Vertical Mapper Version 3.
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Table of Contents Chapter 1: Introduction to Vertical Mapper 3.7. . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 What’s New in Vertical Mapper 3.7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10 Import Raster Data as Vertical Mapper Grid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10 Upgrade to the Vertical Mapper MFAL library . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10 Operating System Support. . . . . . . . . . . . . .
Table of Contents Choosing an Interpolation Technique. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Using the Interpolation Wizard to Create a Grid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Triangulation with Smoothing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Exploring TIN Interpolation: Create TRI Dialog Box . . . . . . . . . . . . . . . . . . . . . . . . . . .
Table of Contents Suggested Reading on Trade Area Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .67 Chapter 5: Creating Grids Using Other Methods . . . . . . . . . . . . . . . . . . . . . . . . . 69 Creating Grids Using Other Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .70 Grid Import Formats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .70 Importing Grids . . . . . . . . . . . . . . .
Table of Contents Smoothing a Grid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 What is Smoothing?. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 Using the Smoother Utility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 Contouring with Grids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Table of Contents Exporting Grids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .141 Using the Export Grid Tool. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .142 Exploring the Export Grid Dialog Box. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .142 Using the Classified Grid Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Table of Contents Performing Simple Point Aggregation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176 Exploring the Aggregation Technique and Distance Dialog Box . . . . . . . . . . . . . . . . 176 Point Aggregation with Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 Exploring the Select Coincident Point Technique Dialog Box . . . . . . . . . . . . . . . . . . .
Introduction to Vertical Mapper 3.7 This manual provides you with the necessary information to create mapping solutions for a wide range of applications. Before using this documentation, you should be familiar with the Windows environment. It is assumed that you know how to access ToolTips and shortcut menus, move and copy objects, resize dialog boxes, expand and collapse directory trees, and are familiar with the basic functionality of MapInfo Professional.
What’s New in Vertical Mapper 3.7 Import Raster Data as Vertical Mapper Grid The Vertical Mapper 3.7 contains a new Import Raster Data as Vertical Mapper Grid feature which will enable you to convert raster data such as *.bmp file into a Vertical Mapper Grid file. The supported Raster Data formats: • • • • • • • • Bitmap (*.bmp) JPEG (*.jpg, *.jpeg) GIF (*.gif) ECW (*.ecw) JPEG 2000 (*.jp2) Portable Network Graphics (*.png) Geo TIFF/Tagged Image Format (*.tif) Multi-resolution Seamless Image Database (*.
Chapter 1: Introduction to Vertical Mapper 3.7 Installing Vertical Mapper You install Vertical Mapper in the same way you install any other conventional application for the Windows operating system. System Requirements Below are the guidelines for minimum and recommended system requirements. Note that hardware requirements do vary based on your use of the product and your system.
Installing Vertical Mapper These are the recommended system requirements for Vertical Mapper 3.
Chapter 1: Introduction to Vertical Mapper 3.7 7. On the Setup Type page, choose the setup type that best suits your needs. • • If the chosen setup type is Complete, click Next. On the Choose Destination Folder page, choose the folder where you want to install Vertical Mapper and click Next. If the chosen setup type is Custom, click Next and on the Custom Setup page, choose the components you want to install and click Next.
Vertical Mapper Documentation 4. When the installation process has finished, click Finish. 5. Click Exit to exit the DemoShield application or see what is available on the CD or find contact information. Note One can install Vertical Mapper 3.5 and 3.7 on the same machine but in different installation folders. But one has to take care that when running MapInfo Professional, only one of the Vertical Mapper versions should be loaded.
Chapter 1: Introduction to Vertical Mapper 3.7 Developing Applications with Vertical Mapper The Vertical Mapper Software Developer’s Kit is available as a separate product. It gives you access to Vertical Mapper interpolation, modeling, contouring, and analysis functions, enabling you to build custom applications and automate repetitive operations. Getting Technical Support You can get technical support by phone or fax.
Send us Your Comments 16 Vertical Mapper 3.
Understanding Grids This section discusses the concept of grids and explains how they are used in Vertical Mapper. In this chapter: Using Vertical Mapper to Display Spatial Data . . . . . . . . . . . . . . .16 Working with Grid Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17 Understanding Grids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17 Understanding Spatial Estimation Techniques . . . . . . . . . . . . . . .
Using Vertical Mapper to Display Spatial Data Vertical Mapper brings two main benefits to MapInfo Professional: • • It provides a mapping technique for calculating and displaying the trends of data that vary continuously over geographic space. It provides a mechanism for sophisticated comparison and analysis of multiple map layers. Three main object types are currently used by MapInfo Professional to represent the spatial distribution of data: regions, lines, and points.
Chapter 2: Understanding Grids Working with Grid Files You should be familiar with the concept of map layers when you work with Vertical Mapper. Each unique layer of information exists as a separate file that can be added as a layer in a Map window. Various map layers covering the same geographical area can hold different types of information. Just as each layer can be visualized above or below another layer, layers can be compared using spatial analysis functions.
Understanding Grids What is a Grid? A grid is made up of regularly spaced square cells arranged over a given area. Each cell has a node, which is a point located at its centre. Each cell can be given a value and a colour representing the value. If there are several cells between two known locations, such as two contour lines, the change in colour indicates how the values change between the locations.
Chapter 2: Understanding Grids An example of a numeric grid showing the continuous variation of elevation across an area. Classified Grids Classified grids are best used to represent information that is more commonly restricted to a defined boundary. They are used in the same way that a MapInfo Professional region is used to describe a boundary area, such as a land classification unit or a census district. In this case, the grid file does not represent information that varies continuously over space.
Understanding Spatial Estimation Techniques Grid File Architecture Every Vertical Mapper grid file (.grc or .grd) is divided into two sections. The first section, called the file header, contains several pieces of information including the following: • • • • • • Map name Map size (number of cells in height and width) Cell size Coordinates of first cell Grid Projection Grid value description The second section, the body of the grid file, contains the attribute data for every cell in the map.
Chapter 2: Understanding Grids • • • • Natural Neighbour (simple and advanced) Rectangular Kriging Custom Point Estimation Modeling Techniques These techniques create grids of derived values. For example, one of the modeling techniques included with Vertical Mapper is trade area analysis. This modeling technique uses store locations and their relative “attractiveness” to calculate grid values measuring the percent probability of customer patronage.
Understanding Spatial Estimation Techniques 22 Vertical Mapper 3.
Creating Grids Using Interpolation This section describes the basic commands associated with the creation of numeric grid files using interpolation techniques. The Vertical Mapper Interpolation Wizard supports six interpolation techniques: • • • • • Triangulation with Smoothing (TIN) Inverse Distance Weighting (IDW) Natural Neighbour (simple and advanced) Rectangular Kriging Custom Point Estimation In this chapter: Grid Creation using Interpolation . . . . . . . . . . . . . . .
Types of Interpolation Grid Creation using Interpolation Interpolation is the process of estimating grid values using measured observations taken from a point file. New values calculated from the original point observations form a continuous, evenly spaced grid surface that “fills in the gaps” between the non-continuous points. Many mathematical formulae can be applied to estimating or interpolating grid values from an existing point file. There is no perfect solution, and many techniques are in use.
Chapter 3: Creating Grids Using Interpolation Natural Neighbour (Advanced) The Advanced option gives you access to a variety of controls in the Natural Neighbour interpolation technique that you can use to make subtle adjustments to the grid surface generated from a points table. Rectangular (Bilinear) Original data points are joined by a network of lines to build a rectilinear mesh.
Choosing an Interpolation Technique Data Type Possible Interpolation Elevation Triangular Irregular Network (TIN), Natural Neighbour (NN) Soil Chemistry Inverse Distance Weighting (IDW), Kriging Demographic NN, IDW, Kriging Drive Test NN 2. How accurate is the data? Some techniques assume that the value at every data point is an exact value and will honour it when interpolating. Other techniques assume that the value is more representative of an area.
Chapter 3: Creating Grids Using Interpolation Point Distribution Possible Interpolation Technique Rectangular can only handle data that is distributed in an evenly spaced pattern. Rectangular, NN, Kriging This type of linear pattern generally occurs when data is collected from aircraft. Samples are taken close together but flight lines are some distance apart. IDW, NN, Kriging This type of linear pattern generally occurs when samples are taken along roads. NN, Kriging 4.
Using the Interpolation Wizard to Create a Grid 5. Is it necessary to overshoot or undershoot the local minimum and maximum values? Overshooting and undershooting the local minimum and maximum values is generally necessary when interpolating elevation surfaces.
Chapter 3: Creating Grids Using Interpolation Triangulation with Smoothing Triangulation is a process of grid generation that is usually applied to data that requires no regional averaging, such as elevation readings. The surface created by triangulation passes through (honours) all of the original data points while generating some degree of “overshoot” above local high values and “undershoot” below local low values.
