1. Space-Time The ESRI Time Project – Comments by Steve Kopp
Time series and ArcGIS: What can I use now?
Tracking Analyst
Plotting graphs of Attribute Series using CRWR TS Plotter
A true Temporal GIS: What does ArcGIS need?
Hydrologic Flux calculations: Florida Example
A new file type?: NetCDF

2. Tracking Analyst Simple Events Complex Event
1 feature class that describes What, When, Where
Complex Event
1 feature class and 1 table that describe What, When, Where
Arc Hydro

3. Simple Event ID Time Geometry Value 1 T1 X1,Y1 0.1 2 T2 X2,Y2 0.3 T3
0.7 T4
X4,Y4
0.4 3 T5
X5,Y5
0.5 T6
X6,Y6
0.2 4 T7
X7,Y7 T8
X8,Y8
0.8 T9
X9,Y9
Unique Identifier
for objects being
tracked through
time
Observation
Time of observation (in order)
Geometry of observation

4. Complex Event (stationary version)ID
Time
Value 1 T1
0.1 2 T2
0.3 T3
0.7 T4
0.4 3 T5
0.5 T6
0.2 4 T7 T8
0.8 T9 ID
Geometry 1
X1,Y1 2
X2,Y2 3
X3,Y3 4
X4,Y4
Cases 1, 2, 3, 4, 5
The object maintains its geometry (i.e. it is stationary)

5. Complex Event (dynamic version)ID
Geometry
Time
Value 1
X1,Y1 T1
0.1 2
X2,Y2 T2
0.3
X3,Y3 T3
0.7
X4,Y4 T4
0.4 3
X5,Y5 T5
0.5
X6,Y6 T6
0.2 4
X7,Y7 T7
X8,Y8 T8
0.8
X9,Y9 T9 ID
Gage Number 1
1001 2
1002 3
1003 4
1004
Cases 6 and 7
The object’s geometry can vary with time (i.e. it is dynamic)

6. Fecal Coliform in Galveston Bay, Texas

7. Tracking Analyst Demo
Show the Galveston Bay Monitoring Point feature class and Time Series Table
Show the temporal layer
Show the tracking analyst time “Playback Manager”
Animate bacteria concentrations

8. Time and Space in GIS Time Series Feature Series Attribute Series
Variable t3
Value t2 t1
Time
Attribute Series
Raster Series
Value t3 t1 t2 t2 t1 t3 y x

9. Time Series and Temporal Geoprocessing
DHI Time Series Manager
Time Series
Feature Series
Time
Variable t3
Value t2 t1
Time
Attribute Series
Raster Series
Value t3 t3 t2 t1 t2 t1 y x
ArcGIS Temporal Geoprocessing
Adobe picture

10. Arc Hydro Attribute Series
TSDateTime
Feature Class
(point, line, area)
TSValue
FeatureID
TSType
TSType Table

11. Arc Hydro Attribute Series
Feature Class (HydroID)
Attribute Series Table (FeatureID)

12. Attribute Series Typing
TSType
Attribute Series 1 *
Type
Units
Regular ….
FeatureID
Type
Time
Value
Map time series e.g. Nexrad
Collections of values recorded at various locations and times e.g. water quality samples
This is current Arc Hydro time series structure

13. Plotting Attribute Series
One feature with a time-dependent Attribute
Observed or Modeled
Complications
Regular or Irregular in time
Many Types (rainfall, streamflow, dissolved oxygen, etc.)
Instantaneous, cumulative, averaged, min, max, etc.
Different units (cfs, m3/d, gpd, etc.)
Plot the data in ArcMap

14. TS Plotter Demo Show TSType Table
Plot time series for a few MonitoringPoint features
Summarize data into yearly averages
Export data and chart to Excel
Show exported data and chart in Excel

15. South Florida Water Management Project
Prototype region includes 24 water management basins,
More than 70 water control structures managed by the South Florida Water Management District (SFWMD)
Includes natural and managed waterways
Prototype Area
Lake Kissimmee
Lake Istokpoga
Lake Okeechobee

16. Questions that SFWMD wants Answered
How much water is there?
Where is the water in the District?
How much water will enter the canal system?
How can water be routed from one basin to another?

