Space-Time

1. Space-Time • Arc Hydro time series structure • Tracking Analyst • A true Temporal GIS: What does ArcGIS need? • Time series, attribute series, raster series, feature series • Space-time grids: NetCDF

2. In 1905, Albert Einstein published his famous Special Theory of Relativity and overthrew commonsense assumptions about space and time. http://archive.ncsa.uiuc.edu/Cyberia/NumRel/NumRelHome.html

4. Additional reading

5. Space-Time • Arc Hydro time series structure • Tracking Analyst • A true Temporal GIS: What does ArcGIS need? • Time series, attribute series, raster series, feature series • Space-time grids: NetCDF

6. Space-Time Cube Time TSDateTime Data Value TSValue FeatureID Space Variable TSTypeID

7. Time Series Data

8. Time Series of a Particular Type

9. A time series for a particular feature

10. A particular time series for a particular feature

11. All values for a particular time

12. MonitoringPointHasTimeSeries Relationship

13. TSTypeHasTimeSeries

14. Arc Hydro TSType Table Units of measure Regular or Irregular Time interval Type Of Time Series Info Recorded or Generated Type Index Variable Name • Arc Hydro has 6 Time Series DataTypes • Instantaneous • Cumulative • Incremental • Average • Maximum • Minimum

15. Time Series Types Incremental Instantaneous Average Cumulative Minimum Maximum

16. Space-Time • Arc Hydro time series structure • Tracking Analyst • A true Temporal GIS: What does ArcGIS need? • Time series, attribute series, raster series, feature series • Space-time grids: NetCDF

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

18. Simple Event Unique Identifier for objects being tracked through time Observation Time of observation (in order) Geometry of observation

19. Complex Event (stationary version) Cases 1, 2, 3, 4, 5 The object maintains its geometry (i.e. it is stationary)

20. Complex Event (dynamic version) Cases 6 and 7 The object’s geometry can vary with time (i.e. it is dynamic)

21. Tracking Analyst Display

22. Feature Class and Time Series Table

23. Temporal Layer Shape from feature class is joined to time series value from Time Series table

24. Space-Time • Arc Hydro time series structure • Tracking Analyst • A true Temporal GIS: What does ArcGIS need? • Time series, attribute series, raster series, feature series • Space-time grids: NetCDF

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

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

27. 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

28. 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 calledDBKEY Date/Time Value • DBHydro can be accessed at:http://www.sfwmd.gov/org/ema/dbhydro/index.html

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

30. Attribute Series Typing TSType Attribute Series • 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 1 * Type Units Regular …. Type Time FeatureID Value

31. Irregularly recorded water quality data form an Attribute Series • A point feature class defines the spatial framework • Many variables defined at each point • Time of measurement is irregular • May be derived from a Laboratory Information Management System Field samples Laboratory Database

32. Fecal Coliform in Galveston Bay(Irregularly measured data, 1995-2001) Coliform Units per 100 ml Tracking Analyst Demo

33. Nexrad over South Florida • Real-time radar rainfall data calibrated to raingages • Received each 15 minutes • 2 km grid • Stored by SFWMD in Arc Hydro time series format

34. Nexrad data as Attribute Series Attribute series Display as a temporal layer in Tracking Analyst

35. Time series from gages in Kissimmee Flood Plain • 21 gages measuring water surface elevation • Data telemetered to central site using SCADA system • Edited and compiled daily stage data stored in corporate time series database called dbHydro • Each time series for each gage in dbHydro has a unique dbkey (e.g. ahrty, tyghj, ecdfw, ….)

36. Compile Gage Time Series into an Attribute Series table

37. Hydraulic head Land surface h Mean sea level (datum) Hydraulic head is the water surface elevation in a standpipe anywhere in a water system, measured in feet above mean sea level

38. Map of hydraulic head Z Hydraulic head, h h(x, y) x y X Y A map of hydraulic head specifies the continuous spatial distribution of hydraulic head at an instant of time

39. Time sequence of hydraulic head maps z t3 t2 t1 Hydraulic head, h x y

40. Attribute Series to Raster Series

41. Inundation d h L Depth of inundation = d IF (h - L) > 0 then d = h – L IF (h – L) < 0 then d = 0

42. Inundation Time Series d(x,y,t) = h(x,y,t) – LT(x,y) h (x,y,t) LT(x,y) d(x,y,t) t Time DEMO: DHI Time Series

43. Ponded Water Depth Kissimmee River June 1, 2003

44. Show Generate Rasters Model

45. 1 2 3 4 Variable Time t y x Hydroperiod Tool TimeSeries Framework Time Series Feature Series Attribute Series Raster Series

46. Depth Classification Depth Class 11 5 9-10 4 7-8 3 5-6 2 3-4 1 1-2 0 0 -1

47. Feature Series of Ponded Depth

48. Show Classify Depths Model

49. Attribute Series for Habitat Zones

50. Show Zonal Stats Model