Triangulation with Smoothing A smooth grid surface is then fitted to the TIN using a bivariate fifth-order polynomial expression in the x- and y- direction for each triangle face. This method guarantees continuity and smoothness of the surface along the sides of each triangle and smoothness of the surface within each triangle.
Chapter 3: Creating Grids Using Interpolation Note Use the Ruler in MapInfo Professional to examine your point data file and measure gaps in the distribution of points over the map area. Use this information as a guideline in entering an appropriate value for the maximum triangle side length. The Coincident Point Distance box enables you to group or aggregate data points into a single new point with a recalculated value.
Triangulation with Smoothing The 5th Order Solution button enables you to apply a complex polynomial expression to the calculation of each grid node value. The calculation is based on solving a number of slope derivatives. The result is a more highly smoothed surface that displays minor angular artifacts from the original TIN. The Linear Solution button enables you to calculate the grid values directly from the TIN surface; therefore, no derivative slope solution is applied.
Chapter 3: Creating Grids Using Interpolation Inverse Distance Weighting Interpolation Inverse Distance Weighting (IDW) interpolation is a moving average interpolation technique that is usually applied to highly variable data. For certain data types, it is possible to return to the collection site and record a new value that is statistically different from the original reading but within the general trend for the area.
Inverse Distance Weighting Interpolation Exploring the Inverse Distance Weighted Interpolation Dialog Box The Inverse Distance Weighted Interpolation dialog box enables you to set a number of user-defined parameters in the algorithm. The Cell Size box enables you to set the cell size in real units. The grid dimensions (in cell units) vary inversely with cell size: the smaller the cell, the larger the grid file.
Chapter 3: Creating Grids Using Interpolation As the exponent increases, the influence a data point has on the calculated grid node decreases. In this example, the data point has the amount of influence indicated by A; however, if the exponent is increased to two, the amount of influence B is dramatically reduced. The Minimum # of Points box enables you to define the minimum number of points per zone, and the Maximum # of Points box enables you to define the maximum number of points per zone.
Inverse Distance Weighting Interpolation The search area is divided into two zones and a zone orientation set to match the distribution of the data points. This forces Vertical Mapper to use data points from two different sample paths when estimating grid values that lie between paths. The minimum and maximum number of points settings apply for each zone. In this figure, the zone orientation is set to 45 degrees.
Chapter 3: Creating Grids Using Interpolation With the search radius defined by the Search Radius setting, the Weight to Furthest Point Only check box enabled, and the maximum number of points set to 20, the decay curve will be based on the search radius indicated by the dotted line. Note .The default values for the search criteria and Number of zones, Zone orientation, and Radius Multiplier options are appropriate for most data. The File name box enables you to enter a new file name.
Natural Neighbour Interpolation Put simply, natural neighbour interpolation makes use of an area-weighting technique to determine a new value for every grid node. As shown in the next figure, a natural neighbour region is first generated for each data point. Then, a new natural neighbour region is generated at every node in the new grid which effectively overlies various portions of the surrounding natural neighbour regions defining each point.
Chapter 3: Creating Grids Using Interpolation The Interpolation Wizard provides two methods of performing natural neighbour interpolation. The simple option offers the first-time user a two-step process for implementing the interpolation method. Many of the controls have been pre-set to generate the most appropriate surface given the distribution of points. The Advanced option enables you to fine-tune the grid surface.
Natural Neighbour Interpolation • • The Smoothed, without overshoot option uses the slope-based solution discussed earlier. This variation of the Natural Neighbour method makes use of the slope of all adjacent points to calculate the area-weighted value of each grid node. Undershoot and overshoot are controlled by assigning a slope value of zero (horizontal) to all local minimum and maximum point values.
Chapter 3: Creating Grids Using Interpolation The Extents button displays a summary of the geographic size and the z-value range of the original point database, the density of the points, and the data value units. Exploring the Natural Neighbour: Solution Method Dialog Box The final step in the Advanced Natural Neighbour technique involves choosing the solution method and setting a number of interpolation parameters.
Natural Neighbour Interpolation Quantitatively, if the proportional natural neighbour area of a point is greater than 50 percent of the total grid node natural neighbour area, the Hermitian curve applies greater weight to this point. If the proportional natural neighbour area of a point is less than 50 percent of the total grid node natural neighbour area, the Hermitian curve applies lower weight to this point.
Chapter 3: Creating Grids Using Interpolation purposes and the processing time and file size. The default value is calculated by dividing the diagonal width of the point file by 500, considered an optimum number based on computing power required to solve this algorithm. The Triangle Size Limit box enables you to specify a Delaunay triangulation setting to limit the creation of natural neighbour regions around adjacent points you consider too far apart.
Rectangular Interpolation A radius is generated around each grid node from which the closest data point in each quadrant is selected to be used in the calculation. Exploring the Rectangular Interpolation Dialog Box The Rectangular Interpolation dialog box enables you to specify parameters for the gridding algorithm. Rectangular interpolation uses a bilinear method for estimating individual grid node values. At each grid node, a circular search area of a set radius is generated and divided into quadrants.
Chapter 3: Creating Grids Using Interpolation The Search Radius box enables you to define the maximum size, in map units, of a circular zone centred on each grid node within which point values from the original data are selected based on the quadrant search technique. The default setting is calculated as a percentage of the total extent of the map area and is appropriate for most data. The File name box enables you to enter a new file name.
Kriging Interpolation Decay Curves used by IDW interpolation. The disadvantage of IDW interpolation is that it treats all points that fall within the search radius the same way. For example, if an exponent of 1 is specified, a linear distance decay function is used to determine the weights for all points that lie within the search radius. This same function is used for all points regardless of their geographic orientation to the node (north, south, etc.) unless a sectored search is implemented.
Chapter 3: Creating Grids Using Interpolation Understanding Kriging Techniques Vertical Mapper provides three variations of kriging interpolation that you can apply in two forms, although they all operate in a similar way. The three methods are ordinary kriging, simple kriging, and universal kriging, and all three of these techniques can be applied in one of two forms: punctual or block.
Using the Kriging Interpolation Technique If you choose all the system defaults, the kriging type will be ordinary, the experimental semivariogram will be calculated, a model will be automatically fitted to the data, and kriging interpolation will be performed. However, experienced users will always spend some time fitting a model to the semivariogram. For more information about generating and interpreting a semivariogram, see Semivariogram Analysis on page 156.
Chapter 3: Creating Grids Using Interpolation Exploring the Kriging: Interpolation Dialog Box The Kriging Interpolation dialog box enables you to set a number of user-defined parameters. The Cell Size (lag distance) box enables you to set the cell size in real units. The grid dimensions (in cell units) vary inversely with cell size: the smaller the cell, the larger the grid file.
Using the Kriging Interpolation Technique The Extents button displays a summary of the geographic size and the z-value range of the original point database, the density of the points, and the data value units. Exploring the Kriging: Set Model Parameters Dialog Box When you click the Set button in the Kriging Interpolation dialog box, the Set Model Parameters dialog box opens. This dialog box provides additional settings for each kriging method.
Chapter 3: Creating Grids Using Interpolation Custom Point Estimation The Custom Point Estimation technique is similar to the IDW (Inverse Distance Weighting) technique, in which grid values are calculated based upon the points found within a predefined search radius. The main difference between these two techniques is that using the Custom Point Estimation technique, you can choose from six different calculations to perform on data points.
Custom Point Estimation • • The Count option counts the number of points found within the search area or within the number of selected points. The Median Value option returns the middle value of all the points within the search area or within the number of selected points. The Extents button displays a summary of the geographic size and the z-value range of the original point database, the density of the points, and the data value units.
Creating Grids Using Spatial Models This section describes all the basic commands associated with the creation of numeric grid files using modeling techniques. This chapter covers how to: • • create a Location Profiler model create a Trade Area Analysis model using a single site or multiple sites In this chapter: Creating Grids using Spatial Models . . . . . . . . . . . . . . . . . . . . . . .54 Understanding the Location Profiler Model. . . . . . . . . . . . . . . . . .
Understanding the Location Profiler Model Creating Grids using Spatial Models Modeling techniques create grids of derived values. The modeling wizard enables you to create grid files using two basic techniques. Location Profiler The Location Profiler creates a model where cell values are calculated as the average distance to all points found within a user-defined radius.
Chapter 4: Creating Grids Using Spatial Models Setting the Number of Points At each cell of the grid, the Location Profiler measures the distance to every point lying within the search area and calculates the average value. However, the pattern of geographic centres generated by the process will vary depending upon the number of points used for each grid cell calculation.
Understanding the Location Profiler Model This illustration shows the geographic profile of the same table of locations calculated using only one percent of the total points. The highlighted local concentrations of points give an effective visual representation of variations in point density across the map area.
