GIS Applications in Civil Engineering Carolyn J. Merry Dept.

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 Evacuation scenario Mean Household Evacuation Time Standard Deviation in Household Evacuation Time Mean Household Evacuation Time Standard Deviation in Household Evacuation Time (1 exit route) (from NCRST-H) (2 exit routes) 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  assumed cross sections  boundary conditions  gaging station  water treatment plant  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 USGS empirical method Land use TR55 Area- Discharge method ADAPT model ADAPT's Hydrological Output for Needles Creek at County Line Rd for 2001 ADAPT Pressure Transducer 0.70 Total daily runoff ( in) 0.60 0.50 0.40 0.30 0.20 0.10 0.00 120 140 160 180 200 Days 220 240 260 Soils types 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: Urban: Forest: Agriculture: Pasture: Grass: 249.43 km 2 1348.53 Km 2 10700.92 km 2 17780.62 km 2 175.50 km 2 2609.45 km 2 1999 Land Use Map Land use Water: Urban: Forest: Agriculture: Pasture: Grass: 268.74 km2 2312.35 Km2 11182.39 km2 16675.65 km2 1308.23km2 1518.18 km2 Urban Area Change from 1984 - 1999 Ashland Ashland Crawford Crawford Delaware Delaware Fairfield Fairfield Franklin Franklin Holmes Holmes Knox Knox Licking Licking Madison Madison Marion Marion Morrow Morrow Perry Perry Richland Richland Union Union Wayne Wayne Wyandot Wyandot Landuse 1984(km2) 1999(km2) Change % Urban 25 52 35.7 Agriculture 504 479 -2.6 Urban 26 43 24.9 Agriculture 723 804 5.3 Urban 42 98 40.5 Agriculture 707 657 -3.6 Urban 36 94 44.5 Agriculture 737 660 -5.5 Urban 411 685 25.0 Agriculture 613 410 -19.8 Urban 17 47 46.4 Agriculture 403 385 -2.3 Urban 17 37 37.1 Agriculture 658 626 -2.5 Urban 54 102 31.2 Agriculture 858 725 -8.4 Urban 22 37 25.0 Agriculture 898 1017 6.2 Urban 44 64 18.3 Agriculture 743 819 4.9 Urban 12 22 31.2 Agriculture 615 662 3.7 Urban 14 26 32.0 Agriculture 366 224 -24.0 Urban 47 73 21.5 Agriculture 587 594 0.6 Urban 30 42 17.1 Agriculture 792 849 3.5 Urban 77 106 15.8 Agriculture 715 751 2.4 Urban 27 69 44.7 Agriculture 784 787 0.2 Urban Area, 1984 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 Concentration (mg/L) Average Reflectance (%) (%) 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 Suspended Sediment Concentration (mg/L) 10 4 6 8 10 12 14 16 15-Jul-99 16-Aug-99 1-Sep-99 17-Sep-99 4-Nov-99 27-Mar-00 14-May-00 1-Jul-00 19-Sep-00 27 22 19 14 8 56 45 62 81 11.6 9.1 8.2 7.8 4.5 9.5 12.9 9.8 14.8 100 Reflectance (%) W W 27 March 2000 (56) 14 May 2000 (62) W W 20 Scale (Km) 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