of space-time GIS publications. Popular outlets for space-

time GIS research include major GIS and Geography journals including International Journal of

Geographic Information Science, Applied Geography, International Journal of Geo Information,

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Computers Environment and Urban Systems, Journal of Transport Geography, and Annals of the

Association of American Geographers.

Figure 1: Number of space-time GIS related publications from 1990s by year.

Figure 2: Number of publications of space-time GIS by research areas.

0

20

40

60

80

100

120

140

1990 1995 2000 2005 2010 2015 2020

Publ

icat

ions

Year

050

100150200250300350

EnvironmentalSciencesEcology

ComputerScience

Geography PhysicalGeography

Engineering Remotesening Geology WaterResources

PublicEnvironmentalOccupational

Health

InformationScienceLibraryScience

Publ

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ions

Reaserach Area

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Table 1: source title of space-time GIS publications

Rank Source Title Freq. Percent. 1 International Journal Of Geographical Information Science 47 3.69% 2 Lecture Notes In Computer Science 40 3.14% 3 Applied Geography 26 2.04% 4 International Archives of The Photogrammetry Remote Sensing and

Spatial Information Sciences 21 1.65%

5 ISPRS International Journal of Geo Information 21 1.65% 6 Journal of Transport Geography 20 1.57% 7 Environmental Monitoring and Assessment 18 1.41% 8 Sustainability 18 1.41% 9 Proceedings of SPIE 17 1.33% 10 Computers Environment And Urban Systems 16 1.25% 11 Annals Of The Association Of American Geographers 15 1.17% 12 Science Of The Total Environment 15 1.17% 13 PLoS One 14 1.11% 14 International Journal Of Environmental Research And Public Health 13 1.02% 15 Transactions In GIS 13 1.02%

Applications of Space-time GIS

The applications of space-time GIs are broad and diverse, ranging from robot navigation or

object tracking in a room to regional urban growth and intercontinental economic dynamics..

Research objects also vary, including travel behaviors, land cover, climate change, etc. Space-time

GIS can be applied to almost anything inherently spatial and temporal.

Nara (2017) identifies five subtopics related to space-time GIS application by employing

dynamic topic modeling (DTM), physical/ environmental/climate geography, urban/ regional

dynamics, risk, mobility/accessibility, and health. These topics resonate with the main research

areas discussed previously. The applications are summarized in Table 2. Space-time GIS can

empower these applications by integrating data and processes in space and time to obtain

spatiotemporal understanding of the chosen issues (May Yuan, 2016b).

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Table 2: Space-time GIS applications by topics

(source: Nara,2017, summarized by the author)

Topic Subtopic Research Method Sample paper title Physical/ environmental/ climate geography

• Land cover change • Water quality • Soil erosion dynamics • Landscape change • Air pollution exposure and

concentration • Climate change

• Remote sensing • DRASTIC model • Voxel-based

automata • Data mining • Spatial statistics

• Survival analysis in land change science: Integrating with GIScience to address temporal complexities

• Spatio-Temporal Groundwater Vulnerability Assessment - A Coupled Remote Sensing and GIS Approach for Historical Land Cover Reconstruction

Urban/ regional dynamics

• Urbanization • Landscape change • City growth/expansion • Developments in China

• Simulation-based model : cellular automata (CA),agent-based models(ABM), spatial Markov chains model

• Simulating sprawl • Modeling gentrification

dynamics: A hybrid approach

• A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area

Risk • Disaster and hazard

• Fire vents • Social media data

analysis • Integer

programming model

• Modelling community evacuation vulnerability using GIS

• Spatial, temporal, and content analysis of Twitter for wildfire hazards

Mobility/accessibility

• Accessibility to health care services

• Crime • Indoor environment • Movement in everyday life

• Trajectory-based analysis

• Agent-based model

• Space-time and integral measures of individual accessibility: A comparative analysis using a point-based framework

• Beyond Space (As We Knew It): Toward Temporally Integrated Geographies of Segregation, Health, and Accessibility

Health • Health service planning • Disease epidemiology • Air pollution exposure in

relation to health • Risk factor analysis

associated health

• Location-based social networking

• Space-time kernel density estimation

• Visualizing space and time in crime patterns: A comparison of methods

• The mortality rates and the space-time patterns of John Snow's cholera epidemic map

Main Themes Space-time GIS embraces spatial and temporal data through the processes of conceptualization,

representation, computation and visualization. The next part of this paper will investigate the two

themes of space-time GIS: (1) conceptualization and representation (2) analysis and visualization.

