GIS Applications in Civil Engineering Carolyn J. Merry Dept by zwd14115

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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

                          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
                                                                           Standard Deviation in
                                   Standard Deviation in        Mean       Household Evacuation

Evacuation scenario     Mean       Household Evacuation
                                                              Household           Time
                                          Time
                      Household                               Evacuation
                      Evacuation                                 Time
                        Time




                            (1 exit route)                        (2 exit routes)

   (from NCRST-H)
                                                           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



                            Fundamentals of GIS
    Cross sections           Boundary conditions




 cross sections            gaging station
 assumed cross sections    water treatment plant
 boundary conditions       wastewater treatment plant
                700
                                                                   measured
                                                                   calculated
                600


                500
Flow (m3/sec)



                400


                300


                200


                100


                 0
                11/1/1998   2/9/1999   5/20/1999    8/28/1999   12/6/1999   3/15/2000
                                             Time (date)



                                           03231500
     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




                                   Fundamentals of GIS
                                             Portage River Basin, Ohio




                                                 DEM with drainage network

Watersheds                                   Hydrologic models                                                                Land use
                                             USGS empirical method
                                             TR55
                                             Area- Discharge method
                                             ADAPT model


                                                                       ADAPT's Hydrological Output for Needles Creek at County Line Rd for 2001
                                           ADAPT
                                           Pressure Transducer
                                          0.70

                                          0.60
               Total daily runoff ( in)




                                          0.50

                                          0.40

                                          0.30

                                          0.20

                                          0.10
 Soils types                              0.00
                                                 120             140            160           180          200          220          240          260
                                                                                                       Days
           Remote Sensing

• Image backdrop
• Source of information on:
  – land use/land cover
  – vegetation type, distribution, condition
  – surface waters
  – river networks
  – geomorphology
  – monitor change


                                     Fundamentals of GIS
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
                                                                    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
                                     Urban Area, 1984   Wyandot     Agriculture    784       787        0.2
                                     Urban Area, 1999
MSS data - 19 Jun 75   MSS data - 1 Aug 86   TM data - 22 Jun 92
                     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.


                                                    Fundamentals of GIS
                  Suspended Sediment Concentration Model
                 Waterville Station – Maumee River Basin, Ohio

   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
                                                                                     100
14-May-00              45                    12.9




                                                         Suspended Sediment Concentration
  1-Jul-00             62                      9.8
19-Sep-00              81                    14.8



(%)          Proposed Equation                       r               (mg/L)


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

 Y = Predicted Suspended Sediment Concentration (mg/L)                                      10

 B1,B2,B3,B4 = Reflectance (%) in ETM+ Bands 1,2,3,4
                                                                                                 4   6   8        10       12   14   16

                                                                                                         Reflectance (%)
W                        W




    27 March 2000 (56)       14 May 2000 (62)




W
                         W                             Scale (Km)

                                                  20           0




      1 July 2000 (45)   19 September 2000 (81)
      Example Applications

• Links to websites
  – The District
  – Urban development
  – Lake Superior
  – Rutgers University
  – OhioView




                         Fundamentals of GIS

								
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