17. DBHydro TimeSeries
Achieve of Water Related Time Series Data currently used by SFWMD
Example of Flow Data:
Daily Average Flow [cfs] at Structure S65 (spillway)
Spatial Information
About point of measurement
Unique 5-digit alphanumeric code called DBKEY
Date/Time
Value
DBHydro can be accessed at:

18. Coupling Table: Linking Control Volume to Features
Water Balance performed over a Control Volume (i.e.: Basin)
Coupling Table links the Control Volume (basin) to all features that transfer water into and out of the Control Volume
Horizontal (structures)
Vertical (rainfall, ETp)
Qin
Qrain
Qevap
Qout
S65BC Basin

19. Water Balancing in ArcHydro
QS65A +QRAIN - QETp –QS65C = Storage

20. Coupling Table Design
HydroID of Inflow or Outflow Feature that contains Time Series Information
If Inflow/Outflow is a flux, include an area over which the flux acts
HydroID of Control Volume
Direction of Flow 1 = IN, 2 = OUT
ObjectID

21. Demo of Flow and Flux Calculations using TSViewer
Links Control Volume Feature with Inflow and Outflows

22. Multidimensional Data Representation for the Geosciences
Atmospheric Science
Hydrology
Ocean
Science
Earth Science

23. Weather and Hydrology Weather Information Hydrologic Information
Continuous in space and time
Combines data and simulation models
Delivered in real time
Hydrologic Information
Static spatial info, time series at points
Data and models are not connected
Mostly historical data
Challenges for Hydrologic Information Systems
How to better connect space and time?
How to connect space, time and models?
How to connect weather and hydrology?

24. Arc Hydro Attribute Series
TSDateTime
Feature Class
(point, line, area)
TSValue
FeatureID
TSType
TSType Table

25. NetCDF Data Model (developed at Unidata for distributing weather data)
Time
Dimensions and
Coordinates
Value
Space (x,y,z)
NetCDF describes a collection
of variables stored in a dimension space that may represent coordinate points in the (x,y,z,t) dimensions
Variables
Attributes

26. NetCDF File for Weather Model Output of Relative Humidity (Rh)
dimensions:
lat = 5, long = 10, time = unlimited;
variables:
lat:units = “degrees_north”;
long:units = “degrees_east”;
time:units = “hours since ”;
data:
lat = 20, 30, 40, 50, 60;
long = -160, -140, -118, -96, -84, -52, -45, -35, -25, -15;
time = 12;
rh = .5,.2,.4,.2,.3,.2,.4,.5,.6,.7,
.1,.3,.1,.1,.1.,.1,.5,.7,.8,.8,
.1,.2,.2,.2,.2,.5,.7,.8,.9,.9,
.1,.2,.3,.3,.3,.3,.7,.8,.9,.9
.0,.1,.2,.4,.4,.4,.4,.7,.8,.9;
rh (time, lat, lon);

27. Relative Humidity Points

28. Interpolate to Raster
GeoTiff format, cell size = 0.5º

29. Zoom in to the United States

30. Average Rh in each State
Determined using Spatial Analyst function Zonal Statistics with
Rh as underlying raster and States as zones

31. Integrated Data Viewer (Developed by Unidata)
Data Probe
Vertical Profile
Time/Height display
Vertical cross-section
Plan view
Isosurface
Note: IDV = Integrated Data Viewer

32. RUC20 – Output Samples Precipitable water in the atmosphere
Cross-section of relative humidity
Wind vectors and wind speed (shading)
Images created from Unidata’s Integrated Data Viewer (IDV)

33. IDV Demo For RUC20 predicted temperature (4D dataset) show:
Plan view changes over time
Cross-section changes over time
Vertical Profile changes over time
Data Probe changes over time