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GIS Program 6th GIS Workshop

GIS Program 6th GIS Workshop. Introduction to ArcGIS GIS CONCEPT. Eng. Hussain Darwish Technical College-Baghdad. Geographic Information Systems. Eng.Hussain Darwish Technical College-Baghdad. A Generic Definition of GIS. Geographic = spatially referenced data

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GIS Program 6th GIS Workshop

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  1. GIS Program6th GIS Workshop Introduction to ArcGIS • GIS CONCEPT Eng. Hussain Darwish Technical College-Baghdad

  2. Geographic Information Systems Eng.Hussain Darwish Technical College-Baghdad

  3. A Generic Definition of GIS • Geographic = spatially referenced data • Information = data processed into a usable form • System = a framework for manipulating, analyzing and presentation of information

  4. What is a Geographic Information System (GIS)? • A GIS is an organized collection of computer hardware, software, geographic data, and people, to efficiently capture, store, update, manipulate, analyze, and display all forms of geographically referenced information. • A GIS is both a database system with specific capabilities for spatially-reference data, as well [as] a set of operations for working with data . . . In a sense, a GIS may be thought of as a higher-order map.”

  5. GIS COMPONENTES

  6. GIS requirements 1. Data input, from maps, aerial photos, satellites, surveys, GPS, and other sources 2. Data storage, retrieval, and query 3. Data transformation, analysis, and modeling, including spatial statistics 4. Data representation (reporting), such as maps, reports, and plans

  7. Basic Questions Asked • with a GIS: • • What is at..._____? (Location) • • Where is it..._____? (Condition) • • What has changed...? (Trend) • • Which is the best way...? (Routing) • • What is the pattern...? (Pattern) • • What if...? (Modeling)

  8. What is a Geographic Information System (GIS)? • An information system has a full range of functions to: • process observations • process measurements • provide descriptions • explain data • make decisions

  9. CaptureData RegisterMap Base Store Datain Computer InterpretData Convert Datato DigitalFormat ProcessData DisplayResults GIS Process

  10. GIS DATA • SPATIAL (POSITIONAL) DATA • ATTRIBUTE (TABULAR) DATA

  11. Images ImageProcessingSystem StatisticalReports Maps Map DigitizingSystem Statistical Analysis System SpatialDataBase AttributeDataBase DatabaseManagementSystem Geographic Analysis System StatisticsTabular Data CartographicDisplay System Maps GIS System

  12. GIS Data Format • There are two formats used by GIS systems to store and retrieve geographical data: • Raster data • Vector data

  13. Spatial Data Model: Basic Data Format • GIS are driven by spatial data • Two basic spatial (coordinate/geometric) data exist • Vector: based on geometry of • points • lines • polygons • Raster: based on geometry of • grid cells (images, bitmaps, DEMs)_

  14. Raster Format • Data are divided into cell, pixels, or elements • Cells are organized in arrays • Each cell has a single value • Row and Column Numbers are used to identify the location of the cell within the array. • Perhaps the most common example of raster data is a digital image.

  15. Vector Format • Data are associated with points, lines, or boundaries enclosing areas (polygons) • Points are located by coordinates • Lines are described by a series of connecting vectors (line segments described) ,by the coordinates of the start and end point • Areas or polygons are described by a series of vectors enclosing the area.

  16. Vector Format • Any number of factors or attributes can be associated with a point line or polygon. • Data are stored in two files: • a file containing location information • a file containing information on the attributes • A third file contains information needed to link positional data with their attributes.

  17. GIS Data Types • Features • Point datasets • Line datasets • Polygon datasets • Surfaces • Grid datasets • TIN datasets • Images datasets • Networks • Simple denstritic networks • Simple loop networks

  18. GIS VectorFormat GIS RasterFormat Map Feature (X,Y)Coordinate in space Cell Located in an Array row and column Vector and Raster Representation of Point Map Features

  19. Point Features • All points required to define the feature geometry have to be stored as part of the feature definition.

  20. Point Features • Point datasets One-to-one relation between features in the map and records in the table.

  21. GIS VectorFormat GIS RasterFormat Map Feature Vector and Raster Representation of Line Map Features

  22. Line Features • Line datasets One-to-one relation between features in the map and records in the table.

  23. GIS VectorFormat GIS RasterFormat Map Feature Vector and Raster Representation of Area Map Features

  24. Area Features • Polygon datasets One-to-one relation between features in the map and records in the table.

  25. Surfaces Features • Grid datasets

  26. (x, y) Number of columns Cell size Number of rows Data Structure of Surfaces • Grid datasets: • Cellular-based data structure composed of square cells of equal size arranged in rows and columns. • Grid definition requires: (1) the coordinates of the upper-left corner, (2) the cell size, (3) the number of rows, (4) the number of columns, and (5) the value at each cell. • Cells that do not store any value are called NODATA cells.