Chapter 4: Creating Grids Using Spatial Models distance decay curves, as shown in the next figure, the slope is zero where x = 0 and gradually decreases, becoming more negative, until the inflection point is reached. At this point, the slope gradually increases, becoming more positive and returning to zero again as x approaches one. Shown here are six search radius distance decay curves supported by the Location Profiler.
Understanding the Location Profiler Model Shown here are six exclusion radius distance decay curves supported by the Location Profiler. Values along the x-axis represent a ratio obtained by dividing the distance between the grid point and data point by the exclusion radius. Curve 3 represents the most typical exclusion radius decay function that can be applied to the widest variety of modeling parameters. The y-axis indicates the decay factor associated with the data point.
Chapter 4: Creating Grids Using Spatial Models Creating a Location Profiler Model To create a Location Profiler Model: 1. From the Vertical Mapper menu, choose the Create Grid > Modeling command. 2. From the Select Modeling Method dialog box, choose the Location Profiler option. 3. Click Next. 4. In the Select Table and Column dialog box, click Load Table to add a table to the Table to Grid list if the table of points you want to use is not listed. 5.
Understanding the Location Profiler Model The Cell Size box enables you to define the cell size in the native coordinate system units of the map. The grid dimension (in cell units) varies inversely with cell size: the smaller the cell, the larger the grid file. The value you choose should be a compromise between the degree of resolution required for analysis, the processing time, and file size.
Chapter 4: Creating Grids Using Spatial Models The Decay Curves check box enables you to control the application of decay functions to the weighting values attached to each point location. If you don’t choose a weighting column in the Select Table and Column dialog box, the decay curves Settings button is disabled. If a weighting column is chosen in the dialog box, you can choose to disable the decay functions by clearing the Decay Curves check box.
Understanding the Location Profiler Model The Decay Approaching Search Radius list enables you to choose one of the supported curves from the list for the calculation. Each decay function defines a smooth curve with a negative slope that always starts at coordinate (0, 1) with a slope of zero and always ends at coordinate (1, 0) with a slope of zero.
Chapter 4: Creating Grids Using Spatial Models Understanding the Trade Area Analysis Model The Trade Area Analysis models enable you to generate trade areas around stores or other services based on the probability of an individual patronizing a particular location. It is possible to identify market islands in a network of competing stores using criteria such as the attractiveness of a store and the distance one must travel to get to the store.
Understanding the Trade Area Analysis Model This map displays the probability that a consumer will patronize Store A. The influence of all stores is taken into account in this model so that the locations of stores surrounding Store A influence the shape of the contours. Patronage probability decreases as the distance from the store increases. This map displays the maximum probability at every potential customer location that a consumer will patronize any one store when presented with all stores.
Chapter 4: Creating Grids Using Spatial Models Where: α = attractiveness coefficient estimated from empirical observations β = distance decay coefficient estimated from empirical observations This formula ensures that all the probabilities are between zero and one and sum to one when considering all the shopping destinations. The α and β coefficients allow you to account for nonlinear behaviour when modeling the effects of store attractiveness or distance.
Understanding the Trade Area Analysis Model 8. In the Data Description box, type an annotation (maximum 31 characters). This will be carried as a header in the grid file. 9. Enable the Ignore Records Containing Zero check box if you want to include only non-zero records. 10. Click the Next button and enter the required information in the dialog box. 11. Click the Finish button.
Chapter 4: Creating Grids Using Spatial Models The Display Radius box indicates the radius around each store or site within which probability values will be calculated. The default display radius is set to equal 50 percent of the maximum diagonal extent of the entire data set. The Units field displays the unit of horizontal distance measurement used in the model calculation (cell size and display radius).
Understanding the Trade Area Analysis Model For further readings on the topic of spatial interaction, refer to: Fotheringham, S. and O'Kelly, M., 1989: Spatial Interaction Models: Formulations and Applications. Kluwer Academic Publishers. Taylor, P. J., 1975: Distance Decay Models in Spatial Interactions. Concepts and Techniques in Modern geography. Norwich: Geo Books. 68 Vertical Mapper 3.
Creating Grids Using Other Methods Vertical Mapper comes with a number of data preparation and grid creation methods that enable you to build grid files from data files and tables of regions, polylines, or points.
Creating Grids Using Other Methods There are a number of ways you can create a grid other than by using the Interpolation or Modeling Wizards. Import grids from other formats You can import a grid from any supported format. For more information on importing grids, see Importing Grids on page 72. Create Point Density Grids Using the Point Density command from the Vertical Mapper, Create Grid menu, you can create a point density grid representing the density of events in an area.
Chapter 5: Creating Grids Using Other Methods the projection, z-unit type, and a number used as a special flag indicating null value grid cells. The default null value is -9999.0; however, if the data includes -9999.0 as a valid numeric value, a new null can be assigned to grid cells with no value. Example of a grid file illustrating the construction of an ASCII grid file.
Importing Grids GeoSoft is a proprietary binary grid format supported by the GeoSoft Inc. suite of industry-standard geochemical and geophysical data interpretation applications. The format is extremely flexible but does not support any projection information in the header. The Grid Import utility prompts you to enter a MapInfo Professional-recognized coordinate system class. The Grid Import utility supports only uncompressed GeoSoft grids.
Chapter 5: Creating Grids Using Other Methods Exploring the Grid Import Dialog Box The top section of the Grid Import dialog box lists all the files you have chosen as well as the associated file formats. The bottom section presents four tabs containing information about the highlighted grid. The Add and Remove buttons enable you to add or remove files from the Import Files list.
Creating Point Density Grids Creating Point Density Grids Calculate Point Density techniques are used to calculate the density of events in an area. Vertical Mapper supports two techniques for calculating point density: Square Area and Kernel Smoothing. These options are available from the Vertical Mapper, Create Grid, Point Density menu.
Chapter 5: Creating Grids Using Other Methods Exploring the Point Density Dialog Box The Cell Size box enables you to specify the cell size in the coordinate unit of the point file to be processed. The Search Area box enables you to specify the area around each cell to search for events. Units are specified in the coordinate units of the point file to be processed. Creating a Square Area Point Density Grid 1. From the Vertical Mapper menu, choose the Create Grid, Point Density, Square Area command. 2.
Creating Point Density Grids Exploring the Kernel Smoothing Dialog Box The Kernel Smoothing dialog box enables you to specify parameters specific to the Kernel Smoothing algorithm. The Cell Size box enables you to specify the cell size in the coordinate unit of the point file to be processed. The Solution Method section contains the following options: • • The In-Radius Search option enables you to define the search radius and the minimum number of points within the search radius.
Chapter 5: Creating Grids Using Other Methods This figure illustrates the weighting of each of the six kernel estimate options. This figure illustrates the results of using each type of weighting option; the choice affects the “pointiness” of the grid in high density areas. The Adaptive Exponent box enables you to specify the coefficient to adjust the kernel algorithm to the peculiarity of the data set. The value you specify must be between 0 and 1.
Region-to-Grid Conversion Region-to-Grid Conversion The Region-to-Grid conversion process involves extracting a text or numeric value from a column in the region table and assigning this value to all the grid cells that fall inside that region. If the assigned value taken from the MapInfo table is a text string, the process automatically creates a classified grid file. If the assigned value is numeric, it generates a numeric grid file.
Chapter 5: Creating Grids Using Other Methods Grid Buffering In a vector GIS applications such as MapInfo Professional, you can create regions around map objects at a predefined distance. You cannot, however, determine distances within a buffer region. For example, if a highway is buffered at a distance of one kilometre, you will not be able to determine the precise distances that fall within the buffered area (for example, 750 m or 300 m).
Grid Buffering If you choose the Use Maximum Distance setting, you must specify the maximum distance between locations where a circular buffer will appear. If the maximum distance setting is too great, as shown in the next figure, there will not be enough circular buffers to cover the length of the line. This graph shows the result when the Use Maximum Distance option is chosen and the distance setting is too big. By reducing the distance setting, the buffers will cover the whole line.
Chapter 5: Creating Grids Using Other Methods 6. In the Enter Data Description box, assign an annotation (maximum 31 characters) that will be carried as a header in the grid file. 7. In the Output Grid Name box, type a new file name or accept the default. 8. Click the Finish button. Exploring the Grid Buffer Dialog Boxes The Source Table list enables you to choose from tables available for processing. The Use Nodes Only option enables you to create points from the existing nodes along the polylines.
Preparing Data using Poly-to-Point The Enter Data Description box enables you to assign an annotation (maximum 31 characters) that will be carried as a header in the grid file. The Output Grid Name box enables you to assign a file name to the points file you create through the Grid Buffer technique. Preparing Data using Poly-to-Point Using Poly-to-Point, you can extract points from existing tables of lines, polylines, or regions to prepare data for creating grids. 1.
