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.

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

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

Simple EventID Time Geometry Value

1 T1 X1,Y1 0.1

2 T2 X2,Y2 0.3

1 T3 X3,Y3 0.7

2 T4 X4,Y4 0.4

3 T5 X5,Y5 0.5

2 T6 X6,Y6 0.2

4 T7 X7,Y7 0.1

1 T8 X8,Y8 0.8

1 T9 X9,Y9 0.3

Unique Identifier for objects being tracked throughtime

Time of observation (in order) Geometry of observation

Observation

Complex Event (stationary version)

ID Geometry

1 X1,Y1

2 X2,Y2

3 X3,Y3

4 X4,Y4

ID Time Value

1 T1 0.1

2 T2 0.3

1 T3 0.7

2 T4 0.4

3 T5 0.5

2 T6 0.2

4 T7 0.1

1 T8 0.8

1 T9 0.3

The object maintains its geometry (i.e. it is stationary)

Cases 1, 2, 3, 4, 5

Complex Event (dynamic version)

ID Gage Number

1 1001

2 1002

3 1003

4 1004

ID Geometry Time Value

1 X1,Y1 T1 0.1

2 X2,Y2 T2 0.3

1 X3,Y3 T3 0.7

2 X4,Y4 T4 0.4

3 X5,Y5 T5 0.5

2 X6,Y6 T6 0.2

4 X7,Y7 T7 0.1

1 X8,Y8 T8 0.8

1 X9,Y9 T9 0.3

The object’s geometry can vary with time (i.e. it is dynamic)

Cases 6 and 7

Fecal Coliform in Galveston Bay, Texas

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

Time Series Feature Series

Raster SeriesAttribute Series

Time

Variable

Time and Space in GIS

xy

Value

t1t2t3

Value

Time

t1t2

t3

t3

t2t1

Time Series and Temporal Geoprocessing

Time Series Feature Series

Raster SeriesAttribute Series

Time

Variable

xy

Value

t1t2t3

Value

Time

t1t2

t3

ArcGIS Temporal Geoprocessing

t3

t2t1

DHI Time Series Manager

Adobe picture

TSDateTime

FeatureID

TSType

TSValue

Arc Hydro Attribute Series

TSType Table

Feature Class(point, line, area)

Arc Hydro Attribute Series

Feature Class (HydroID)

Attribute Series Table (FeatureID)

• 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

Type

TSType

Units Regular …. 1Attribute Series

FeatureID Time Value* Type

Attribute Series Typing

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

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

South Florida Water Management Project

Prototype Area

•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 waterwaysLake

Okeechobee

Lake Istokpoga

Lake Kissimmee

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?

DBHydro TimeSeriesAchieve of Water Related Time Series Data currently used by

SFWMD

Example of Flow Data:Daily Average Flow [cfs] at Structure S65 (spillway)

Unique 5-digit alphanumeric code called DBKEY

Date/Time Value

Spatial Information About point of measurement

•DBHydro can be accessed at: http://www.sfwmd.gov/org/ema/dbhydro/index.html

Coupling Table: Linking Control Volume to Features

Qin

Qout

Qrain Qevap

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)

S65BC Basin

Water Balancing in ArcHydroQS65A +QRAIN - QETp –QS65C = Storage

Coupling Table Design

ObjectID

HydroID of Control Volume

HydroID of Inflow or Outflow Feature that contains Time

Series Information

Direction of Flow 1 = IN, 2 = OUT

If Inflow/Outflow is a flux, include an area over which the flux acts

Demo of Flow and Flux Calculations using TSViewer

Links Control Volume Feature with Inflow and Outflows

Multidimensional Data Representation for the Geosciences

Ocean Science

Earth Science

Atmospheric Science

Hydrology

Weather and Hydrology

• Weather 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?

TSDateTime

FeatureID

TSType

TSValue

Arc Hydro Attribute Series

TSType Table

Feature Class(point, line, area)

Time

Space (x,y,z)

Variables

Value

NetCDF Data Model (developed at Unidata for distributing weather data)

Attributes

Dimensions andCoordinates

NetCDF describes a collection of variables stored in a dimension space that may represent coordinate points in the (x,y,z,t) dimensions

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 1996-1-1”;

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);

Relative Humidity Points

Interpolate to Raster

GeoTiff format, cell size = 0.5º

Zoom in to the United States

Average Rh in each State

Determined using Spatial Analyst function Zonal Statistics with Rh as underlying raster and States as zones

Integrated Data Viewer(Developed by Unidata)

• Data Probe

• Vertical Profile

• Time/Height display

• Vertical cross-section

• Plan view

• Isosurface

Note: IDV = Integrated Data Viewer

RUC20 – Output SamplesPrecipitable water in the atmosphere

Cross-section of relative humidity

Images created from Unidata’s Integrated Data Viewer (IDV)

Wind vectors and wind speed (shading)

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