Introduction to GIS / GISc 01 / 23 / Six Components of a GISystem

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1 /0/0 Introduction to GIS / GISc 0 / / 0 Topics Today: GIS components GIS knowledge GIS functions (intro) Validation and Verification Problem Solving Six Components of a GISystem People Software Network Data Hardware Procedures

2 /0/0 What is GIScience? GISc advocates claim that: the procedures of users, and the functions of GIS software (geographic knowledge) in conjunction with the data stored in tabular databases accommodate the ability for both Idiographic, and Nomothetic analysis simultaneously, thus GISc is born! Do you agree? Think about it for a while~ Nomothetic and Idiographic Epistemological terms to describe two distinct approaches to producing and comprehending knowledge Epistemology theories of knowledge or ways of knowing Nomothetic concerned with the universal and the general Usually quantitative Idiographic concerned with the unique and the particular Usually qualitative

3 /0/0 One of many definitions for GISc A system of integrated, computer-based tools for end-toend processing (capture, storage, retrieval, analysis, display) of data using location on the earth s surface for integration in support of integrated decision making. set of integrated tools for spatial analysis encompasses end-to-end processing of data capture, storage, retrieval, analysis/modification, display uses explicit location on earth s surface to relate data aimed at decision support (and on-going operations) What is GIS? GIS s are spatial (geographic) databases that support a myriad of organizations and activities Therefore, they are crucial to operation of organizations Organizations like: US EPA; US NGA; US DoD; US DHS; US NOAA; US NPS; US FEMA; PA DEP; PA DCNR; PennDOT; Federal Express; Chase Manhattan Bank; Sears; USA Today Or Apple, FourSquare, Facebook, Googel, Giant Eagle the list goes on, and on, and on~

4 /0/0 from Longley, et. al~ GIS is --- A container of maps in digital form A computerized tool for solving geographic problems A spatial decision support system A mechanized inventory of geographically distributed features A tool for revealing what is otherwise invisible in geographic information Defining Geographic Information Systems (GIS) The common ground between information processing and the many fields using spatial analysis techniques (Tomlinson, 97) A powerful set of tools for collecting, storing, retrieving, transforming, and displaying spatial data from the real world (Burroughs, 986) A computerized database management system for the capture, storage, retrieval, analysis and display of spatial (locationally defined) data (NCGIA, 987) A decision support system involving the integration of spatially referenced data in a problem solving environment (Cowen, 988)

5 /0/0 The Purpose of a GISystem Allows the geographic features in real world locations to be digitally represented so that they can be abstractly presented in map (analog) form, and can also be worked with and manipulated to address some problem Provides a digital representation of the real world for use in operational management, decision making, and science Who Uses GIS and How do They Use It? Urban Planning, Management & Policy Zoning, subdivision planning Economic development Code enforcement Emergency response Crime analysis Tax assessment Political Science Redistricting Analysis of election results Business Demographic Analysis Market Penetration/ Share Analysis Site Selection Environmental Sciences Monitoring environmental risk Management of watersheds, floodplains, wetlands, forests, aquifers Environmental Impact Analysis Hazardous or toxic facility siting Groundwater modeling and contamination tracking Real Estate Neighborhood land prices Traffic Impact Analysis Determination of Highest and Best Use Health Care Epidemiology Needs Analysis Service Inventory

6 /0/0 What GIS Applications Do: manage, analyze, communicate Make possible the automation of activities involving geographic data map production calculation of areas, distances, route lengths measurement of slope, aspect, viewshed logistics: route planning, vehicle tracking, traffic management Allow for the integration of data previously confined to independent domains (e.g property maps and air photos) By tying data to maps, permits the succinct communication of complex spatial patterns (e.g environmental sensitivity) Provides answers to spatial queries (how many elderly in the Pittsburgh region live further than 0 minutes at rush hour from ambulance service?) Perform complex spatial modeling (what if scenarios for transportation planning, disaster planning, resource management, utility design) Contributing Disciplines to GIS: I The convergence of technological fields and traditional disciplines Geography thinking spatially long tradition in spatial analysis provides techniques for conducting spatial analysis Cartography concerned with the display of spatial information maps have been a major source of information input for GIS long tradition in map design which is an important output from GIS Remote Sensing images from air and space are a major (& growing) source of spatial data low cost and consistent update of input data anywhere in the world interpreted data from remote sensing can be merged with other GIS data Photogrammetry uses aerial photographs for making accurate spatial measurements source of most data on topography (elevation) used in GIS 6

7 /0/0 Contributing Disciplines to GIS: II The convergence of technological fields and traditional disciplines Geodesy Source of high accuracy positional control for GIS GPS (global positioning system) technology is revolutionizing efficiency, cost, and accuracy Statistics many GIS models are statistical many statistical techniques used in GIS analysis statistics important to understanding issues of error and uncertainty in GIS data Computer Science earlier computer-aided design (CAD) work in CS computer graphics and visualization database management systems (DBMS) Five M s of GIS Applications:. Mapping Traditional Output Perhaps the least powerful output Maps are source of input data too (data capture). Measurement Extracting distance information from data i.e., stream length from A location to B location. Monitoring Accessing information spatially and temporally. Modeling Assembling the data housed in the hardware in an organized and analytical manner in the software for knowledge extraction. Management Theory The creation, deletion, storage, organization, updating and archiving of data 7

