Geographic Information Systems

1. Geographic Information Systems Chapter 1 - Introduction

2. 1.1 What is a GIS? • A Geographic Information Systems (GIS) is a computer system for capturing, storing, querying, analyzing, and displaying geographically referenced data. • It is also called geospatial data. • Geographically referenced data means the data that describe both the location and characteristics of spatial features such as roads, land parcels, and vegetation stands on the earth’s surface.

3. 1.1.1 GIS applications • GIS from the beginning, has been important in natural resources management including: land-use planning, natural hazard assessment, wildlife habitat analysis تحليل مواطن الحيوانات البرية , Water availability and quality , and many more different applications that could be enhanced using the application of GIS. • Recently, GIS is used in : crime analysis, emergency planning, market analysis, and transportation applications. • You will find several examples in the text book.

4. Cont. • Integrating GIS with GPS (Global Positioning System) using satellites and special towers introduces new and exciting different applications such as: interactive mapping, and location based services.

5. Some different applications • Forestry: • GIS is an efficient management tool to keep an up-to-date inventory of the timber resources. • Fire Departments: • GIS enhance their routing capabilities to ensure rapid response in emergencies. • Cellular Companies: • Site their transmission towers to ensure clear line of sight for signal transmission.

6. Cont. • Local governments: • Develop growth and development plans to modify zoning regulations to account for increasing population pressures. • Academic Disciplines: • To develop and test hypothesis concerning patterns of natural phenomena on the earth.

7. 1.1.2 Components of GIS • Like any other Information Technology, GIS requires the following four components to work with geospatial data: • Computer Systems: computers and Os to run GIS like Windows or UNIX, monitors to display data, digitizers and scanners for spatial data input, printers, plotters for hardcopy data display. • GIS software: it includes the program and the user interface for driving the hardware (like menus, graphical icons, and command lines).

8. Cont. • Brainware: important as HW and SW, it refers to the purpose and objectives, and provides the reason and justifications for using GIS. • Infrastructure: the necessary physical, organizational, administrative, and cultural environments to support GIS operations. This infrastructure includes requisite skills, data standards, data clearinghouses, and general organizational patterns.

9. 1.2 History of GIS • GIS is not new science, from the beginning of 1960s computers have been used to store and process spatial data. • Several companies and organizations have been involved in the development of GIS applications. • We will use arcView software developed by ESRI Inc. to make some GIS applications.

10. Cont. • Some of the centers and institutes that have GIS improvement: • Computer mapping at the University of Edinburgh, the Harvard Laboratory for Computer Graphics. • Canada Land Inventory. • Introduction of an urban street network with topology in the U.S. • GIS has to be difficult and hard to implement before the development of GUI, powerful and affordable HW and SW, and public digital data in 1990.

11. 1.3 Geographically Referenced Data • Geographically Referenced Data separate GIS from other Information Systems. • Before we begin discussing GIS, we have to understand data nature used with GIS applications. • For example roads: • To describe a road we need locations (where it is), and its characteristics: length, name, speed limit, and direction). • The location, also called geometry or shape, represents spatial data, whereas the characteristics are attribute data. • So the road, like any other geographically referenced data, has two main components: spatial data and attribute data.

13. 1.3.1 Spatial Data • Spatial data describes the location of spatial features which may be discrete or continuous. • Discrete features: • are individually distinguishable features that do not exist between observations. • Discrete features include points (well), lines (roads), and areas (land-use type). • Continuous features: • Are features that exist spatially between observations. • For example elevation and precipitation هطول.

14. Cont. • GIS represents these spatial features (on earth) as map features on the plane surface. • There must be a transformation system between features on the earth and those on the map. • Features on earth could have longitude طول and latitude خط العرض, while on the map there will be x- and y- directions. • Projection is the process of converting earth’s spatial surface to a plane surface, which could have some distortion.

15. Cont. • Data Model defines how spatial features are represented in a GIS.

16. Cont. • Vector Data Model uses points and x-, y- coordinates to construct spatial features of points, lines and areas. • Raster Data Model uses a grid and grid cells to represent the spatial variation of a feature. • Vector data model is suitable for representing discrete features, while raster data model is suitable for representing continuous features. • They also differ in data structure: raster could be represented simply by an array, vector could be using special mathematical equations.

18. Cont. • Topology: as used in GIS, expresses explicitly the spatial relationships between features, such as two lines meeting perfectly at a point an a directed line having an explicit left and right side. • Topological data are necessary to correct errors that could result from the projection process. • ESRI Inc. uses the term coverage for topological data and the term shapefile for nontopological data to distinguish between them.

19. Cont. • Higher level data are built in simple vector data of points, lines, and polygons. • Triangulated Irregular Network (TIN): approximates the terrain منطقة with a set of nonoverlapping triangles , is made of points and edges. • The Regions Data Model: which allows regions to overlap and to have spatially disjoint components, is built on lines and polygons.

21. Cont. • The Object-Oriented Data Model uses objects to organize spatial data. • An object is a set of built-in properties and can perform operations upon request. • To represent spatial features, objects may take the form of points, multipoints (collection of points), poly-lines (set of line segments), or polygons (including disjoint polygons).

