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Fundamentals of GIS
Civil Engineering Applications
• Transportation
• Watershed analysis
• Remote sensing
Fundamentals of GIS
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
Fundamentals of GIS
Location-Allocation Inputs
• Customer or demand locations
• Potential site locations and/or
existing facilities
• Street network or Euclidean
distance
• The problem to solve
Fundamentals of GIS
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
Fundamentals of GIS
Initial Configuration
(From Jay Sandhu, ESRI)
Fundamentals of GIS
Available Sites
(From Jay Sandhu, ESRI)
Fundamentals of GIS
Final Configuration
(From Jay Sandhu, ESRI)
Fundamentals of GIS
Vehicle Routing
(From Jay Sandhu, ESRI)
Fundamentals of GIS
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)
Fundamentals of GIS
Demand (population density)
(From Jay Sandhu, ESRI)
Fundamentals of GIS
Possible Candidate Sites…?
(From Jay Sandhu, ESRI)
Fundamentals of GIS
Feasible Candidate Sites
(From Jay Sandhu, ESRI)
Fundamentals of GIS
Optimal One Site
(From Jay Sandhu, ESRI)
Fundamentals of GIS
Optimal Two Sites
(From Jay Sandhu, ESRI)
Fundamentals of GIS
Optimal Six Sites
(From Jay Sandhu, ESRI)
Fundamentals of GIS
Optimal Nine Sites
(From Jay Sandhu, ESRI)
Fundamentals of GIS
Coverage vs. Distance
(From Jay Sandhu, ESRI)
Fundamentals of GIS
Other Transportation Applications
• Planning & locating new roadway
corridors
(from NCRST-E)
Fundamentals of GIS
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
Fundamentals of GIS
Mean
Household
Evacuation
Time
Standard Deviation in
Household Evacuation
Time
Mean
Household
Evacuation
Time
Standard Deviation in
Household Evacuation
Time
(1 exit route) (2 exit routes)
(from NCRST-H)
Evacuation scenario
Fundamentals of GIS
Watershed Characterization
• Relate physical characteristics to
water quality & quantity
• Data – land use & land cover,
geology, soils, hydrography &
topography – related to hydrological
properties
Fundamentals of GIS
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
 cross sections
 assumed cross sections
 boundary conditions
Cross sections
 gaging station
 water treatment plant
 wastewater treatment plant
Boundary conditions
0
100
200
300
400
500
600
700
11/1/1998 2/9/1999 5/20/1999 8/28/1999 12/6/1999 3/15/2000
Time (date)
Flow
(m3/sec)
measured
calculated
03231500
Fundamentals of GIS
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
Watersheds Land use
Soils types
DEM with drainage network
Hydrologic models
USGS empirical method
TR55
Area- Discharge method
ADAPT model
Portage River Basin, Ohio
ADAPT's Hydrological Output for Needles Creek at County Line Rd for 2001
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
120 140 160 180 200 220 240 260
Days
Total
daily
runoff
(
in)
ADAPT
Pressure Transducer
Fundamentals of GIS
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
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
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
Urban Area Change from 1984 - 1999
Urban Area, 1984
Urban Area, 1999
Landuse 1984(km2
) 1999(km2
) Change %
Ashland Urban 25 52 35.7
Ashland Agriculture 504 479 -2.6
Crawford Urban 26 43 24.9
Crawford Agriculture 723 804 5.3
Delaware Urban 42 98 40.5
Delaware Agriculture 707 657 -3.6
Fairfield Urban 36 94 44.5
Fairfield Agriculture 737 660 -5.5
Franklin Urban 411 685 25.0
Franklin Agriculture 613 410 -19.8
Holmes Urban 17 47 46.4
Holmes Agriculture 403 385 -2.3
Knox Urban 17 37 37.1
Knox Agriculture 658 626 -2.5
Licking Urban 54 102 31.2
Licking Agriculture 858 725 -8.4
Madison Urban 22 37 25.0
Madison Agriculture 898 1017 6.2
Marion Urban 44 64 18.3
Marion Agriculture 743 819 4.9
Morrow Urban 12 22 31.2
Morrow Agriculture 615 662 3.7
Perry Urban 14 26 32.0
Perry Agriculture 366 224 -24.0
Richland Urban 47 73 21.5
Richland Agriculture 587 594 0.6
Union Urban 30 42 17.1
Union Agriculture 792 849 3.5
Wayne Urban 77 106 15.8
Wayne Agriculture 715 751 2.4
Wyandot Urban 27 69 44.7
Wyandot Agriculture 784 787 0.2
MSS data - 19 Jun 75 MSS data - 1 Aug 86 TM data - 22 Jun 92
Fundamentals of GIS
Stream Water Quality in the 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.