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Conceptualization and Representation

Conceptualization deals with how we view and reason about reality. Our conceptual models of

space and time lead to ways in which we recognize spatiotemporal objects, their structures and

relationships and ways in which we represent these spatiotemporal constructs in data models or

mathematical formalizations (May Yuan, 2016a). There are two core conceptual perspectives of

space and time: absolute and relative. The former perspective originated from Newtonian

absoluteness, in which space is Euclidean with a three-dimensional Cartesian frame of reference,

and time can be added as a fourth orthogonal axis. Under the relative conceptual perspective, space

and time are viewed as coexistent relationships between changes and events, and they are defined

by the spatial elements and processes under consideration (Nara, 2017).

Based on these two fundamental conceptualizations of space and time, various space-time GIS

conceptualizations and representations have been proposed such as object-oriented

conceptualization, event-based data model, three-domain representation, topological temporal

framework, and trajectory conceptualization (Langran, 1988; Nara, 2017; Raper & Livingstone,

1995; May Yuan, 2016a).

Analysis and Visualization

Analytically and computationally, space-time GIS research manifests itself in statistics,

modeling and simulation. Advanced visualization techniques have been developed to aid analysis

and demonstrate processes and patterns.

With respect to space-time statistics, various methods are employed, including exploratory

space-time attribute pattern analysis, space-time density statistics, geographically and temporally

weighted regression, and trajectory analysis. R is a major language in the progress of spatial

statistics. In terms of modelling and simulation, Cellular automata (CA) and agent-based models

(ABMs) are two popular simulation models. CA are suitable for simulating spatiotemporal

processes in a spatially continuous field such as urban process and land-use land-cover change. In

contrast, ABMs have a great capability of representing mobile entities such as human flows and

vehicles (Nara, 2017).

Efforts have been made by scholars to enhance data visualization. Space-time paths, prisms,

and cubes are frequently used to operate data in 2D space and 1D time. Space-time paths are often

used in trajectory analysis of travel behaviors. For example, Kwan (2004) and her group developed

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a set of computational algorithms and visualization tools. 3D visualization of human activities

patterns demonstrates the effectiveness of GIS in computing and displaying a large number of

space-time paths to support space-time analysis. Figure 3 is an example of her work. Space-time

cubes are gaining importance as well. Bach et al. (2017) developed a general framework based on

generalized space-time cubes to communicate operations and patterns in space-time data

visualization. Visual analytics are effective in detecting spatiotemporal hot spots. Figure 4 shows

a traditional hot spot analysis using cross-sectional data, while Figure 5 shows a map of emerging

hot spot analysis which integrates with time using spatial panel data. The new tool “Emerging Hot

Spot Analysis” in ArcGIS can identify trends in the clustering of point densities or summary fields

in a space-time cube. Categories include new, consecutive, intensifying, persistent, diminishing,

sporadic, oscillating and historical hot and cold spots.

Figure 3: Space-time aquarium showing the space-time paths of African and Asian Americans

Source: Kwan and Lee (2004)

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Figure 4. Traditional hot spot analysis

(Source: Author)

Figure 5. Space-time Hot Spot analysis in 2D and 3D

(Source: Author)

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Discussion Research in space-time GIS and applications has grown tremendously over the past several

decades. Significant progress has been made in conceptualization, representation, analysis and

visualization in different application domains.

The future of space-time GIS is evidently bright. Currently, conceptualization is framed

maturely and various challenges lie in technological domains including space-time model

validation and integration of different data sources (Nara, 2017). These challenges will be

overcome by technology development ultimately. There needs to be more robust theoretical and

reasoning frameworks, powerful techniques for analysis and visualization, and effective

communication among different research areas, especially between conceptualization and

analytics.

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