8 /0/0 Functional Elements of a GIS The Functional Steps in a Typical GIS Project Practice Steps FOLLOWING project scoping: I. Data acquisition (never underestimate the cost!) paper maps digital files remote sensing/satellite fieldwork II. Preprocessing: preparation & integration format conversion digitizing and/or scanning edge matching and rectification III. Data Management variable selection & definition table design (performance v. usability) CRUD policies/procedures: Create (data entry), Retrieve (view), Update (change), Deletion (remove) IV. Manipulation and Analysis (all the user cares about!) address matching network analysis terrain modeling (e.g. slopes, aspects) V. Product Generation tabular reports graphics (maps and charts) The GIS Data Model: Geographic Integration of Information Data is organized in layers, coverages or themes (synonomous concepts), with each theme representing some phenomena on the earth s surface Layers are integrated using explicit location on the earth s surface, thus geographical location is the organizing principal. 8

9 /0/0 Changing Domain and Role of GIS Source: Forer and Unwin, 998 Evidence and Wisdom: Evidence is somewhere between Information and Knowledge Evidence can be a thing or things helpful in forming a conclusion or judgment to indicate clearly; exemplify or prove in science, evidence usually goes toward supporting or rejecting an hypothesis scientific evidence is usually empirical Wisdom is at the top of the decision making process hierarchy Wisdom knowledge of what is true or right coupled with just judgment as to action Insight into a process (whether physical or conceptual) the ability to optimally (effectively and efficiently) apply perceptions and knowledge and so produce the desired results 9

10 /0/0 Validation vs. Verification The process of checking to see if something satisfies a certain criteria to give official sanction, confirmation, or approval to; substantiate Models are often validated Quality control Validation- Verification- evidence that establishes or confirms the accuracy or truth of something the process of research, examination, etc., required to prove or establish authenticity or validity of results Results should be verified (but this is rarely done) Quality assurance Problem Solving: How do we solve problems? Do we first define what we want to know? Are we confronted with a situation in which we have no solutions or answers? What is the difference between a solution and an answer? We must define the problem- We must determine what kind of data is needed to provide a solution to the problem Then, we must understand how to make information from the data 0

11 /0/0 From Data to Information to Knowledge: Basic way: Categorization of Data (idea) User-determined characteristics to be sought out in the data Used to Identify patterns in data Patterns are interpreted as information Information used in problem solving Classification of Data (method) Method to determine differences or similarities of data based on knowledge (often based on rules) Rules are determined on agreed upon procedures Should be based on knowledge (and a little wisdom, too) Research Question (example) What do we want to know? How much and what kind of land-use changes occurred in southwestern PA from 99 to 00? What kind of data is needed to provide a solution to the problem? Satellite image data (raster) from 99 and 00 How will we process (make information) from the data? Categorize then classify the data, then search for differences between the two years

12 /0/0 Research Question (example) How much and what kind of land-use changes occurred in southwestern PA from 99 to 00? Supervised Classification Anderson Level II (idea to categorize the data) Maximum Likelihood (Probability) (method to classify the data) Recoded to Five basic information classes (data categories). Water. Urban (High-Density Built-Environment). Residential (Low-Density Built-Environment). Agriculture / Grass (Open Space). Forest Image Differencing Technique Matrix Analysis Data Sets: Data Landsat TM(99) & ETM+ (00) 7/ 7/ 0/0/99 0/06/00

13 /0/0 Data Sets: Raster (starts with an array) Data Sets: then array is populated with data. Water. Urban (High-Density Built-Environment). Residential (Low-Density Built-Environment). Agriculture / Grass (Open Space). Forest

14 /0/0 Data Sets: data is then coded and displays like-patterns (using color). Water. Urban (High-Density Built-Environment). Residential (Low-Density Built-Environment). Agriculture / Grass (Open Space). Forest Data Sets: but is still just data until the user makes information from it. Water. Urban (High-Density Built-Environment). Residential (Low-Density Built-Environment). Agriculture / Grass (Open Space). Forest

15 /0/0 The GIS Model: example Here we have multiple layers: --vegetation --soil --hydrology They can be related because precise geographic coordinates are recorded for each layer. longitude Layers may be represented in two ways: in vector format as lines in raster(image) format as pixels Analysis Model: 99 Classified Image 00 Classified Image Model was validated by others with knowledge that the process was sound and that it would provide the intended results required to answer the problem: Matrix fromto landuse classes Table of Zonal Results

16 /0/0 Spatial Analysis Classified Results: Verification of Results An attempt to verify the results of the analysis was performed Accuracy Assessment 6 points were verified out of millions of pixels Accuracy Reports Overall Classification Accuracy: 99 8% 00-8% Change Detection Accuracy: 67% 6

17 /0/0 Categorized Tabular Results: Information Class Change Distribution by Pixel Count (Percentage) 00 Water Urban Residential Forest AgGrass 99 TOTAL 09,877, ,7 Water (89%) (0%) (<%) (<%) (<%) 7,977 7,8,707,99,60 79,068 Urban (%) (%) (%) (%) (9%) 7,7,069,0 87,97 6,98,,087 Residential (<%) (%) (69%) (9%) (8%) 67 6,9 86,99 8,06, 96,8 9,66,9 Forest (<%) (<%) (6%) (88%) (%) 8,99,9,977,9,9,7,09 7,8,88 AgGrass (<%) (%) (7%) (8%) (6%) TOTAL 8,779 6,6,86,69 0,9,6,67,9 Combine Data for further Information Percent Change Socioeconomic Data Shaler Township Mount Lebanon Upper St. Claire Robinson Township (A) McCandless Bethal Park Kennedy Township McKeesport City Pine Township Adams Township Municipality N. Huntingdon Township Cranberry Township S. Fayette Township Ohio Township Peters Township N. Strabane Township Union Township Robinson Township (W) Redstone Township Carrol Township Centreville Borough Menallen Township N. Fayette Township Deemston Borough 0 Number of Planning Tools Change in Population Change in Housing Households Units Change in Income Forest to Urban Forest to Residential Forest Open space Upper Tyrone Township Percent Change Forest 7

18 /0/0 Query Information for Knowledge At- Risk Municipalities 8