Modeling Space/Time Variability with BMEGUI Prahlad Jat(1) and Marc Serre(1) (1) University of North Carolina at Chapel Hill

Agenda Introduction Mean Trend Analysis Space/Time Covariance Analysis

Introduction

Temporal GIS analysis process Read Data File Data Field Screen Check Data Distribution Data Distribution Screen Exploratory Data Analysis Screen Exploratory Data Analysis Mean Trend Analysis Screen Mean Trend Analysis Space/Time Covariance Analysis Screen Covariance Analysis BME Analysis BME Estimation Screen

Mean Trend Analysis Screen Display temporal mean trend Display spatial mean trend (Raw & Smooth) Model Parameter (Exponential Smoothing)

Space/Time Covariance Analysis Screen Display spatial & temporal covariance Plot covariance models

Mean Trend Analysis

Mean Trend Calculation Assume a separable additive space/time mean trend model Input Parameter Spatial Radius/Spatial Range Temporal Radius/Temporal Range Averaging the measurement at each MS (or at each time point) Find measurements within “Radius” , then apply exponential filter

Smoothed Mean Trend Sradius Tradius

Z - (SSM+STM-mean(STM)) Remove Mean Trend Removing the mean trend from data Z - (SSM+STM-mean(STM)) Z: Value SSM: Smoothed Spatial Mean Trend STM: Smoothed Temporal Mean Trend

Calculate Mean Trend Click “Model mean trend and remove it from data” BMEGUI automatically calculate mean trend using the default parameters

Temporal Mean Trend Raw Temporal Mean Trend is shown in dotted line Smoothed Temporal Mean Trend in shown in solid line Zoom in/out

Spatial Mean Trend Two tabs – Spatial Mean Trend (Raw) Spatial Mean Trend (Smoothed) Zoom in/out Point Layer File

Recalculate Mean Trend Input parameters and click “Recalculate Mean Trend” button Spatial Radius/Spatial Range Temporal Radius/Temporal Range Spatial Range Spatial Radius Click Button Temporal Radius Temporal Range

Space/Time Covariance Analysis

Space/Time Covariance Analysis Experimental Covariance (Red dots) Fit experimental covariance with covariance model (Solid Line)

Spatial/Temporal Components Two tabs Spatial Component Temporal Component Temporal Component Tab Spatial Component Tab

Experimental Covariance BMEGUI automatically calculate experimental covariance using the default lag setting User can modify the lag setting Change the number of lags Input user-defined lag and lag tolerance

Change number of lags Input the number of lags, then click “Recalculate Spatial/Temporal Covariance” button Recalculate Spatial Cov. Number of lags for Spatial Cov. Recalculate Temporal Cov. Number of lags for Temporal Cov.

Modify lag and lag tolerance Click “Edit Spatial/Temporal Lags…” Input lag and tolerance in dialog box, then click “OK” (Use “,” to separate the values)

Covariance Model BMEGUI supports homogeneous/stationary Space/Time random field Space/Time separable model Maximum four model structures Following covariance model exponential gaussian spherical holecos holesin

Set the number of model structures Input the number into text box (1-4) The number of tabs will change

Select covariance model Select model from the combo box Input sill and range, then click “Plot Model”

Clear covariance model Plot “Clear Plot” button Covariance model will be erased from the figures