  27. Surfaces Features • TIN datasets

  28. Data Structure of Surfaces • Triangular Irregular Network (TIN) Datasets: • Dataset constructed by connecting points -- for which the TIN parameter is known – forming triangles. • Triangle sides are constructed by connecting adjacent points so that the minimum angle of each triangle is maximized. • Triangle sides cannot cross breaklines. • The TIN format is efficient to store data because the resolution adjusts to the parameter spatial variability.

  29. Data Structure of Surfaces • Triangular Irregular Network (TIN) Datasets

  30. Image Surface Features • Image datasets

  31. Data Structure of Surfaces • Image datasets: • ARC Digitized Raster Graphics (ADRG) • Windows bitmap images (BMP) [.bmp] • Multiband (BSQ, BIL and BIP) and single band images [.bsq, .bil and bip] • ERDAS [.lan and .gis] • ESRI Grid datasets • IMAGINE [.img] • IMPELL Bitmaps [.rlc] • Image catalogs • JPEG [.jpg] • MrSID [.sid] • National Image Transfer Format (NITF) • Sun rasterfiles [.rs, .ras and .sun] • Tag Image File Format (TIFF) [.tiff, .tif and .tff] • TIFF/LZW

  32. Networks • Simple networks

  33. Networks • Simple loop networks

  34. Nodes Vertices Data Structure of Features • A line is an open sequence of points in which the first and last points are called nodes, and the remaining intermediate points are called vertices.

  35. Data Structure of Features • Simple lines • Complex lines

  36. Data Structure of Features • Simple polygons • Complex polygons

  37. Data Structure of Features • Space-filling polygons • Not space-filling polygons

  38. 5 B C 1 II 3 4 A I D 2 III Data Structure of Features • Line and polygon topology

  39. A B 5 C 4 6 3 2 D E F 8 7 G 1 1 10 11 I H 9 J 12 K Data Structure of Networks • Simple loop networks: • System of simple lines -- called links -- connected at their nodes. • Links can point in either direction or in both directions.

  40. Vector and Raster Formats • Most GIS software can display both vector and raster data. • Raster formats are efficient when comparing information among arrays with the same cell size. • Raster files are generally very large because each cell occupies a separate line of data. • Vector formats are efficient when comparing information whose geographical dimensions are different.

  41. Vector Data Model • Major types (formats) of vector data available in ArcGIS • ESRI GeoDatabases • ESRI shapefiles • ArcInfo coverages and libraries • CAD files (AutoCAD DWG, DXF;Microstation DGN) • StreetMap files • Spatial Database Engine (SDE) data • ASCII point coordinate data • Linear measure (route) data_

  42. Vector Data Model • Characteristics of the vector data model: • + Features are positioned accurately • + Shape of features can be represented correctly • + Features are represented discretely (no fuzzy boundaries) • – Not good for representing spatially continuous phenomena • – Potentially complex data structure (especially for polygons); can lead to long processing time for analytical operations_

  43. Raster Data Model • Raster spatial data model • origin is set explicitly • cell size is always known • cell references (row/column locations)are known • cell values are referencedto row/column location • values represent numerical phenomena orindex codes for non-numerical phenomena_

  44. Raster Data Model • Characteristics of the raster data model: • Rectangular grid of square cells • Shape of discrete polygonal features generalized by cells • Continuous (surface) data represented easily • Simple data structure_

  45. Raster Data Model • Raster data are good at representing continuous phenomena, e.g., • Elevation, slope, aspect • Soil types. • Electromagnetic reflectance (photographic or satellite imagery) • Radar images. • Continuous phenomena

  46. Raster formats are efficient when comparing information among arrays with the same cell size. Raster files are generally very large because each cell occupies a separate line of data, only one attribute can be assigned to each cell, and cell sizes are relatively small. Vector formats are efficient when comparing information whose geographical shapes and sizes are different. Vector files are much smaller because a relatively small number of vectors can precisely describe large areas and a many attributes can be ascribed to these areas. Comparison of Raster and Vector Formats Raster Vector

  47. Raster representations are relatively coarse and imprecise Vector representations of shapes can be very precise. Comparison of Raster and Vector Formats Raster Vector Most GIS software can display both raster and vector data. Only a limited number of programs can analyze both types of data or make raster type analyses in vector formats.

  48. Attributes data Types of Attributes data • Numeric data ( e.g. size, area, temperature,…etc.). • Semantic data (e.g. class, type, name, quality…etc.). Each of them may be stored in a coded manner.

  49. Relational Database Model & Attribute Data Structures • The “where” of GIS is determined by coordinate (map) data structures, but … • The “what” of GIS is determined by tabular (relational database) data structures • Thus, tabular data are just as important as coordinate data.

  50. Relational Database Model & Attribute Data Structures • Attribute data are stored in database tables. • Tables are composed of: • fields(columns) and • records(rows)_

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