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Geographical Data Structures and Models for Inputting Spatial Information

This article explores the different geographical data structures and models for inputting spatial information, including raster and vector representations. It also discusses the ArcView Shapefile model and the process of editing vector objects.

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Geographical Data Structures and Models for Inputting Spatial Information

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  1. Topic 3 – Geographical Data Structures A – Geographic Data Models B – Inputting Spatial Information

  2. A Geographic Data Models • 1. Raster Representation • 2. Vector Representation • 3. The ArcView Shapefile Model

  3. 1 Spatial Objects • Definition • Delimited geographic areas. • Ex. park, golf course, wildlife reserve. • Associated attributes. • Attributes are qualities or characteristics of spatial objects. • Ex. census data, types of vegetation, heights or depths. • Types of geographical delimitation • Three conventional delimitations. • Points, lines and polygons. Grass, 1 feet Shrubs, 6 feet Forest, 25 feet

  4. Representation 1 Raster Representation • Issue • A model for a computer to represent real geographical elements as graphical elements (on screen or on paper). • Two models of representation possible: • Raster (grid-based) • Vector (line-based)

  5. 1 Raster Representation • Cellular organization • Divides space in a series of units. • Each unit is generally similar in size to another. • Grid cells is the most common raster representation. • Features are divided into cellular arrays. • Coordinate (X,Y) is assigned to each cell, as well as a value. • Allows for registration with geographic reference system. • JPEG, GIF, BMP and TIF are raster formats. • Tessellation • Geometric shapes that can completely cover an area. • Squares / Rectangles. • Triangles. • Hexagons.

  6. Column Row 1 Raster Representation Point Line Real world Value =0 =1 =2 =3 Raster Grid Area Triangles Hexagons

  7. 1 Raster Representation 700 meters • Advantages • Easy to conceptualize. • Overlay operations are easy. • A two-dimensional array forms a coverage. • The problem of resolution • For a small grid: • Coarse resolution but limited storage space. • For a large grid: • Fine resolution but large storage space. Size = 7x7x4 = 196 Cell = 10 m x 10 m = 100 m2 Size = 10x10x4 = 400 Cell = 7 m x 7 m = 49 m2

  8. 1 The Mixed Pixel Problem

  9. 2 Vector Representation • Concept • Assumes that space is continuous, rather than discrete. • Infinite (in theory) set of coordinates. • Points • Spatial objects with no area but can have attached attributes. • A single set of coordinates (X and Y) in a coordinate space. • Lines • Spatial object made up of connected points (nodes). • Have no width. • Polygon • Closed areas that can be made up of a circuit of line segments. • Line segments that make up a portion of a polygon. Point (X,Y) (X2,Y2) Line (X4,Y4) (X3,Y3) (X5,Y5) (X,Y) (X,Y) (X2,Y2) Polygon (X5,Y5) (X3,Y3) (X4,Y4)

  10. Node 1 Node 2 Node 3 2 3 1 Arc C Arc D Arc E Arc B Node 5 5 Node 4 Arc H 4 Arc F Arc G Arc A Node 8 8 6 Node 6 Arc I Node 7 Arc J 7 Node X Y Arc From To 1 2 3 4 5 6 7 8 12 22 53 24 5 36 17 38 4 16 42 17 9 43 21 44 A B C D E F G H I J 6 4 1 2 5 4 7 3 8 7 4 1 2 3 2 5 5 8 7 6 2 Vector Representation

  11. 2 3 1 C D A E B 5 C H 4 F G A B 8 6 I J 7 Poly # of arcs Arc list A B C 4 4 5 B,C,E,F A,F,G,J E,D,H,I,G 2 Vector Representation

  12. Point Table Line Table Poly. Table Attrib. Table Pt. ID X Y Ln. ID Pt. 1 Pt. 2 Pol. ID Ln. ID Pol. ID Attrib. 1 2 3 4 5 ... 24.5 24.8 27.8 30.1 14.2 ... 27.4 24.1 22.5 29.9 30.1 ... 35 36 37 38 39 ... 1 4 6 2 8 ... 3 2 8 10 11 ... 74 74 74 75 75 ... 38 35 29 28 42 ... 74 75 76 77 78 ... 104.2 100.1 105.7 102.7 106.1 ... 2 Vector Representation Relational Links

  13. 2 GIS Vector Models – 3 Major Models Unique identifier Coordinate and Topological files Attribute tables Relational database Hybrid (Features) - Relational join – (Attributes) Relational database Integrated Element – Class – Attribute Object store Object-Oriented

  14. 3 The ArcView Shapefile Model • Format • Hybrid data model. • Store spatial information in a vector format. • Sequential list of features. • Less processing intensive (faster drawing time). • Two-dimensional (x,y) and three-dimensional (x,y,z) features supported. • Each shapefile represent one shape type. • Point, Polyline, and Polygon are the most common. • Three major components: • Main file (*.shp): Store the list of geographical features. • Database file (*.dbf): Store the attributes in a table. • Index file (*.shx): Links the database and geographical features.

