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CE 525 GIS in Civil Engineering

CE 525 GIS in Civil Engineering. Dr. Souleyrette April 9, 2013. GIS Vision for the future – or present?. Esri’s take on GIS for CE. Civil engineering is about developing and sustaining infrastructure Broad Big data (volume, variety , velocity) Create, manage, analyze, visualize

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CE 525 GIS in Civil Engineering

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  1. CE 525 GIS in Civil Engineering Dr. Souleyrette April 9, 2013 GIS Vision for the future – or present?

  2. Esri’s take on GIS for CE • Civil engineering is about developing and sustaining infrastructure • Broad • Big data (volume, variety, velocity) • Create, manage, analyze, visualize • Projects and context • Database to re-use, share

  3. Serve it up…

  4. Spatial analysis • Intelligent, fast decisions • Discover patterns • Optimize • automate

  5. Infrastructure Life Cycle Architecture:

  6. Workflow

  7. Case Study—GIS Technology Refines Flood Insurance Rate Mapping Process

  8. Case Study—GIS System Model Integration Facilitates Storm Water Management

  9. Visualization benefits … • prioritize your work, • convince others of its importance, and • make good decisions

  10. Case Study—GIS Puts Australian Road Project in the Fast Lane

  11. Site Analysis parcel maps, zoning and city designations, environmental protection areas, aerial photos, and topographic and soil maps

  12. Critical Infrastructure Protection Emergency managers use the enterprise GIS database to • Identify critical infrastructure and hazards within affected areas. • Identify medical resources and route patients to nearest facilities. • Prepare evacuation routes for at-risk populations. • Provide accurate damage estimates. • Identify priorities for short-term recovery needs. • Assess long-term recovery needs.

  13. Minneapolis Quickly Solves Bridge Routing Problem with GIS Web Mapping Technology

  14. CAD Integration

  15. Spatial Analysis with Raster Datasets Francisco Olivera, Ph.D., P.E. SrikanthKoka Department of Civil Engineering Texas A&M University (Used by permission)

  16. Map analysis consists of inferring information – necessary for a given engineering/scientific task – from general information contained in digital spatial datasets. In map analysis with raster datasets, the digital spatial datasets consist of grids. Map Analysis

  17. To enable the raster data analysis capabilities, load the Spatial Analyst ArcGIS extension by clicking Tools/ Extensions/Spatial Analyst and then Tools/Customize/ Spatial Analyst. The Spatial Analyst adds a toolbar that contains a Spatial Analyst menu, a combo box Layer for selecting the layer, a Create contour tooland a Histogram tool. Spatial Analyst

  18. Grid Datasets

  19. (x, y) Number of columns Cell size Number of rows Grid Data Structure • Cellular-based data structure composed of square cells of equal size arranged in rows and columns that store the value of a terrain parameter • Cells that do not store a value are assigned a NODATA code and are called NODATA cells.

  20. Grid Properties • Type: Integer or Floating Point. • Depending on the type of numbers the grid cells store, a grid is considered Integer if it stores integer values or Floating Point if it stores real values. Floating Point grids store the same information as an Integer grid but take significantly much more storage space. • Status: Permanent or Temporary. • Many grids created in ArcGIS are stored as temporary files and are subject to be erased automatically. A temporary grid can be saved as a permanent grid by right-clicking on the layer name and then on Make Permanent.

  21. Value Attribute Table • Value Attribute Tables (VATs) are tables associated with grids which have two fields: Value and Count. The Value field lists all values found in the grid and the Count field lists the number of cells that have that value. • Only Integer grids have VATs. • VATs are created automatically for Integer grids with less than 500 unique values or with a range of values that does not exceed 100,000.

  22. Analysis Extent and Cell Size • Analysis Extent and Cell Size are defined for a Data Frame. • To define the Analysis Extent and Cell Size click on Spatial Analyst/Options and then on the Extent or Cell Size tabs. • The Analysis Mask flags the cells – within the Analysis Extent – where grid values are calculated. Outside the mask, grid cells are assigned NODATA. • Analysis Extent defines the size of the grid rectangle.