Maumee River Basin
Ln(Y) = -0.125 + 1.39Ln(B2) + 1.03Ln(B3/B4) 84.1
(%) Proposed Equation r
Y = Predicted Suspended Sediment Concentration (mg/L)
B1,B2,B3,B4 = Reflectance (%) in ETM+ Bands 1,2,3,4
10
100
4 6 8 10 12 14 16
Reflectance (%)
Suspended
Sediment
Concentration
(mg/L)
Date Suspended Sediment Average
Concentration (mg/L) Reflectance (%)
15-Jul-99 27 11.6
16-Aug-99 22 9.1
1-Sep-99 19 8.2
17-Sep-99 14 7.8
4-Nov-99 8 4.5
27-Mar-00 56 9.5
14-May-00 45 12.9
1-Jul-00 62 9.8
19-Sep-00 81 14.8
Suspended Sediment Concentration Model
Waterville Station – Maumee River Basin, Ohio
Scale (Km)
20 0
27 March 2000 (56)
W
14 May 2000 (62)
1 July 2000 (45)
W
19 September 2000 (81)
W
W
Fundamentals of GIS
Example Applications
• Links to websites
– The District
– Urban development
– Lake Superior
– Rutgers University
– OhioView

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GISapplication.ppt

  • 1. Fundamentals of GIS Civil Engineering Applications • Transportation • Watershed analysis • Remote sensing
  • 2. Fundamentals of GIS 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
  • 3. Fundamentals of GIS Location-Allocation Inputs • Customer or demand locations • Potential site locations and/or existing facilities • Street network or Euclidean distance • The problem to solve
  • 4. Fundamentals of GIS 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
  • 5. Fundamentals of GIS Initial Configuration (From Jay Sandhu, ESRI)
  • 6. Fundamentals of GIS Available Sites (From Jay Sandhu, ESRI)
  • 7. Fundamentals of GIS Final Configuration (From Jay Sandhu, ESRI)
  • 8. Fundamentals of GIS Vehicle Routing (From Jay Sandhu, ESRI)
  • 9. Fundamentals of GIS 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)
  • 10. Fundamentals of GIS Demand (population density) (From Jay Sandhu, ESRI)
  • 11. Fundamentals of GIS Possible Candidate Sites…? (From Jay Sandhu, ESRI)
  • 12. Fundamentals of GIS Feasible Candidate Sites (From Jay Sandhu, ESRI)
  • 13. Fundamentals of GIS Optimal One Site (From Jay Sandhu, ESRI)
  • 14. Fundamentals of GIS Optimal Two Sites (From Jay Sandhu, ESRI)
  • 15. Fundamentals of GIS Optimal Six Sites (From Jay Sandhu, ESRI)
  • 16. Fundamentals of GIS Optimal Nine Sites (From Jay Sandhu, ESRI)
  • 17. Fundamentals of GIS Coverage vs. Distance (From Jay Sandhu, ESRI)
  • 18. Fundamentals of GIS Other Transportation Applications • Planning & locating new roadway corridors (from NCRST-E)
  • 19. Fundamentals of GIS 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
  • 20. Fundamentals of GIS Mean Household Evacuation Time Standard Deviation in Household Evacuation Time Mean Household Evacuation Time Standard Deviation in Household Evacuation Time (1 exit route) (2 exit routes) (from NCRST-H) Evacuation scenario
  • 21. Fundamentals of GIS Watershed Characterization • Relate physical characteristics to water quality & quantity • Data – land use & land cover, geology, soils, hydrography & topography – related to hydrological properties
  • 22. Fundamentals of GIS 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
  • 23.  cross sections  assumed cross sections  boundary conditions Cross sections  gaging station  water treatment plant  wastewater treatment plant Boundary conditions