Chapter 5: Creating Grids Using Other Methods The Extract From section enables you to choose any or all of the Include Existing Points, Lines, Polylines, and Regions options to determine the type of objects in the table from which points are to be extracted. The Distance Between Points section includes the following options: • • The Use Nodes Only option enables you to specify that only the nodes are included in the calculation.
Import Raster Data as Vertical Mapper Grid . Note This dialog will only be displayed when we have multiple raster tab files open. Even if the raster file is open in multipe mapper windows there will be a single entry in the Select Raster dialog. Raster files which are open but are not associated with any mapper window will still be displayed in the dialog. Raster files having greater than 32000 pixels will not be displayed. • • • • 84 Supported Raster Data formats: Bitmap (*.bmp), JPEG (*.jpg), GIF (*.
Chapter 5: Creating Grids Using Other Methods 3. Once the raster file is decided, the Color to Value Mapping dialog will be displayed: Using this dialog you can assign Z-values to colors used in the raster image. You can use the following options to get the colors and assign z-values: • User Guide Click the button and then click on the snapshot of the image in the dialog.
Import Raster Data as Vertical Mapper Grid Grid control. • Click the button to stop selecting color. The caption of the button changes back to Start Pick Colors. • Click the button to generate colors from the image and add into the Grid control. Using the slider bar or edit box, you can provide maximum number of colors for generating optimum colors from the image. The total number of colors generated can be less than or equal to the Max No of Colors.
Chapter 5: Creating Grids Using Other Methods Assign Same Value dialog box accepts the value you want to assign to all checked colors. The default value is the value of the last selected Color (row). If no row is selected, the first non-null value from the checked color list is taken. If you want the NULL value to be assigned to all checked colors, it can be left blank. For every color, which is left without being assigned any value in the Grid Control, will be assumed as null.
Import Raster Data as Vertical Mapper Grid 88 Vertical Mapper 3.
Working with Grids Gridding is the basic mapping technique used in Vertical Mapper. The Grid Manager is the central dialog box from which you can open, sort, view, and manipulate grids. Vertical Mapper also includes several tools that enable you to extract information from grids, create legends for grids, display graphs relating to grid information, and create contour grids.
Working with the Vertical Mapper Toolbar The Vertical Mapper toolbar provides you with easy access to a number of tools. Using these tools, you can show/hide the Grid Manager, get information about various grids, and conduct a variety of grid analyses. If the Vertical Mapper toolbar is not visible, you can display it using the Options > Toolbars command. Toolbar button Functionality The Show/Hide Grid Manager button enables you to show or hide the Grid Manager.
Chapter 6: Working with Grids Working with the Grid Manager The Grid Manager enables you to obtain information about grid files, access the Grid Colour tool or the Dictionary Editor, run the 3D Viewer, create a 3D drape file, create region and polyline contours, and analyze or modify your grid files. • On the Vertical Mapper Project toolbar, click the Show Grid Manager button . Note You can also open the Grid Manager by choosing the Show Grid Manager command from the Vertical Mapper menu.
Working with the Grid Manager Grid Manager Options Description The Grid Colour Tool button enables you to access the Grid Colour Tool for numeric grids (for example, elevation .grd files) and the Dictionary Editor for classified grids (for example, clutter .grc files). The Grid View button enables you to make 3D drape files or to run the 3D Viewer. For more information, see Launching GridView on page 190. The Contour Grid button enables you to generate Region and Polyline contours for numeric grids.
Chapter 6: Working with Grids The Info tab summarizes the spatial characteristics of the selected grid including cell size, geographic unit of measure, grid dimension (in cells), file size, x and y extent of the grid, light source settings that define the relief shading of the grid (if applicable), and the name of the MapInfo Professional coordinate system to which the grid is referenced. Light source information does not apply to classified grids.
Working with the Grid Manager • • • • point inspection line inspection grid info line info The Meta Data tab provides access to historical information relating to the creation of the grid and is carried as a header string within the grid file.
Chapter 6: Working with Grids Legend for a classified grid. The Histogram tab displays a histogram of the grid data in a graph window. The histogram provides you with a visual display of the distribution of your data so that you can make better decisions for grid display and grid analysis operations. This window can also display classified grid data by class name, class count, percentage, and area. You can customize the display of the histogram by rightclicking on the histogram.
Using the Grid Info Tool Using the Grid Info Tool The Grid Info tool enables you to query and return grid values from selected locations in the grid file and view the results in a Grid Info dialog box. If more than one grid is open and active, values will be returned from each one. Only grid information from those grids that are active in the Grid Manager and are in the same geographic location as the point being inspected are displayed.
Chapter 6: Working with Grids Every capture session is entered into the vmCapture table and, therefore, you cannot make any changes using the Grid Manager during a session without saving the current vmCapture table. Changes include adding or removing other grid files or making existing ones active or inactive. Vertical Mapper always prompts you to save the current vmCapture table to another name.
Using the Line Info Tool Using the Line Info Tool The Line Info tool displays a statistical summary of the data along a selected line. The values displayed are for the grid highlighted in the Grid Manager. To display information for a large number of lines contained in the same table, use the Line inspection tool. For more information about line inspection, see The Line Inspection Function on page 130. 1. On the Vertical Mapper toolbar, click the Line Info button . 2. Click on a line in the Map window.
Chapter 6: Working with Grids Any numeric grid file generated in Vertical Mapper, using interpolation or modeling, is automatically assigned a default colour palette that is applied when the file is first opened. Colour is assigned to a numeric grid file according to ranges of grid values. Assume that a grid consists of values from zero to 100. Discrete colour gradients are then assigned by range according to defined inflection points.
Using Colour in Grids . 1. In the Grid Manager, choose a numeric grid (.grd). 2. Click the Colour button 3. Do any of the following: • • • • • • • • 100 . To add a colour inflection point, double-click the colour slider bar. To delete a colour inflection point, click a colour inflection point to highlight it and press the Delete key. To define a new colour for the inflection point, double-click on a colour inflection point.
Chapter 6: Working with Grids 4. In the Colour Profile section, do one of the following: • Click the Save button to save colour settings as a text file with a .vcp extension. • • Click the Load button to load a .vcp file. Click the Add button to add the current profile to the registry. • Click the Remove button to remove the selected profile from the registry. 5.
Using the Dictionary Editor for Classified Grids The Contrast box enables you to determine the difference between the lightest and darkest tones in an image. Increasing the contrast setting will make the brighter areas brighter and the darker areas darker. Both are measured on a scale of one to 255, and the default values presented in the dialog box are considered appropriate for most renderings. The Brightness box enables you to set a measure of both the colour intensity and overall greyness of an image.
Chapter 6: Working with Grids The New Group button enables you to add a new group to the dictionary. You can also access this command by right-clicking and choosing the New Group command from the shortcut menu. The Remove Group button enables you to delete a group from the dictionary. You can also access this by right-clicking and choosing the Remove Group command from the shortcut menu.
Displaying Legends The Range tab displays and allows editing of the values to be plotted on a legend bar. The values and percentiles that appear are those that you have defined in the Grid Colour Tool as the colour inflection points. For numeric grids the values and percentiles that appear in the top portion of the dialog box represent the colour inflection points currently used. It is these values that will be used by default. For classified grids this area displays only the different class names.
Chapter 6: Working with Grids The following options are available on the Text tab: • • • In the Titles section, you can enter a Main Title and, if desired, a Subtitle that will be positioned immediately below the main title. Using the Other box, you can also enter another title which is positioned at the bottom of vertical legends and at the lower left base of a horizontal legend bar. You can choose the desired font for each of the three titles by clicking the Text Style button to the right.
Displaying Legends The following options are available on the Format tab: You can use the buttons in the Tick Line Style section of the dialog box to modify the line style and colour of the Value, Percentile, or Scale tick lines. The Length of each set of tick lines may also be set independently. These commands are not available for classified grids. In the Frames section, you can enable one or both of the following options: The Legend check box draws a box around the entire legend.
Chapter 6: Working with Grids Once all the settings have been made to the colour legend, a file name must be chosen before selecting OK to continue. The on-screen grid file display is immediately updated. If a legend option was chosen, this file must also be saved as a .TAB before being displayed in a different Map Window.
Customizing a Graph The Y-axes tab contains settings that control how the labels for each graph in the Graph window are presented. The window to the left of the dialog box displays the number of different graphs that appear in the Graph window. The numbering convention represents the number of graphs that appear in the Graph window starting from the top of the window. • • • The Title box enables you to change the title of the y-axis for the selected graph.
Chapter 6: Working with Grids • The Point Style list box displays all the point styles for graph types that have a symbol component. When you click the coloured button near the bottom of the dialog box, the Colour dialog box opens, enabling you to change the plot colour of the chosen grid. The Colours tab contains settings that control the colours of the different components of the Graph window.