  23. Analysis Extent and Cell Size • Analysis Cell Size defines the length of the cell side. • The Number of Rows and Number of Columns are redundant if the Analysis Extent and Cell Size have been defined already. If all the grids of a data frame have to be aligned and with their cells coinciding exactly, the analysis Extent and Cell Size must be set before any grids are created.

  24. Feature-to-Raster Conversion • Point-to-grid: • Each point is converted into the grid cell where it is located. The cell value is a user-selected attribute of the point feature class. • If two points coincide in the same cell, one is chosen randomly for the cell value. Coincidence of two or more points within a cell might reflect inconsistency between the resolution of the grid and point dataset. • To convert a point dataset into a grid, click on Spatial Analyst/Convert/ Features to Raster in the Spatial Analyst toolbar.

  25. Feature-to-Raster Conversion • Line-to-grid: • Each line is converted into the grid cells with which it intersects. The cell value is a user-selected attribute of the line dataset. • If two lines coincide in the same cell, one is chosen randomly for the cell value. • To convert a line dataset into a grid, in the Spatial Analyst toolbar click on Spatial Analyst/Convert/ Features to Raster.

  26. Vector-to-Raster Conversion • Polygon-to-grid: • Each polygon is converted into the grid cells whose centroid it contains. The cell value is a user-selected attribute of the polygon dataset. • If two polygons coincide in the same cell (overlap), one is chosen randomly for the cell value. • To convert a polygon dataset into a grid, click on Spatial Analyst/ Convert/Features to Raster in the Spatial Analyst toolbar.

  27. Raster-to-Feature Conversion • Raster-to-line: • It is not an unambiguously defined process. • Raster-to-point: • Each no NODATA cell is represented by a point located in the center of the cell. • The cell value is stored in an attribute Grid_Code of the polygon dataset. • To convert a grid into a point dataset, click on the Spatial Analyst/Convert/Raster to Features in the Spatial Analyst toolbar.

  28. Raster-to-Feature Conversion • Raster-to-polygon: • All adjacent cells (i.e., share a side) with the same value are aggregated into a single polygon. • Grids have to be Integer grids. • The cell value is stored in an attribute Grid_Code of the polygon dataset. • Polygon outlines are smoothed to avoid jagged edges. • To convert a polygon dataset into a grid, click on the Spatial Analyst/ Convert/Raster to Features in Spatial Analyst toolbar.

  29. Raster Functions • Raster functions create output grids using input grids as arguments. • Raster functions are classified into: • Local functions • Focal functions • Zonal functions • Global functions

  30. Local Functions • The value of an output grid cell depends on the value of the cells of the input grids that have the same location. Neighbor cells have no influence on the output values. • Local functions can have one or many input grids as arguments. Input Output

  31. Focal Functions • The value of an output grid cell depends on the value of the cells of the input grids in the neighborhood. • The neighborhood can be defined in different ways. • Focal functions usually have one input grid as argument, but could have more than one. Input Output

  32. Zonal Functions • The value of an output grid cell depends on the value of the cells of the input grids of the same zone. • A zones grid has to be one of the function arguments. • Besides the zones grid, zonal functions usually have only one input grid as argument, but could have more than one. Input Output

  33. Global Functions • The value of an output grid cell depends on the value of all the cells of the input grids. • Global functions usually have one input grid as argument, but could have more than one. Input Output

  34. Reclassification • Reclassify creates a new grid by replacing the input cell values with new output cell values. • New cell values are based on new information or grouping existing values together. • To reclassify, click on Spatial Analyst/Reclassify.

  35. Straight Line Distance • Straight Line gives the distance from each cell in the grid to the closest source (point or line dataset). • Optionally, Create Allocation and Create Direction can be used to create grids with cells representing the value of the source and direction (out of eight options) of the source, respectively. • To use the straight line distance function, click on Spatial Analyst/ Distance/Straight Line.

