Learning to organize, analyze, and visualize space-time data can be daunting. Get up to speed in this workshop by learning how to manage your space-time data aptly, analyze it appropriately, and map it artfully. A variety of examples are used demonstrate how ArcGIS helps you gain greater understanding of space-time data using powerful analytical tools for aggregating your data into a space-time cube; performing hot spot, cluster, and outlier analyses; and visualizing your data and analysis results. Techniques are also presented for creating captivating and informative displays to share your insights with others. 2018 AAG Annual Meeting Wednesday, April 11, 3:20 p.m. – 5:00 p.m.

1. Analyzing and Mapping Space-time
Data
Aileen Buckley
Esri - Redlands

2. This presentation…
• The nature of space-time data
• Data types
• Managing
• Analyzing
• Mapping

3. Moving features
• Storm centers
• Airplanes, boats, cars
• People, animals
Features that move over time
Storms in the Atlantic - 1993

4. Discrete events
• Crimes
• Accidents
• Earthquakes, lightening strikes,
volcanic events
Events that happen at specific locations
Crimes in Lincoln, Nebraska

5. Stationary recorders
• Stream gauges
• Weather stations
• Traffic sensors
Features that stay in one place and record changes
Living At;las Real-time Stream Gauges

6. Change / growth
• Fire perimeters
• Flood extents
• Demographics
Features that change condition over time
Station Fire, Angeles National Forest, California, 2010

7. The nature of space-time data
• Conceptualizations of time vary
- Linear (unique, directional time periods)
- Cyclic (repeating after a specific range in time)
- Others
• Time is relative to something
- Clock-driven time – synchronized to a specific clock
- e.g., traffic sensors or stream gauges
- Event-driven time – synchronized to an event
- e.g., post-Katrina, Obama era
- State-driven time – synchronized to a change in state
- e.g., melting of the ice sheets, inflation
http://www.businessinsider.com/how-different-cultures-understand-time-2014-5
T1 Sx, T2 Sx, T3 Sx, …
T1 – T0, T2 – T0, T3 – T0, …
S1, S2, S3, …
where T = Time and S = State

8. The nature of space-time data
• Point data – specific to point in time
• Range data – accumulated over an
interval of time
• Regular or “irregular” intervals

9. GIS integrates space-time data
• Unified experience for time
- Part of Desktop, Pro, Runtime,
and Portal products
• Geoprocessing (GP) tools
- Managing time aware data
- Analyzing through time or
space and time
• Ability to share
• space-time data/maps
- Videos, images, map series
- Packages
- Web layers and image services
T1
Analysis, simulation,
& modeling
Stationary
Mobile
Real-time
sensor network
Space-time maps
Fixed time
space-time
data
x
y
T
Multidimensional
(x,y,z,t)
Time stamps /
time extents
Data Sources

10. Demo
ArcMap

11. Types
of space-time data

12. Supported data types
• Feature layers
• Mosaic datasets
• NetCDF layers
• Tables
• Raster catalogs
• Tracking layers / Streaming layers
• Network dataset layers with traffic data
• Plus service layers with historical content and updating data feeds

13. Feature layers – Separate features
• Enable time on the Time tab of the feature layer’s Layer Properties dialog box
• With feature layers, features can be visualized over time in two ways:
1. The shape and location of each feature changes over time
- Store separate features

14. Feature layers – Features joined to a table
• Enable time on the Time tab of the feature layer's Layer Properties dialog box
• With feature layers, features can be visualized over time in two ways:
1. The shape and location of each feature changes over time
- Store separate features
2. The shape and location of each feature is constant but attribute values change over time
- You can represent the changing attributes in a separate (one-to-many) joined table

15. Mosaic datasets
• Enable time on the Time tab of the mosaic
dataset’s Layer Properties dialog box
• Mosaic datasets store rasters that represent
change over time
• The time field is in the Footprint attribute
table of the mosaic dataset