Customizing a Graph To export a graph: 1. Position the cursor over a grid histogram, a cross section graph, or a point-to-point solution graph. 2. Right-click, choose the Export command, and choose one of the three Export options: Text File, Bitmap & Tab, or Windows MetaFile. 3. In the Save As dialog box, navigate to the folder where you want to save the file and type the file name. 4. Click the Save button.
Chapter 6: Working with Grids Hiding or Showing the Legend • Position the cursor over a grid histogram, a cross section graph, or a point-to-point solution graph, right-click and choose the Hide Legend or Show Legend command. Smoothing a Grid The Vertical Mapper Smoothing feature reduces the variability in a numeric grid by averaging cell values contained in a specific area. In general there are two categories of filters.
Smoothing a Grid A default output table file name will be provided in the Smoothed Grid Table field based on the name of the selected input grid (“_Smooth” suffix is added). You may change this default file name or click the Browse button to select an existing TAB file to overwrite with the new smoothed data. You may want to use the default settings until you are comfortable with the way this utility works. Use the Smoothing Window Size field to control the level of smoothness of the grid.
Chapter 6: Working with Grids 1 + 2 + 1 + 4 + (5.6) + 3 + 7 + 0 + 9 --------------------------------------------8+6 Check the Fill Null Cells check box to have the Smoother compute the average for grid cells that contain no data. You can clear this check box to ignore cells that do not contain data (though this may retain some ‘noise’ in your output contour data). Consider the example above with the exception of a null central cell value (‘V’, meaning ‘void’ or ‘no data’): 1 + 2 + 1 + 4 + (V.
Contouring with Grids Creating Polyline and Region Contours A standard contour line map can be generated from within Vertical Mapper using a process that threads polylines through an existing grid file. You can define a number of settings including the range of grid values to be contoured, the contour interval, and the colour and style of individual contour lines. These settings can be saved in a configuration file and applied to other grid files.
Chapter 6: Working with Grids 6. To save contour profile settings, click the Save As button. Profiles are saved as text files with a .pfc extension. Note The default setting in the Minimum box is the lowest value encountered in the grid file and may need to be changed for the contouring process. If you want to maintain consistency in contour intervals throughout a series of grid files, save the settings for the contour plot in a profile.
Contouring with Grids 116 Vertical Mapper 3.
Using Grids for Spatial Analysis The power of Vertical Mapper lies in the ability it gives you to use grids in complex spatial analysis. This section describes how to: • • • • • • • use the Grid Calculator create grid queries use the Point-to-Point Visibility function use the Viewshed function create slope and aspect grids create cross sections use the Point, Line, and Region Inspection functions In this chapter: Using Grids for Spatial Analysis. . . . . . . . . . . . . . . . . . . .
Using the Grid Calculator Using Grids for Spatial Analysis Vertical Mapper gives you the ability to create grids based on geographic information and apply this information to complex spatial analysis problems. For example, annual variations in air temperature can be calculated by subtracting one year’s measurements from those of another year. In Vertical Mapper, this arithmetic calculation is performed using the Grid Calculator.
Chapter 7: Using Grids for Spatial Analysis 7. In the Grid Calculator – Save dialog box, do the following: • In the Save the New Grid As box, type a file name for the new derived grid built from the math expression. • In the Description box, type a description of the new grid. • From the Z-Unit Type list, choose a z-unit type. If the unit type is user-defined, you can type a custom entry in the Enter User Defined Type box. 8. Click the OK button.
Using the Grid Calculator • • • The Value box enables you to enter a numeric value. The Type box displays the type of the variable; this is always NUM for new variables because only numeric variables can be used in expressions with numeric grids. The Alias box enables you to enter a character string that represents a substitute name for the entry in the Expression box. The Modify button opens the Variable Editor to enable you to edit the Alias of a list entry.
Chapter 7: Using Grids for Spatial Analysis Button Usage () Explanation Adds a left or right bracket Sqr Sqr(X) Square of X Sin Sin(X) Sine of X ArcSin ArcSin(X) Arcsine of X Use the Inv button to toggle between Sin and ArcSin.
Understanding Grid Queries Understanding Grid Queries You can use grid queries to build new grids from existing grids where the new grid values are derived according to whether specific queries imposed on the existing grid files have been met. For example, you can create an expression that will query a set of grid files and identify all coincident cells that meet these conditions: cells in Grid1 are >1049m AND cells in Grid2 are <=$250,754.
Chapter 7: Using Grids for Spatial Analysis Creating and Editing Conditional Queries The first step in creating a conditional query involves building a query expression from a selection of open grid files as a series of individual conditional clauses. The second step involves the assignment of values to the new grid, cell by cell, according to whether the query conditions are met (true) or not met (false) for each set of overlying cells.
Understanding Grid Queries The Operator list enables you to choose the appropriate operator for the query. The choices available vary depending upon whether the grid is numeric or character-based. In both cases, you can also choose “Any Value” or “Null Value”. The Value box enables you to enter a user-defined value. If the query is being created for a character-based grid, this box becomes a list because there are only a specific number of unique classes in any .grc file.
Chapter 7: Using Grids for Spatial Analysis The Cell Size box enables you to set any user-defined value but, as with any grid creation technique, cell size is inversely proportional to file size. This value defaults to the smallest cell size found in all of the open grids. The X-min, X-max and Y-min, Y-max boxes enable you to set any user-defined values. They default to the maximum extent covered by the grids used in the query expression.
Understanding Grid Queries The Output Format section enables you to choose the format of the output grid. You can choose a numeric grid file where each cell in the grid is assigned a numeric value or a classified grid file where each cell in the grid is assigned a character-based value. The When True section contains the following options: • • • The Use Value option assigns a specific value to each TRUE cell in the new grid that is userdefined and entered into the edit box.
Chapter 7: Using Grids for Spatial Analysis Understanding Slope and Aspect As it applies to grid geometry, slope is a measurement of the “steepness” of a grid cell in threedimensional space and is therefore most applicable to elevation surfaces. In Vertical Mapper, slope is calculated by averaging the slopes of the eight triangle faces that are formed from the surrounding nodes.
Understanding Slope and Aspect Exploring the Slope and Aspect Dialog Box You can use this dialog box to create a slope grid, an aspect grid, or both. The Grid list Enables you to choose the list for the analysis. The Create Slope Grid check box Enables you to create a slope grid. The Slope Parameters section This section is available only when you enable the Create Slope Grid check box: The Description box Enables you to enter a description for the slope grid.
Chapter 7: Using Grids for Spatial Analysis Creating a Cross Section You can create a query of grid values along a line or polyline constructed in a Map window using the Cross Section command. The values are displayed as an x, y line plot in a graph window. 1. On the Vertical Mapper toolbar, click the Cross Section button. 2. Draw the line of the cross section directly on the grid image, then double-click to end the line.
The Point Inspection Function The Horizontal Distance is the “crow fly” distance from the beginning point of the transect line to the indicated sample. The True Distance (Elevation.grd) is the ground or “overland” distance from the beginning point of the transect line to the indicated sample Note Whenever a cross section line crosses a null area, the true distance is reset to zero.
Chapter 7: Using Grids for Spatial Analysis This figure shows a MapInfo Professional SQL Query. Using the Line Inspection Function The Line Inspection function updates a table of polyline data with values taken from a grid file. The process inspects the samples between the beginning and end of the line, calculates the selected number of statistical parameters, and writes the values to new columns in the data table. 1.
The Region Inspection Function Each statistical parameter calculated for each open and active grid is written into a separate column of the region table and given a default column name consisting of both the parameter name and the grid file name. Note The number of samples taken along the line is determined by the Cross Section: No of Samples parameter in the Preferences settings. The default is 100.
Chapter 7: Using Grids for Spatial Analysis The Point-to-Point Visibility Function Intervisibility and viewpoint analysis uses elevation grid files to determine visual exposure relationships within a map area. Intervisibility is defined as the ability to see in a direct line of sight from one position on the earth’s surface to another, considering the intervening terrain. The Point-to-Point Visibility function enables you to specify a line across an elevation grid file (i.e.
The Point-to-Point Visibility Function The Grid list enables you to select the appropriate open grid file for analysis if such selection is not made in the Grid Manager. The Viewing Parameters section enables you to control the intervisibility calculation for each endpoint of the line. You can enter x- and y-coordinates as well as an offset height above the surface at both the Looking From and the Looking To viewpoint positions.
Chapter 7: Using Grids for Spatial Analysis • • • The Surface Elevation value is the elevation value found at the sampled location. All values are based on the “no earth curvature” model, and they are not displayed in the graph window. The Relative Viewable Elevation value is the elevation at the sampled location that can be seen from the viewing point. All values are based on the selected earth curvature model and are represented by the green line in the graph window.
The Viewshed Function The relative elevation indicated by the red line represents the surface topography along the line of sight, while the relative viewable elevation (green) represents the line of visibility. Where the two lines are coincident, that section of topography is visible from the “From” point. Immediately below the graph is a written description of the relationship between the “From” and “To” points of the line of sight path.
