location transport and land use modelling spatial temporal information
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Location, Transport and Land-use : Modelling Spatial-Temporal Information. Yupo Chan, PhD PE Professor & Founding Chair Department of Systems Engineering University of Arkansas at Little Rock. Underlying Principles for. Siting Facility location

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location transport and land use modelling spatial temporal information

Location, Transport and Land-use: Modelling Spatial-Temporal Information

Yupo Chan, PhD PE

Professor & Founding Chair

Department of Systems Engineering

University of Arkansas at Little Rock

underlying principles for
Underlying Principles for
  • Siting

Facility location

Competitive allocation of products & service

  • Product/service delivery

Location-routing

  • Community development

Land-use planning

Spatial forecasting

when asked about the three most important factors for fast food success

When asked about the three most important factors for fast-food success,

McDonald\'s founder :

"Location, location, location.”

E-Commerce:

Location, price, service

extremal solution
Extremal Solution
  • Network facility-location models
  • Nodal-optimality property
  • Extremal conditions also exist in planar location models
image processing using p medoid method
Image Processing Using p-medoid Method

Original Picture (from GOES satellite IR2 channel)

slide8

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(a) Raw image

(b) Spectral pattern- recognition (w=0)

(c) Spectral and spatial pattern-recognition (0.5<w< 1.0)

Legend

* Representative

pixel

Contextual image-classification using p-medoid method

result
Result

Classification using p-medoid (3 classes)

W=0.5

slide10

3-dimensional Space-filling Curve

z

j

i

Y

X

Legend

demands

facility

i, i´

j

slide11

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i Hospital XiLatitude YiLongitude Zi Patients 

1 Charlotte 35.21 80.44 0 0.03125

2 Ft Gordon 33.37 81.97 39 0.8125

3 Ft Bragg 35.17 79.02 234 0.8594

4 Ft Jackson 33.94 81.12 44 0.9063

5 Charleston SC 32.90 80.04 29 0.9531

Medical-evacuation Problem

spatial location allocation
Spatial Location & Allocation
  • Gaming
  • Generalized transportation model

– Includes regional input-outputs

  • Equilibrium vs. Disequilibrium

–Generalized multi-regional growth equilibria

  • Entropy

–freq. with which an event occurs

  • Entropy maximization

–to capture all possible patterns (information-minimization or spatial uncertainty principle)

slide16

Legend

Wi Facility in zone i

pi Price of goods and services at zone i

ri Land rent in zone i

A probable configuration of zonal activities

slide17

Facility

stock at

zone 1

W3(t)

W2(t)

W1(t)

W4(t)

Facility

stock at

zone 2

0.22–

0.2–

0.4–

0.17–

0.26–

0.3–

0.29 –

0.12 –

0.2 –

Facility

stock at

zone 3 & 4

time t

time t

time t

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< 14

= 70

= 70

 = 0.35

 = 14

 = 70

 = 14

 = 0.35

Responses to a New Shopping Center in zone 2

slide18

Dallas

1 2 3 4 . . .

STUDY AREA

San Antonio

Houston

. . . 398 399 400

Pixel map of Texas Gulf Coast

random or poisson field
Random or Poisson Field
  • Backshift operator, lag operator, image-processing mask, & spatial location/allocation

All based on a weight matrix

  • Homoscedasticity, stationarity, homogeneity

If the correlation parameters are finite, the derived local averaging field become a continuous parameter Gaussian field.

  • Ergodicity and isotropy

A useful property & through proper local-averaging, such properties can often be obtained

emerging techniques for
Emerging Techniquesfor
  • Emergency-response to natural and manmade hazards
  • Supply-chain management
  • Intelligent transportation systems
  • Real-estate development
  • Urban land-use plans
  • Satellite remote-sensing
  • Environmental planning
  • Infrastructure management
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