  36. Allocation • Allocation is used to allocate cells to the closest source. The source can be a point feature class or any grid or feature class. It is similar to the Straight Line Allocation function. • To create an allocation grid click on Spatial Analyst/ Distance/Allocation.

  37. Cost Weighted Distance • The Cost Weighted Distance function creates a grid in which each cell represents the least accumulative cost from that cell to the nearest source (cost can be money, time, etc.). • Needs a cost grid; for example: Cost raster = f(slope, landuse). • To create a cost weighted distance grid, click on Spatial Analyst/Distance/Cost Weighted.

  38. Interpolate to Raster • Interpolate to raster is a global function which creates a grid that stores values interpolated from a point feature dataset. • The options are Inverse Distance Weighted, Spline and Kriging. • To create an interpolated surface, click on Spatial Analyst/Interpolate to Raster.

  39. Create contours creates a line feature dataset in which the lines connect points of equal cell value. To create contours, click on Spatial Analyst/Surface Analysis/Contour. Surface Analysis-Contour

  40. Surface Analysis-Slope • Slope is a neighborhood function which creates a grid of maximum rate of change of the cell values of the input grid. The slope is derived based on a 3 x 3–cell neighborhood. • Slope does not indicate the direction of the calculated slope. • To create a slope surface, click on Spatial Analyst/Surface Analysis/Slope.

  41. Surface Analysis-Aspect • Aspect is a neighborhood function which creates a grid of aspect or direction of maximum slope of the cells of the input grid. • Aspect values are in degrees with 0° for the North direction. • To create a aspect surface, click on Spatial Analyst/ Surface Analysis/Aspect.

  42. Surface Analysis-Hillshade • Hillshade is a neighborhood function which creates a grid of surface brightness for a given position of a light source. • Hillshade values can be used to enhance the legend of themes. • To create a hillshade surface, click on Spatial Analyst/Surface Analysis/ Hillshade.

  43. Surface Analysis-Viewshed • Viewshed is a global function which creates a grid of visible and non-visible surface from an observation point. • To create a viewshed grid, click on Spatial Analyst/ Surface Analysis/ Viewshed.

  44. Surface Analysis-Cut/Fill • Cut/Fill is a local function that creates a surface with cells representing the area and volume of cut or fill needed to modify a source surface to a destination surface. • To create a cut/fill surface, click on Spatial Analyst/Surface Analysis/Cut/Fill.

  45. Cell Statistics • Cell Statistics is a local function that creates a grid with cell values equal to a statistic of the corresponding cell values of the input grids. • The statistic can be: majority, maximum, mean, median, minimum, minority, range, standard deviation, sum and variety. • To calculate the statistics of a set of grids, click Spatial Analyst/Cell Statistics…

  46. Neighborhood Statistics • Neighborhood Statistics is a focal function that creates a grid with cell values equal to a statistic of the neighborhood cell values of the input grid. • The statistic can be: majority, maximum, mean, median, minimum, minority, range, standard deviation, sum and variety. • The neighborhood can have different shapes. • To calculate neighborhood statistics, select the grid and click on Spatial Analyst/Neighborhood Statistics… Mean over a 20-cell square neighborhood

  47. Zonal Statistics • Zonal Statistics is a zonal function that creates a table with all the statistics of the cell values within each zone. Table rows correspond to zones and columns to statistics. This function can also create a chart of user-specified statistics. • The statistics are: majority, maximum, mean, median, minimum, minority, range, standard deviation, sum and variety. • The zones can be defined by polygons or (integer) grid cells with the same value. • To summarize by zones, click on Spatial Analyst/Zonal Statistics…

  48. Raster Calculator • The Raster Calculator is a calculator that evaluates local functions.

  49. Histogram • The Histogram is a global function that creates a column chart of the cell values. • To create a histogram, click on the Histogram tool. Histogram of cell values of the reclassification of elevation grid into 10 classes

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