Chapter 7: Using Grids for Spatial Analysis Using the Viewshed Function The Viewshed function is appropriate only for use on a grid file that has a unit of elevation (feet or metres) as its z-value. 1. On the Vertical Mapper toolbar, click the Viewpoint Pick button. 2. Using the left mouse button, choose a point in the Map window of the open elevation grid file that represents the point of origin for the viewshed calculation. 3.
The Viewshed Function • The Simple Calculation option enables you to create a classified grid file and assigns either the category “Visible” or “Invisible” to each cell depending upon whether it is visible or invisible from the viewpoint. If multiple viewpoints are selected, each grid cell of the new classified grid is assigned a category “NumVisible_n”, where “n” is the number of viewpoints visible from that cell; the values will range from zero to the total number of viewpoints used in the calculation.
Using the Grid Tools The grid tools are a series of utilities that work with grid files to increase the flexibility and workability of grids in the MapInfo Professional desktop mapping environment. In this chapter: Using the Grid Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .140 Using the Alter Meta Data Tool . . . . . . . . . . . . . . . . . . . . . . . . . . .140 Exporting Grids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Using the Alter Meta Data Tool Using the Grid Tools Vertical Mapper provides a selection of grid tools that enable you to export grids to other mapping formats, reproject grids from one coordinate system into any other MapInfo Professional-supported system, reclassify grid values to predefined values or classes, splice adjacent or coincident grids into a seamless map coverage, trim a grid to fit into a custom map boundary, and change the resolution of a grid to reduce the file size or to make it more compa
Chapter 8: Using the Grid Tools The Grid list enables you to select the appropriate open grid file to process if it is not chosen in the Grid Manager. The top portion of the dialog box contains a list displaying the current meta data for the grid. The text colour, either black or red, indicates whether entries are editable (black) or not editable (red). You cannot edit entries containing Vertical Mapper or MapInfo Professional keys.
Using the Export Grid Tool Using the Export Grid Tool 1. In the Grid Manager, click the Tools button and choose the Export command. 2. In the Export Grid dialog box, from the Grid list, choose the grid you want to export. 3. In the Export Type section, choose the export type. 4. If you are exporting to either of the DXF mesh formats or the VRML format, specify a null value in the Null Value box. This differentiates a “real” zero value from a null value in the export file. 5.
Chapter 8: Using the Grid Tools Using the Classified Grid Filter Using the Classified Grid Filter, you can reclass small isolated areas of cells. This has the effect of smoothing the grid. The classes are processed individually, beginning with the class containing the smallest number of grid cells. 1. In the Grid Manager, click the Tools button and choose the Classified Grid Filter command. 2. In the Classified Grid Filter dialog box, from the Grid list, choose the grid to be filtered. 3.
Reclassing Numeric Grids 4. Do one of the following: • Click the Insert button to insert a row in the Reclass table. • Click the Delete button to delete the selected row in the Reclass table. • Click the Interval button to specify the minimum and maximum for the range or interval. 5. Click the Save button to save the reclass profile to a .pfr file. 6. In the File name box, type a new file name or accept the default. 7. Click the OK button.
Chapter 8: Using the Grid Tools • The Method section enables you to choose which method to use to create the range. There are two options: Interval in the Value box, type the range of values that each class will encompass. The default setting is based on dividing the range between the minimum and maximum values into 10 classes Number in the Value box, type the number of classes that will be created based upon the Minimum, Maximum and Interval settings. The default is 10 classes.
Reclassing Classified Grids 4. To save the reclass profile to a .pfr file, click the Save button. 5. In the File name box, type a new file name or accept the default. 6. Click the OK button. 7. If you select to Numeric (*.grd), the Classified to Numeric Grid Converter dialog opens. In this dialog box, you can do the following: • • • All the classes that are present in the classified grid are listed. Default values are already assigned to each of them.
Chapter 8: Using the Grid Tools The Assigned Class(es) section lists classes that you have assigned. The Add button enables you to create new classes or groups and add them to the new grid to be reclassified. The Delete button enables you to remove any highlighted class or group from the new grid to be reclassified. The Verify button enables you to verify that no class or group is left unassigned. If any classes from the original grid are left unassigned, a dialog box opens listing those classes.
Using the Reproject Tool The Table will display the list of open tables. The Class Column will display the list of columns in the selected table which are of type character. The Value Column will display list of columns in the selected table which are of type numeric. Clicking on OK in this dialog will update the values in the Class Value column in the Classified to Numeric Grid converter dialog.
Chapter 8: Using the Grid Tools The Reproject tool enables you to perform a preliminary transformation test using the chosen projection. The test calculation involves projecting the bottom left and upper right points of the original grid into a new projection and then back again. The difference in the position between the original and transformed sets of locations is measured and compared to the original. Most coordinate transformations return error values less than 0.0000001%.
Resizing a Grid The Suggested Range box displays the suggested range of cell sizes appropriate for the projection. The File Size and Dimension boxes display the file size and dimensions of the grid in the new projection. The File Name box enables you to specify the file name. Resizing a Grid You can adjust the resolution of a grid. For example, you might need to reduce the size and complexity of grid files in preparation for contour threading.
Chapter 8: Using the Grid Tools Splicing Grids Together The Grid Splicer tool combines one or more grids into a single grid file. There are two distinct ways in which grids can be spliced together: merging and stamping. The difference lies in how each of these procedures handles the values of grid cells that overlap other grid cells. In merging, two or more grids are combined, and where they overlap a mathematical calculation is performed to determine the new grid value. Only numeric grids can be merged.
Splicing Grids Together You can update specific areas of an existing grid. This is best done by creating polygonal regions around the areas to be updated, i.e., the new subdivision or building footprint. Attach the appropriate information to these regions, for example, “urban” for the subdivision and the building heights to the footprint. Use the Region to Grid command to convert these regions to a grid. Be sure that the projection and the grid units are the same.
Chapter 8: Using the Grid Tools The Spliceable Grids list displays all grid files open in the Grid Manager that can be successfully spliced with the reference grid. This list is restricted to those grids that are the same grid type (numeric or classified), the same projection, and the same z-units as the reference grid. There are no restrictions placed upon the cell size of the input grids. The resulting grid will always have the same cell size as the reference grid.
Trimming a Grid choose it and use the Convert to Regions command from the Objects menu in MapInfo Professional. 2. Choose the region that represents the trimming edge. 3. In the Grid Manager, click the Tools button and choose the Trimmer command. 4. In the Save Trimmed Grid As dialog box, type a new file name for the trimmed grid in the File name box. Once the .grd file is created, it appears in a Map window with a default colour palette applied. You can change the colour range assigned to the grid file.
Data Analysis Surface Analysis in Vertical Mapper provides data analysis tools that make your analysis tasks easier. In this chapter: Semivariogram Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .156 Spatial Correlation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .163 Polygon Overlay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .167 Predictive Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Semivariogram Analysis Grid creation is a valuable way to visualize how data, represented by points, changes through space. The change in value between known locations can easily be shown. However, one thing a grid does not show very well is how values change in any given direction and how strong that directional trend is. This can be particularly valuable to know in some fields.
Chapter 9: Data Analysis Put simply, every point is compared to every other point to determine which points are approximately the first lag distance apart. When points this distance apart are found, the variance between their values and their geographical orientation is determined. Once the first lag distance has been analyzed the process is repeated using the second lag distance and then the third, and so on until all distance possibilities are exhausted.
An example of a directional semivariogram. Notice the two experimental semivariograms, one representing points oriented north and south of each other, and the other representing points oriented east and west of each other. When two or more directions are analyzed, an experimental semivariogram will be generated for each direction. In the previous figure, two directions are being investigated and therefore two experimental semivariograms are plotted.
Chapter 9: Data Analysis A two-directional semivariance search. In the previous figure, two directions are analyzed, represented by the dark and light grey pie shapes. It is important to note that although the diagram shows four pies, variance analysis is always performed in opposing directions. When more than one direction is set, the angle to which these sectors will be oriented must be specified. In the above diagram, the angles are zero degrees (Sector A) and 80 degrees (Sector B).
The sill is a variance value that the model curve ideally approaches but does not cross. The range is the distance value at which the variogram model determines where the sill begins. Anisotropic Modeling It is quite natural for the behaviour of a data set to vary differently in one direction as compared to another. For example, a steeply sloping hill will typically vary in two directions.
Chapter 9: Data Analysis Exploring the Variogram Dialog Box This dialog box is available from the Vertical Mapper, Data Analysis, Semi-variogram Analysis command and from the Variogram Builder button in the Kriging Interpolation dialog box. The top portion of the dialog box displays the experimental semivariogram of the data along with settings that control the directional calculations. The bottom portion of the dialog box contains settings that tune the model.
