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GIS Applications in Civil Engineering Carolyn J. Merry Dept. of Civil & Environmental Engineering & Geodetic Science Col PowerPoint Presentation
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GIS Applications in Civil Engineering Carolyn J. Merry Dept. of Civil & Environmental Engineering & Geodetic Science College of Engineering merry.1@osu.edu. Civil Engineering Applications. Transportation Watershed analysis Remote sensing. Location-Allocation.

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slide1

GIS Applications in Civil EngineeringCarolyn J. MerryDept. of Civil & Environmental Engineering & Geodetic ScienceCollege of Engineeringmerry.1@osu.edu

civil engineering applications
Civil Engineering Applications
  • Transportation
  • Watershed analysis
  • Remote sensing
location allocation
Location-Allocation
  • Finding a subset of locations from a set of potential or candidate locations that best serve some existing demand so as minimize some cost
  • Locate sites to best serve allocated demand
  • Application areas are warehouse location, fast food locations, fire stations, schools
location allocation inputs
Location-Allocation Inputs
  • Customer or demand locations
  • Potential site locations and/or existing facilities
  • Street network or Euclidean distance
  • The problem to solve
location allocation outputs
Location-Allocation Outputs
  • The best sites
  • The optimal allocation of demand locations to those sites
  • Lots of statistical and summary information about that particular allocation
initial configuration
Initial Configuration

(From Jay Sandhu, ESRI)

available sites
Available Sites

(From Jay Sandhu, ESRI)

final configuration
Final Configuration

(From Jay Sandhu, ESRI)

vehicle routing
Vehicle Routing

(From Jay Sandhu, ESRI)

synergy between spatial data and analysis
Synergy between spatial data and analysis
  • Imagine you are a national retailer
  • You need warehouses to supply your outlets
  • You do not wish the warehouses to be more than 1000 km from any outlet

(Example from Jay Sandhu, ESRI)

demand population density
Demand (population density)

(From Jay Sandhu, ESRI)

possible candidate sites
Possible Candidate Sites…?

(From Jay Sandhu, ESRI)

feasible candidate sites
Feasible Candidate Sites

(From Jay Sandhu, ESRI)

optimal one site
Optimal One Site

(From Jay Sandhu, ESRI)

optimal two sites
Optimal Two Sites

(From Jay Sandhu, ESRI)

optimal six sites
Optimal Six Sites

(From Jay Sandhu, ESRI)

optimal nine sites
Optimal Nine Sites

(From Jay Sandhu, ESRI)

coverage vs distance
Coverage vs. Distance

(From Jay Sandhu, ESRI)

other transportation applications
Other Transportation Applications
  • Planning & locating new roadway corridors

(from NCRST-E)

transportation emergency operations
Transportation – Emergency Operations
  • Transportation maps are critical
  • Disaster response plans can be developed
  • Outside computer models used for advance warnings
  • Land use maps enhance emergency operations
slide21

Evacuation scenario

(1 exit route)

(2 exit routes)

(from NCRST-H)

watershed characterization
Watershed Characterization
  • Relate physical characteristics to water quality & quantity
  • Data – land use & land cover, geology, soils, hydrography & topography – related to hydrological properties
watershed applications
Watershed Applications
  • Estimate the magnitude of high-flow events, the probability of low-flow events
  • Determine flood zones
  • Identify high-potential erosion areas
  • For example, BASINS, HEC-RAS, MIKE11 models integrated with GIS
slide24

Cross sections

Boundary conditions

cross sections

assumed cross sections

 boundary conditions

gaging station

water treatment plant

 wastewater treatment plant

slope stability analysis
Slope Stability Analysis
  • Derive physical characteristics
    • area, perimeter, flow path length, maximum width, average closing angle, watershed topology, soil data
  • Derive watershed characteristics
    • watershed boundaries, drainage network, slope & aspect maps
slide27

Portage River Basin, Ohio

DEM with drainage network

Watersheds

Hydrologic models

USGS empirical method

TR55

Area- Discharge method

ADAPT model

Land use

Soils types

remote sensing
Remote Sensing
  • Image backdrop
  • Source of information on:
    • land use/land cover
    • vegetation type, distribution, condition
    • surface waters
    • river networks
    • geomorphology
    • monitor change
1984 land use map
1984 Land Use Map

Land use

Water: 249.43 km2

Urban: 1348.53 Km2

Forest: 10700.92 km2

Agriculture: 17780.62 km2

Pasture: 175.50 km2

Grass: 2609.45 km2

slide30

1999 Land Use Map

Land use

Water: 268.74 km2

Urban: 2312.35 Km2

Forest: 11182.39 km2

Agriculture: 16675.65 km2

Pasture: 1308.23km2

Grass: 1518.18 km2

slide31

Urban Area, 1984

Urban Area, 1999

Urban Area Change from 1984 - 1999

slide32

MSS data - 19 Jun 75

MSS data - 1 Aug 86

TM data - 22 Jun 92

stream water quality in the maumee river basin
Stream Water Quality in the Maumee River Basin

Maumee River Basin

9 Landsat-7 images over the Waterville station in the Maumee River Basin were selected.

A 3-by-3 pixel window over the Waterville station for each date was converted to % reflectance values. A least squares regression was used to correlate these % reflectance values with USGS ground data on suspended sediment concentration collected at the Waterville station.

slide34

Suspended Sediment Concentration Model

Waterville Station – Maumee River Basin, Ohio

(%) Proposed Equation r

Ln(Y) = -0.125 + 1.39Ln(B2) + 1.03Ln(B3/B4) 84.1

Y = Predicted Suspended Sediment Concentration (mg/L)

B1,B2,B3,B4 = Reflectance (%) in ETM+ Bands 1,2,3,4

slide35

W

W

W

Scale (Km)

20

0

W

14 May 2000 (62)

27 March 2000 (56)

19 September 2000 (81)

1 July 2000 (45)

example applications
Example Applications
  • Links to websites
    • The District
    • Urban development
    • Lake Superior
    • Rutgers University
    • OhioView