22. 1.3.2 Attribute Data • Attribute Data describes the characteristics of spatial features. • For raster data, each cell has a value that corresponds to the attribute of the spatial feature at that location. • For vector data, the amount of attribute data to be associated with a spatial feature can vary significantly. • A road segment may have the attributes of only length and speed limit, whereas a soil polygon may have dozens of physical and chemical properties, interpretations, and performance data.

23. 1.3.3 Joining Spatial and Attribute Data • There are two models for joining spatial and attribute data. • The georelational data model: • Stores attribute data separately from spatial data in a split data system. • Spatial data are stored in graphic files, attribute data are stored in tables, and they are linked through the feature IDs.

24. Cont. • Object Oriented Data Model: • Stores spatial data as an attribute along with other attributes data in a single table. • Whether spatial and attribute data are stored in a split system or a single system, the relational database model is the norm for data management in GIS. • Relational Database: • Is a collection of tables (relations). • the connection between tables is made through a key, a common filed whose values can uniquely identify a record in a table.

25. Cont. • Relational databases are efficient and flexible for data search, data retrieval, data editing, and creation of tabular reports.

26. 1.4 GIS Operations • We can group GIS activities into spatial data input, attribute data management, data display, data exploration, data analysis, and GIS modeling.

27. 1.4.1 Spatial Data Input • The most expensive part of a GIS project is data acquisition. • There are two basic options for that: • Use existing data. • Create new data. • It is preferable to try the digital data clearinghouses to see if they have public or private data to start with, if not, creating data in this case will be the choice.

28. Cont. • New digital spatial data can be created from satellite images, GPS data, field surveys, street addresses and text files with x-, y- coordinates (also paper maps could be used). • Manual digitizing or scanning can convert paper maps into digital format.

29. 1.4.2 Attribute Data Management • To complete a GIS database, we must enter, verify, and manage attribute data. • Attribute data are usually managed in a relational database. • Two basic elements in the design of relational database are the key and the type of data relationship: • The key establishes a connection between corresponding records in two tables. • The type of data relationship dictates how the tables are actually joined or linked.

30. 1.4.3 Data Display • Mapmaking is a routine GIS operation for data visualization, query, analysis, and presentation, • A map has a number of elements: title, subtitle, body, legendدليل, north arrow, and scale. • These elements work together to bring spatial information to the map user. • The first step in data display is to assemble map elements (using GUI). • The second step is map design (creative process that cannot be easily replaced by default templates and computer codes).

31. 1.4.4 Data Exploration • Is data-centered query and analysis. • It allows the user to explore the general trends in the data, to take a close look at data subsets, and to focus on possible relationships between data sets. • There will be dynamically linked visual tools, so that when a data subset is highlighted in a table, the corresponding features in the map will be highlighted. • Geographic Visualization: • refers to the use of maps for setting up a context حالةfor visual information processing.

33. 1.4.5 Data Analysis • The previous figure classifies data analysis into six groups. • The basic data models are vector and raster, each having its own set of common analytical tools. • For vector data, these tools include map overlay, map manipulation, buffering (for example highlight the areas that far 500 meters beside a river), and distance measurement.

34. Cont. • Map overlaying combines spatial data and attribute data from different maps to create the output.

35. Cont. • Map manipulation tools perform dissolving احلال, clipping, merging, splitting, erasing, and other tasks. • Distance measurement, as the term suggests, measures distance between map features. • Common tools for raster data include local, neighborhood, zonal operations.

36. Cont. • A local operation involves individual cells; a neighborhood operation, a specified neighborhood; a zonal operation, a group of connected cells; and a global operation, an entire grid. • These, operations may apply to a single grid or multiple grids. • As examples, a local operation involving single grid can convert the measurement unit of a slope map from percent to degrees, and a local operation involving multiple grids can compute the average of the input grids on a cell-by-cell basis.

37. Cont. • A raster operation involving multiple grids is conceptually similar to a vector-based map overlay operation but the procedures differ: the raster operation can take advantage of the fixed cell locations, whereas the vector operation must deal with the intersection of polygon boundaries.

38. Raster data analysis with multiple grids can take advantage of the fixed cell locations.

39. 1.4.6 GIS Models and Modeling • A model is a simplified representation of a phenomenon or a system. • GIS Modeling refers to the use of a GIS and its functionalities in building a model with geographically referenced data. • There are 4 different models used by GIS : binary, Index, Regression, and Process models.

40. Cont. • Binary model: uses a query statement to produce a binary (true or false) map that separates map features that satisfy the criteria from those that do not.

42. Cont. • Index Model: is similar to binary model, but it is much more elaborate in its evaluation procedure. • Regression Model: uses map overlay to gather data for analyzing the statistical relationship between a dependent variable and independent variables. • There are two regression types: • Linear regression: when dependent and independent variables are numeric. • Logistic regression: when dependent and independent variables are categorical.

43. Cont. • Process Model: integrates existing knowledge about the environment processes in the real world and quantifies the processes with a set of relationships and equations.