The Apply button enables you to recalculate and refresh the semivariogram using new settings. The graph in the dialog box is a semivariogram of the data and plots variance between sample pairs on the y-axis and the lag distances for the calculated variances on the x-axis. The experimental semivariograms that appear in the graph are updated only when you click the Apply button. The model curves will automatically update when changes that affect the models have been made to the dialog box.
Chapter 9: Data Analysis • Anisotropy view diagram shows the directional trends in the data. A wide ellipse indicates that there is a greater degree of correlation of the variances between sample pairs in that direction. Conversely, a narrow ellipse indicates that there is a smaller degree of correlation. The angle setting for each model determines the degree of rotation for each ellipse.
Spatial Correlation Creating a Correlation Matrix 1. From the Vertical Mapper menu, choose the Data Analysis > Spatial Correlation > Correlation Matrix command. 2. In the Correlation Analysis dialog box, clear any open grids you do not want to include in the correlation matrix. 3. In the File Name box, type a new file name or accept the default. 4. Click the OK button. A Browser opens displaying the correlation matrix. This figure shows part of the correlation matrix for a large number of grids.
Chapter 9: Data Analysis In this example, the specified group similarity was 0.7. The members in Group #1 and Group #2 have a correlation coefficient among themselves of 0.7 or higher. Significance Analysis Significance analysis enables you to determine quickly which grids are the most significant by displaying the names of grids that have a weight factor of at least the value you specify. Significance analysis is particularly useful when you have large numbers of grids.
Spatial Correlation This Browser shows the results of a significance analysis where the specified weight was 8.5. Principal Components Analysis Principal component analysis is an effective and popular method of multidimensional statistical analysis. It provides a method both of reducing the number of variables to be analyzed by eliminating redundancy and of detecting structure in the relationship between variables.
Chapter 9: Data Analysis Exploring the Principal Components Dialog Box The Select Grids to Analyze list displays all open grids. These are enabled by default. You can clear any you do not want to include in the analysis. The Maximum Number box enables you to specify the maximum number of principal components you want to find. The Cumulative Variance box enables you to specify the minimum cumulative variance you want the analysis to achieve.
Polygon Overlay The second step is to calculate the value for each cell in the new grid. The calculation involves knowing how many cells each region contains, and then dividing the region’s value by that number. In this way, the region’s total value is spread among the grid cells contained inside it. A grid cell is considered to be inside the polygon when the centre of the grid cell (the grid node) is located within the polygon.
Chapter 9: Data Analysis Some polygons may be too small for a grid node to be located inside. In this instance the polygons data is attributed to the closest node. This would be the node to the upper right of the selected region in the above diagram. This problem can be minimized by decreasing the cell size used in the analysis. You can determine what is a reasonable cell size by clicking the Advise button in the Polygon Overlay dialog box.
Predictive Analysis In the Column section, you can choose either of the following options: Existing Column enables you to choose an existing column in the target table that will be updated with data from the source table. New Column enables you to specify the name of a new column that will be added to the target table and will contain the data from the source table. The Data Table list displays all the valid tables open in MapInfo Professional. The highlighted table becomes the source data table.
Chapter 9: Data Analysis regions representing a high crime rate “1,” and the regions representing a low crime rate “2.” Any region assigned a value of 0 in this column will not be included in the analysis. This table is the “teaching table.” The colours that you assign to the regions will be used for displaying the results. 3. From the Vertical Mapper menu, choose the Data Analysis > Predictive Analysis command. 4.
Predictive Analysis The Class Column list enables you to choose the column in the table that contains the class of the region; the class must be an integer. The File Name box enables you to enter a new file name. 172 Vertical Mapper 3.
Aggregating Data There are two methods of data aggregation: simple point aggregation and point aggregation with statistics. This section discusses: • • • when to aggregate data how to aggregate data using simple point aggregation how to aggregate data using point aggregation with statistics In this chapter: Aggregating Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .174 When to Aggregate Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
When to Aggregate Data Aggregating Data Data aggregation is a mathematical process for reducing the number of points in a point file. Different methods are available to process a point file, but the underlying goal is to spatially group and statistically merge points that are in close proximity. This not only results in fewer points but also creates a more uniform distribution of points and point values. Vertical Mapper provides two options for data aggregation.
Chapter 10: Aggregating Data Simple Point Aggregation Simple point aggregation is useful for quickly grouping points that are virtually coincident or that are separated by relatively small gaps. For example, when soil samples are collected, you may need to take several samples at each sample site. When creating a surface of this data, you may want to average all of the samples taken at each site before proceeding with the surface creation.
Simple Point Aggregation Performing Simple Point Aggregation You can use simple point aggregation to quickly group points that are virtually coincident or that are separated by relatively small gaps. 1. From the Vertical Mapper menu, choose the Data Aggregation > Simple Point Aggregation command. 2. From the Select Table to Aggregate list in the Select Table and Column dialog box, choose a point table. 3. From the Select Column list, choose a column of data to transfer to the aggregated file. 4.
Chapter 10: Aggregating Data • • • Median Value: The median value is the middle value of all points within the “same point” distance of the aggregated coordinate. If there are an even number of points, the median value is the average of the two middle values. Average of Min & Max Values: This value is determined by averaging the minimum and maximum values of all points within the “same point” distance of the aggregated coordinate.
Point Aggregation with Statistics The calculated statistical information is retained in the Browser window of both the aggregated point file and the aggregation regions file as shown below. Exploring the Select Coincident Point Technique Dialog Box This dialog box is the same one that is used to set parameters for simple aggregation. There are two steps in statistical aggregation. The first step allows you to deal with virtually coincident points separately before you aggregate the points further.
Chapter 10: Aggregating Data performed regardless of whether the dialog box is greyed out. If you do not choose any of the settings in this dialog box, the default values will be used. A reminder will appear when this technique is chosen. Exploring the Select Aggregation Technique and Statistics Dialog Box The Select Aggregation Technique and Statistics dialog box enables you to set the aggregation technique and aggregate point attributes.
Point Aggregation with Statistics • • • Number of Points Aggregated: This value is the total number of points selected for aggregation. It does not include the points processed in the Coincident Point Handling step. Standard Deviation: This value is the degree of dispersion between the mean of the values for those points selected for aggregation. % Normalized Coeff. of Variation: The coefficient of variation is the standard deviation divided by the average expressed as a percentage (multiplied by 100).
Chapter 10: Aggregating Data new aggregated point. The process ends by performing the aggregation calculations on the selected points as specified in the Point Aggregation dialog box, and the results are attributed to the new aggregated point. Once the first point is processed, the procedure sweeps from left to right and top to bottom across the study area, selecting and aggregating unflagged points. It is important to note that not every data point will be aggregated on the first pass through the data set.
Point Aggregation with Statistics Original distribution of data points. The Cluster Density Aggregation technique is usually most effective for small to medium size data sets, because it makes better decisions during the aggregation process. It aggregates the more densely clustered points first within a reasonable processing time. However, it is not appropriate if you need to know the number of points aggregated or if there are coincident points in the data.
Chapter 10: Aggregating Data There are a total of 330 points in the sample data set shown in the previous figure. After using the cluster density aggregator, you can see that the data is clustered in about ten separate areas. The more randomly distributed points lying outside these clustered zones (circles) are also aggregated, but with significantly fewer points included. Although many circles overlap, the degree of overlap is significantly less than when the forward stepping method is used.
Building a Table of Standard Deviation Ellipses maximum dispersion in a point pattern is always at right angles to the axis of minimum dispersion. The length of the X axis is set to one standard deviation of the X values, and the length of the Y axis to one standard deviation of the Y values. An example of standard deviation ellipses. The ellipses are generated around the original data points, which are at the mean centres of the ellipses containing them.
Using Natural Neighbour Analysis Using the Natural Neighbours technique, you can analyze point data that needs to be mapped to discrete regions with constant values assigned to each point. This section describes how to perform natural neighbour analysis: • • • natural neighbours how to create regions from points how to calculate a region area In this chapter: Understanding Natural Neighbours . . . . . . . . . . . . . . . . . . . . . . .186 Creating Regions from Points (Voronoi) . . . . . . . . . .
Understanding Natural Neighbours While the strength of Vertical Mapper lies in the ability it gives you to create a continuous grid from non-continuous data points, not all types of data are best represented as a continuously varying surface. Some types of point data should be mapped as discrete regions within which the values assigned to each point are constant. Point data such as this is referred to as having a natural neighbour.
Chapter 11: Using Natural Neighbour Analysis The following section describes the two main procedures in Vertical MapperSurface Analysis that make use of natural neighbour relationships: building Voronoi diagrams from point tables and calculating point density. Creating Regions from Points (Voronoi) Using the Voronoi technique, you can generate a region around each individual data point. The resulting network of regions is often referred to as a Voronoi diagram.