16. NetCDF layers
• NetCDF is a file format for storing
space-time data
- Multiple dimensions (x, y, z, t)
- Multiple variables (temperature, pressure,
salinity, wind speed)
• Time values are stored as one dimension of the netCDF layer
• Enable time on the Time tab of the Layer Properties dialog box
• For netCDF feature layers, specify the layer time using a time dimension or the
attribute fields
• For netCDF raster layers, specify layer time using the time dimension
X
Y

17. Demo
Mosaic dataset data

18. Managing
space-time data

19. Space-time data stored in multiple columns
• Store space-time data in a row format
- Each feature in a row
• Transpose Fields GP tool
- Shifts data entered in columns into rows

 Best practices for managing space-time data
Sorted on DateField

20. Number and Text field types
• Only “sortable” formats are supported
- YYYYMMDD 20160701 > 20150701 = TRUE
- MMDDYYYY 07012016 > 08012015 = FALSE
• Named month is not supported
- AUG-01-2016 would come before JUL-01-2016
• Index the field for faster display and query performance

21. Date field type
• Store time values in a date field
• A field type that stores dates, times, or dates
and times
• Most efficient format for query and display
performance
- Supports more sophisticated database queries
• Easiest to configure on the layer

A wide range of
standard formats

22. Converting to a Date field type
• Use Data Management GP tools to convert to a date field type
• Convert Time Field GP tool
- Converts custom Text/Number formats into a new Date field
- “July 09, 2016”  07/09/2016  MM/DD/YYYY
Date Date_Converted

The Date field can also
have a custom format
MM dd, yyyy HH:mm:ss

23. Setting duration
• Calculate End Time GP tool
- Populates an end time field with the next record’s start time
- The last record will not have a duration – the end time is calculated to be the same as the
start time of the feature – edit it manually, if known or if necessary

24. Demo
Managing Space-time Data

25. Analyzing
space-time data

26. Analyzing space-time data
• Geoprocessing tools to manage space-time data – we have already seen these
• All GP tools honor time
• Some GP tools specifically analyze space and time
• ArcPy site-package can be used to analyze space-time data

27. All GP tools honor time
• GP tools honor the space-time settings for time-enabled layers
• Tool process only those features within the time extent set in the Time Slider
• Similar to a selection or definition query

28. GP tools for space-time data: ArcGIS for Desktop and Pro
• ArcToolbox > Spatial Statistics > Mapping Clusters
• These use a spatial weights matrix that has a space-time constraint
- Hot Spot Analysis GP tool
- Creates a map of statistically significant hot and cold spots
- Cluster and Outlier Analysis GP tool
- Identifies statistically significant hot spots, cold spots, and spatial outliers
- Grouping Analysis GP tool
- Groups features based on feature attributes and
optional spatial/temporal constraints

29. GP tools for space-time data: Pro
• Space Time Pattern Mining toolbox
- Create Space Time Cube GP tool
- Summarizes a set of points into a netCDF data structure by aggregating them into space-time bins
- Emerging Hot Spot Analysis GP tool
- Identifies trends in the clustering of point counts or attributes in a netCDF space-time cube
- Local Outlier Analysis GP tool
- Identifies statistically significant clusters of high or
low values as well as outliers

30. Demo
Analyzing space-time Data

31. Mapping
space-time data

32. A variety of ways to share space-time visualizations
• As a time-enabled web map
- TIP: Publish time-aware web maps from Pro (instead of per-layer in 10.x)
- Open Pro, import an .mxd, and publish the web map directly to AGOL
- Known issues with current AGOL means two edits to an imported .mxd before publishing:
1. Replace the basemap (to avoid group layers)
2. Do not use a definition query against a time field
• As time-enabled image services (Portal only)
• As an animation / video
• As a series of exported images
• As a space-time map book
• As “small multiples” on a single layout
• As map or layer packages

