Beyond the Vector Data Model

Beyond The Vector Data Model Introduction • • • • • Collecting, Managing, and Analyzing Data The Raster World Adding Functionality with Spatial Analyst Managing Grid Themes Introduction to Lab 6 Vector Data Model (ArcView) Models boundaries of feature data Vector feature types include points, lines, and polygons Vector data formats include *.shp, *.shx, and *.dbf Files are easily moved and copied Demonstration #1 ArcView using vector data model (points = crime events, lines = streets, and polygons = public school parcels) Point, Polyline, Polygon Corresponding Files *.shp (required) Stores the feature geometry *.shx (required) Stores the index of the feature geometry *.dbf (required) Stores the attribute information features *.sbn and *.shx (optional) Stores the spatial index of features (Note: adding a shape that has a corresponding *.avl file) A quick look at functionality that comes with ArcView How to load and unload extensions Adding functionality to your ArcView session In the Project Window --- Help, Help Topics, Extensions, Spatial Analyst What is Spatial Analysis? Approach used to answer complex geographic questions by evaluating suitability, predicting and interpreting patterns. Spatial modeling involves analytical procedures to abstract and simplify complex systems. We will use geographic data to describe, simulate, or predict real-world problems or systems. There is more than one answer, and our role is to compare alternative solutions. ArcView's Spatial Analyst The software provides several tools to perform spatial queries using grids: overlay analysis, surface analysis like distance, proximity, density, slope, aspect, hillshade, viewshed, and contours. Vector Vs Raster Data Models There are two spatial models for storing geographic data - the vector data model and the raster data model. (Note: A surface can also be represented as a TIN - triangulated irregular network. TIN is a vector model that can represent continuous surfaces as a series of linked triangles. While Spatial Analyst does not support TIN datasets, ArcView 3D Analyst does.) VECTOR Data stored as (x, y) coordinates RASTER Data stored as cell values Defines boundaries No boundaries Feature shape is accurate Feature shape is generalized Spatial Analyst allows the user to integrate vector and raster themes. RASTER DATA MODEL CREDO • • • • Earth is treated as one continuous surface Each location is represented as a cell Cells are organized into a matrix of rows and columns called a grid Each grid contains cells that represent some kind of geographic phenomenon EXAMPLES (OF THE RASTER DATA MODEL) • Information from satellites • • • Scanned data Aerial photographs Other forms of image data where each pixel (grid cell) has a value What is a Grid Theme? A grid divides geographic space into uniform blocks or cells Every cell represents a portion of the earth (square kilometer, square meter, etc.) Each cell has a value that describes its location The grid theme is the primary data source used by Spatial Analyst Spatial Analyst stores raster themes as directories in the ARC GRID format Uniform structure important when combining or comparing data types (Note: Grid themes with integer values have a theme table, value attribute table that store the codes and categories. In a floating point grid theme, each cell stores a value that represents a measure of geographic phenomena have no theme table.) What is a Cell? Cell is the basic spatial unit for a grid theme CELL CREDO • • • • Cells are squares (equal height and width) User defines cell size Cell locations are referenced by their row and column position Every cell can be uniquely identified by its row and column position • • • • Top left cell in a grid is at the 0,0 position Rows and columns are numbered from 0,0 position The 0,0 cell is the row and column index position/origin of the grid Number of rows and columns does not have to be the same CELL VALUES • Cells are assigned an integer, floating point, or NO DATA value Value of the cell may represent… • • User can perform analysis cell by cell, by groups of cells, and for the entire grid Each cell can be referenced by an X,Y location Converting Vector Data (Themes) and Raster Data (Grids) Themes, including feature and image themes, can be converted to grids Vector to raster conversion is called rasterization Raster to vector conversion is called vectorization Demonstration #2 Examine Streets Feature Theme Convert Street Feature Theme to Street Grid Theme (using 50 foot radius) Convert Street Feature Theme to Street Grid Theme (using 10 foot radius) Compare Grid Themes and Consider Advantages and Disadvantages Why Would You Want to Convert From Feature to Grid or Visa Versa? Storing and managing grid themes Grid and INFO subdirectories Using source manager to copy, delete, and rename files Things to Consider When Choosing a Cell Size Resolution of input data Resulting database size and disk capacity Desired response time (processing speeds) The application and analysis being performed Storing Grid Themes User defines workspace where grid datasets will be stored ArcView creates the INFO subdirectory and grid subdirectories There is one INFO subdirectory and a subdirectory for each grid INFO subdirectories contain several files that relate to each grid's theme table Grid subdirectories contain several files that store geographic data Grid Subdirectory Grid subdirectories store data files about each grid Some grid data files have related INFO files, some do not If you alter a grid, ArcView automatically updates corresponding information dblbnd.adf - contains the minimum and maximum X,Y coordinates of the grid theme hdr.adf - contains grid cell resolution, type, etc. sta.adf - contains statistics about cell values (min, max, mean, etc.) vat.adf - stores unique cell values and a cell count for each value (only integer grids) W001001.adf - stores the first tile (W001002.adf - stores the second tile) prj.adf - optional ASCII text file used to store map projection information log - contains history of the grid dataset (type and time of operation performed) INFO Subdirectory arc.dir - contains data dictionary *.nit and *.dat - some vat.adf (grid data files) have related INFO files that occur in pairs Managing Grid Themes Storage of grid datasets in subdirectories complicates data management Important to use Source Manager to manage grid datasets This includes copying, deleting, and renaming grids Vector Vs Raster Vector Advantages Raster Advantages Very high resolution Simple structure High spatial accuracy Grid structure makes analysis easier Require less storage space Allows integration of imagery and GIS data Easier for the general public to understand Modeling can be performed easily and rapidly Introduction to Lab 6 We will use raster models to create a housing value surface for Cambridge It will be necessary to convert vector data sets into raster data sets We will rasterize the 1989 housing sales and 1990 Census data for Cambridge The key steps are as follows: Open Project Load Spatial Analyst Extension Add Themes - cambtigr, camborder, cambbgrp.shp, sales89 Set View Properties - meters Set Analysis Properties - cell size 100 Convert camborder to grid - it will later be used as a mask Now we will explore different ways to estimate housing values for cambridge • • • City assessor's database (agency monitors accuracy, but constituents lobby for lowest assessment) Recent sales (reflects market value, but not all sales reflect market value) Census (median housing values aggregated at the block group level, but values are self-reported)