Calculating the Region Area The Select Region From Map check box—enables you to use a pre-defined MapInfo region as the Voronoi boundary. The Set Region Style button—enables you to customize the fill and line style pattern of the Voronoi diagram. In this Voronoi diagram, the Hull Boundary Margin width setting is very small (1). Therefore polygons are effectively cut off at the outermost limit of the point file.
Creating 3D Views Using GridView GridView enables you to generate 3D renderings of one or more numeric grid files as well as adjust many settings such as the lighting, viewing angles, reflectance, and shading properties. Through the use of drape files, text, line work, colour-filled polygons, and raster imagery, you can render scenes in three dimensions. In addition, you can save any scene as a bitmap image with a corresponding MapInfo .tab file.
Launching GridView GridView can be accessed in three different ways. The most common way is through the Grid Manager. The highlighted grid in the Grid Manager will be the master grid in the resulting 3D scene. You can also access GridView by clicking the GridView button in the Point-to-Point Visibility dialog box, available from the Point-to-Point Visibility button on the Vertical Mapper toolbar.
Chapter 12: Creating 3D Views Using GridView The Set Viewing Mode section enables you to determine the location of the viewing position in geographic space. There are three ways in which this location can be defined and, depending on which mode is chosen, different settings will be available on the Viewing tab. The default is the From and To mode.
This diagram illustrates the To Your Location viewing mode. The Camera Angle box enables you to set the width of the view-scene in degrees. It allows you to control the field of view similar to using a wide-angle lens on a camera. Using a smaller angle will result in seeing less of the grid. The Center button enables you to restore all default viewing settings. The Looking From section defines the x-, y- and z- coordinates of the location that the viewer is looking from.
Chapter 12: Creating 3D Views Using GridView . In the From Your Location mode, the azimuth is the direction the viewer is looking toward in relation to the viewing location. • • In the To Your Location mode, the azimuth is the direction the viewer is looking toward in relation to the focus point. Inclination is the angle measured from the horizon to the line of sight at either the viewing location or the focus point, depending on the selected viewing mode.
The Surface and Lighting Tab The Surface and Lighting tab contains settings that affect the visual characteristics of the rendered scene. Properties in this dialog box will affect all the grids listed in the Grid Layer Control. The Lighting section enables you to choose lighting settings implemented in a GridView scene. Each type of lighting is generated from a different source and each is user-controlled.
Chapter 12: Creating 3D Views Using GridView Solid displays a continuous colour surface. Wireframe displays a wireframe mesh. The Shading section enables you to set the manner in which colours are applied to individual grid cells during the rendering process. There are two options: Smooth and Flat. • Smooth renders a colour gradient between each grid cell when rendering a scene. This can greatly improve the appearance of low-resolution grids (see the figure below on the left).
colour can be generally seen in three different locations: the grid base, the grid apron, and the inside holes within the grid area (see the next figure). When this setting is chosen, a standard Windows Colour dialog box opens. The areas affected by the Null Value Colour setting are easily identified. The Backdrop Colour button enables you to set the colour applied to the backdrop or background of the rendered scene. When this setting is chosen a standard Windows Colour dialog box appears.
Chapter 12: Creating 3D Views Using GridView The Grid section enables you to set the display characteristics of the highlighted grid file. • • • User Guide The Transparency slider bar enables you to set the degree of transparency the highlighted grid will have. With the slider bar set fully to the right, the grid will display normally. As the slider bar is moved to the left, the grid will begin to vanish into the background.
The Base section contains settings to control the display and size of the base of the grid. • The Show Base check box specifies whether the base will be displayed or not (see the next figuresa). This setting is typically used in conjunction with the Draw Underside check box. A rendered scene with Base • The Thickness box enables you to set the thickness of the base in the coordinate units of the master grid (see the next figures).
Chapter 12: Creating 3D Views Using GridView The Z Values section enables you to control the vertical exaggeration of the highlighted grid in the Grid Layer Control. • The Exaggeration box controls the degree of exaggeration of the z-value. This enables you to vertically stretch the rendered scene (see the next two figures).
• The Hide When Over Null Value check box controls the display of a drape where it is geographically coincident with null values on the grid that it is draped upon (see the next two figures). These areas are made invisible. This figure shows a drape file overlying a grid that has null values in the lake area. This figure shows how the Hide When Over Null Value setting behaves when checked.
Chapter 12: Creating 3D Views Using GridView The Cancel button enables you to close the dialog box without rendering the GridView scene. The Grid Extents button opens the Grid Extents dialog box which displays the x- and y- extents as well as a range of values of the highlighted grid file. The x- and y- values are expressed in the coordinate system units of the grid, and the z-value range is expressed in data units.
Working with Grid Layers Working with Grid Layers The Layer/Grid Height list in the Scene Properties dialog box displays the grids and drape files that are loaded into the memory of GridView. The master grid is the first grid loaded into the Layer/Grid Height list box. Any x- or y- location or distance setting is specified in the coordinate units of the master grid. In any single GridView session, only one grid can be used as the master grid.
Chapter 12: Creating 3D Views Using GridView The Open/Save Workspace command opens an existing workspace or saves the current rendered scene to a workspace. When you save a workspace, all the settings for recreating the rendered scene are saved to an ASCII text file with a .gvw extension. The Print/Print Set Up command controls how the rendered scene is printed and enables you to select an installed printer.
Making 3D Drape Files • • • Ensure proper registration in GridView; the grid file upon which the drape will be placed must be present as one of the layers in the current MapInfo Map window. This layer does not have to be visible. All of the MapInfo layers contained in the drape file must be in the current Map window and be coincident with the geographic extents of the grid being draped. Only those map entities that fall within the extents of the grid will be included in the drape.
Other Commands This section covers how to set preferences for grid file management and dialog box usage and how to exit from Vertical Mapper. In this chapter: Setting your Preferences. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .206 Exiting Vertical Mapper . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Setting your Preferences You can determine the default settings that control grid file management and dialog box usage in the Preferences dialog box. • From the Vertical Mapper menu, choose the Preferences command. Exploring the Preferences Dialog Box The Preferences dialog box enables you to assign a number of default settings. The Show for all open grids check box—enables you to show all grids in the Grid Info dialog box regardless of whether the grid file is active or inactive.
Chapter 13: Other Commands • The Add and Remove buttons enable you to add any number of profiles to or remove them from the list. In the absence of any preferred colour profile, the Vertical Mapper default gradient colour pattern is used. This profile cannot be edited. The Decimal Places box—enables you to set the number of decimal places of accuracy that will be visible when working with entered or returned values.
Index A Alter Meta Data tool 132 Analyzing data calculating point density 72 using gravity models 61 using natural neighbourhoods 73 using the Huff model 61–62, 64 using the trade area analysis model 61 Analyzing grids 19 using spatial analysis 108 ASCII classified grids 69 ASCII Grid 69 Aspect creating 117 B Bi-Weight kernel estimate 74 Block kriging 45, 48 Buffers creating 77–78 C Classified grids 17 adding colour 95 contouring 106 filtering 135 histogram 89 reclassing 137 Colour adding to grids 93, 95
exporting 102 maximizing 103 printing 103 setting the zoom for 103 Grid architecture 18 Grid Buffering 77 Grid buffering 78 Grid Calculator 19, 109 opening 108 Grid files description of 15 Grid Filter 135 Grid Import 71 Grid Info tool 90 Grid Manager description 84 Histogram tab 89 info tab 87 Legend tab 88 Meta Data tab 88 Z-units tab 87 Grid Query 19 derivative grid 112 Grid Tools Alter Meta Data 132 Classified Grid Filter 135 Grid Export 133 Grid Reclass tool 135 Grid Splicer 141, 143 Reproject tool 139–
number of zones 33 radius multiplier 34 zone orientation 33 K Kernel estimates Bi-Weight 74 Epanechnikov 74 Gaussian 74 Triangular 74 Tri-Weight 74 Unit 74 Kernel smoothing 73 Kriging interpolation dialogue 47 interpolation process 45 point aggregation 46 setting model parameters 48 suggested readings 50 Kriging Interpolation 23, 43 how it works 43 punctual or block 45 simple 45 variations 45 Kriging interpolation ordinary 45 universal 45 L Legends creating 97 hiding or showing 104 Line Info tool 92 Line
R U Reclass profiles 137 Reclassing classified grids 137 numeric grids 135 Rectangular interpolation 41 Region contours creating 104 Region Info tool 91 Region inspection 122 Region to Grid conversion 19, 76 Relief Shading 95 Relief shading 85 Reprojecting grids 139–140 Resizing grids 140 Resolution 18 UK Ordnance grids 70 Unit kernel estimate 74 Universal kriging 45 Upgrading, Vertical Mapper 10 USGS DEM grids 70 Using the Grid Colour Tool for numeric grids on page 11 13 S SDTS grids 70 Showing or hidi