  • 24. 0 100 200 300 400 500 600 700 11/1/1998 2/9/1999 5/20/1999 8/28/1999 12/6/1999 3/15/2000 Time (date) Flow (m3/sec) measured calculated 03231500
  • 25. Fundamentals of GIS 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
  • 26. Watersheds Land use Soils types DEM with drainage network Hydrologic models USGS empirical method TR55 Area- Discharge method ADAPT model Portage River Basin, Ohio ADAPT's Hydrological Output for Needles Creek at County Line Rd for 2001 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 120 140 160 180 200 220 240 260 Days Total daily runoff ( in) ADAPT Pressure Transducer
  • 27. Fundamentals of GIS Remote Sensing • Image backdrop • Source of information on: – land use/land cover – vegetation type, distribution, condition – surface waters – river networks – geomorphology – monitor change
  • 28. 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
  • 29. 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
  • 30. Urban Area Change from 1984 - 1999 Urban Area, 1984 Urban Area, 1999 Landuse 1984(km2 ) 1999(km2 ) Change % Ashland Urban 25 52 35.7 Ashland Agriculture 504 479 -2.6 Crawford Urban 26 43 24.9 Crawford Agriculture 723 804 5.3 Delaware Urban 42 98 40.5 Delaware Agriculture 707 657 -3.6 Fairfield Urban 36 94 44.5 Fairfield Agriculture 737 660 -5.5 Franklin Urban 411 685 25.0 Franklin Agriculture 613 410 -19.8 Holmes Urban 17 47 46.4 Holmes Agriculture 403 385 -2.3 Knox Urban 17 37 37.1 Knox Agriculture 658 626 -2.5 Licking Urban 54 102 31.2 Licking Agriculture 858 725 -8.4 Madison Urban 22 37 25.0 Madison Agriculture 898 1017 6.2 Marion Urban 44 64 18.3 Marion Agriculture 743 819 4.9 Morrow Urban 12 22 31.2 Morrow Agriculture 615 662 3.7 Perry Urban 14 26 32.0 Perry Agriculture 366 224 -24.0 Richland Urban 47 73 21.5 Richland Agriculture 587 594 0.6 Union Urban 30 42 17.1 Union Agriculture 792 849 3.5 Wayne Urban 77 106 15.8 Wayne Agriculture 715 751 2.4 Wyandot Urban 27 69 44.7 Wyandot Agriculture 784 787 0.2
  • 31. MSS data - 19 Jun 75 MSS data - 1 Aug 86 TM data - 22 Jun 92
  • 32. Fundamentals of GIS Stream Water Quality in the 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. Maumee River Basin
  • 33. Ln(Y) = -0.125 + 1.39Ln(B2) + 1.03Ln(B3/B4) 84.1 (%) Proposed Equation r Y = Predicted Suspended Sediment Concentration (mg/L) B1,B2,B3,B4 = Reflectance (%) in ETM+ Bands 1,2,3,4 10 100 4 6 8 10 12 14 16 Reflectance (%) Suspended Sediment Concentration (mg/L) Date Suspended Sediment Average Concentration (mg/L) Reflectance (%) 15-Jul-99 27 11.6 16-Aug-99 22 9.1 1-Sep-99 19 8.2 17-Sep-99 14 7.8 4-Nov-99 8 4.5 27-Mar-00 56 9.5 14-May-00 45 12.9 1-Jul-00 62 9.8 19-Sep-00 81 14.8 Suspended Sediment Concentration Model Waterville Station – Maumee River Basin, Ohio
  • 34. Scale (Km) 20 0 27 March 2000 (56) W 14 May 2000 (62) 1 July 2000 (45) W 19 September 2000 (81) W W
  • 35. Fundamentals of GIS Example Applications • Links to websites – The District – Urban development – Lake Superior – Rutgers University – OhioView

Editor's Notes

  1. Landsat-7 Images from nine date were selected along the Maumee River. A window of 3-by-3 pixels was defined over the Waterville Station.