33. Create web map services
• Map services preserve time information from time-enabled layers
- Used to query and display content (with the time slider)
• Animated GIFs can be used for icons (e.g., in the Living Atlas)
- LINK - ArcGIS Online web map search for “time” and owner:esri
• Example space-time web maps:
- Atlantic Storms (1993-95)
- Imported an MXD, updated the basemap, publish
- One year of ice pack imagery (North Pole)
- Time-aware aerial imagery
World Traffic Service
NWS Precip Forecast
NWS Snowfall Forecast

34. The purpose of mapping space-time data
• To allow for estimation of the degree of change or spatial pattern of
cross-correlation between time periods
• The effectiveness of any particular mapping method is related to:
- Clear and accurate representation of the data and
- Comprehension by the reader
• Mapping space-time data usually results in increased complexity of the display
• This complexity can lead to:
- Misunderstanding or misinterpretation, or even…
- …missing the change altogether (change blindness)
• Maps of space-time data benefit from clear, explanatory indicators of the current
time step within the full range
- Time slider control
- Timeline, time text, etc…

35. Methods to map space-time data
• Static displays
- Superimposed features
- Isochron maps
- Small multiples
- Complementary graphics
- Change maps
- Change analysis maps
- Space-time cubes
• Dynamic displays
- Use movement or variation to show or draw
attention to change

36. Superimposed features
• Superimpose features using distinguishable graphic marks or symbols
• Example
- Zebra Mussel Sightings

37. Zebra Mussel Sightings, 1986-2011

38. Zebra Mussel Sightings, 1986-2011
Directional Trend and Mean Center of Distribution

39. Zebra Mussel Sightings, 1986-2011
Directional Trend and Mean Center of Distribution

40. Icochron maps
• Map the change over time as isochrons (lines connecting points relating to
the same time or equal time differences)
• Areas between isochrones can be colored
• Color selection should reflect the nature of the data (usually sequential)
• Example
- Age of the Ocean Floor
- Station Fire, 2009

46. https://www.greatamericaneclipse.com/maps-and-posters/oregon-state-map

47. Small multiples
• A series of displays with the same graphic design structure depicting changes from
multiple to multiple (i.e., map to map)
• Should be comparable, multivariate, “shrunken, high-density graphics” that are
based on a large data matrix and used to show shifts in relationships among
variables
• The consistency of design assures that attention is directed toward changes in the
data
• Example
- Dam Construction in the US
- Plate Tectonics

48. 2000
1910 1920 1930
1940 1950 1960
1970 1980

52. Complementary graphics
• Combining a map of a single time period with other graphics to display the space-
time data
• Graphics used to display the space-time data include:
- Timelines
- Time series graphs
- Spiral displays
- Circular graphs
• Examples
- Birds vs Aircraft by Month
- Water Balance App

53. http://www.esri.com/products/maps-we-love/birds-vs-aircraft
Birds vs Aircraft by Month

54. https://vannizhang.github.io/water-balance-app/

56. Change maps
• Depict the change over time at point locations, within homogeneous areas,
or along linear features
• Calculate the change and map it accordingly
• Often used to show change between only two time periods as the rate of
change
• Examples
- Percent Change in Total Population

59. Population Change, 1900 - 2010

60. Change analysis maps
• The change in a variable between time periods or over a range of time periods is
analyzed statistically and summarized in a single numerical index displayed on a
single map
- Hot spot analysis
- Cluster and outlier analysis
• The amount of change is sometimes simplified to a binary index (e.g.,
increase/decrease)
• Example
- Percent Change in Poverty Rates of School-Aged Children

64. Space-time cubes
• Superimpose features using distinguishable graphic marks or symbols
• Examples
- Space-Time Cube Explorer
- Napolean’s March on Moscow

65. www.esriurl.comSpaceTimeCubeExplorer

67. This presentation…
• The nature of space-time data
• Data types
• Managing
• Analyzing
• Mapping