  15. 3 The ArcView Shapefile Model Main file (*.shp) Index file (*.shx) dBase table (*.dbf) a a b b c c d d

  16. 3 The ArcView Shapefile Model geometry object identifier (optional) geometry tracking field (optional) geom id shp_len type surface width lanes name 101 102 103 104 105 ... 4507.4 3491.1 2321.8 682.9 1279.1 ... 2 1 3 5 4 ... asphalt concrete asphalt gravel asphalt ... 85.3 45.1 75.9 35.2 60.3 ... 4 2 4 2 4 ... abc def ghi jkl mno ... Predefined fields custom fields

  17. C Inputting Spatial Information • 1. The Input Subsystem • 2. Choosing What to Input • 3. Editing Vector Objects

  18. 1 Input Subsystem • Digitizing • Most difficult and time consuming task in mapping and GIS. • Takes about 75% of the time in a mapping project. • About 75% of the costs of operating a GIS system. • Digitizing and errors • Since digitizing is very time consuming, you must get it right on the first time. • Error correction is excessively long and costly. • The larger the file, the bigger the number of potential errors. • Each model, raster or vector, requires special digitizing equipment.

  19. 1 Input Subsystem • Mouse • The mouse is the most basic input system. • A rolling ball with two sensors, one of X, one for Y. • It continuously sends a set of X,Y coordinates to the CPU. Buttons are sending interrupts to the CPU. • By itself, it cannot be used to encode mapping information, but it is suitable for tracing. X,Y Pointer

  20. 1 Input Subsystem • Tracing and digitizing • Tracing is a form of digitizing. • Mainly imply using a scanned image. • Easier for less experienced users. • Precision is limited to the resolution of the scanned image.

  21. 1 Input Subsystem • Digitizer • Table containing a matrix of very small cables. • A mouse-like device, often called a puck (cursor), moves over the table. • Creates an electromagnetic field disruption on the grid, the center of which is the X,Y coordinate. • One of the most precise digitizing technique. • Varies according to: • Stability: Tendency of coordinates to change with temperature. • Repeatability: With the same location, are the X,Ys exact? • Linearity: Keeping up with movements of the cursor. • Resolution: The smallest unit or measure it can handle. • Skew: Differences between variation of Xs and Ys.

  22. 1 Input Subsystem • Scanner • An horizontal light makes a pass and each line is read by a photoelectric cell (like a photocopy machine). • Resolution: • Number of pixels per units of surface the cell can read. • 1,200 DPI (Dots per inch) is common. • Color depth: • Number of different colors the cell can read. • 1-bit only supports B&W, 4-bit 16 colors (or shades of gray), 8-bit 256 colors and 12-bit 16.7 million colors. • Two types: • Drum scanners (rotating drum), • Flat-bed scanners.

  23. 2 Choosing What to Input • Some Rules • Find what are your goals. • Digitize the information you really need: • Most base maps contain a lot of information. • Try to choose a conventional source of spatial data. • Use the level of accuracy corresponding to your task: • High levels of accuracy equal high levels of diminishing returns. • Input data as separate themes: • Each theme should be specific. • Each theme has a specific geographic feature (point, line or polygon).

  24. 2 Choosing What to Input Type of Feature Information Points Lines Polygons Streets Store Locations Parks Highways Themes

  25. Not enough Too Many Good Solution 2 Choosing What to Input • How Much to Input • Choosing the right amount of information to encode is difficult. • Depends on the level of accuracy.

  26. 2 Base Map (Air Photograph)

  27. 2 Digitizing Major Roads and the Hydrography

  28. 2 Digitizing Lots

  29. 2 Final Product

  30. 3 Editing Vector Objects • Points • Simply changing the coordinate. • Dragging and dropping the most common. • Lines • Changing the coordinate of one or more points. • Splitting a line in two. • Merging lines. • Polygons • Changing the coordinate of one or more points (the last point is also the first point). • Splitting a polygon in two. • Using a boundary to draw another polygon. • Merging polygons. • Creating an island in a polygon. • Creating an intersection.

  31. Intersection 3 Editing Vector Objects Splitting a line Moving a point (vertex) Merging lines Line B Line A

  32. Polygon A Polygon B 3 Editing Vector Objects Moving a point (vertex) Splitting a polygon

  33. 3 Editing Vector Objects Merging polygons Using a boundary

  34. 3 Editing Vector Objects Creating an island Creating an intersection

  35. 3 Editing Vector Objects • Snapping • Make a vertex take the coordinates of a reference. • Spanning tolerance defines the “search space”. • Avoid overshoots and undershoots for lines. • Avoid gaps and overlaps for polygons. • Snap to Vertex • Snaps the next vertex to the nearest vertex in an existing line or polygon. • Snap to Boundary • Snaps the next vertex to the nearest line segment in an existing line or polygon boundary.

  36. 3 Editing Vector Objects • Snap to Intersection • Snaps the next vertex to the nearest node common to two or more lines or polygons. • Snap to Endpoint • Snaps the next vertex to the nearest endpoint of an existing line. • For lines only.

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