Introduction to GIS / GISc 01 / 25 / 2017

Transcription

1 //07 Introduction to GIS / GISc 0 / 5 / 07 Topics Today: GIS components GIS knowledge GIS functions (intro) Validation and Verification Problem Solving Six Components of a GISystem People Software Networ k Data Hardware Procedure s

2 //07 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 //07 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 //07 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 //07 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 5

6 //07 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) Five M s of GIS Applications: Theory. 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 5. Management The creation, deletion, storage, organization, updating and archiving of data 6

7 //07 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. 7

8 //07 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 8

9 //07 Validation vs. Verification Validation 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 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 control 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 9

10 //07 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) How Do We Represent These Data Types in a GIS? The Raster and Vector data models 0

11 //07 Rasters and Vectors How to represent phenomena conceived as fields or discrete objects? Raster Divide the world into square cells Register the corners to the Earth Represent discrete objects as collections of one or more cells Represent fields by assigning attribute values to cells More commonly used to represent fields than discrete objects Concept of Vector and Raster Real World Raster Representation R T R T H R R R R 5 R 6 R T T H 7 R T T 8 R 9 R Vector Representation point line polygon

12 //07 Characteristics of Rasters Pixel size The size of the cell or picture element, defining the level of spatial detail All variation within pixels is lost Assignment scheme The value of a cell may be an average over the cell, or a total within the cell, or the commonest value in the cell It may also be the value found at the cell s central point Raster representation Each color represents a different value of a nominal-scale field denoting land cover class Legend Mixed conifer Douglas fir Oak savannah Grassland

13 // X Y Data Sets: then array is populated with data Water. Urban (High-Density Built-Environment). Residential (Low-Density Built-Environment). Agriculture / Grass (Open Space) 5. Forest

14 //07 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) 5. 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) 5. Forest

15 //07 Representing Data using Raster Model Area is covered by grid (usually) with equal sized cells commercial Res. Location of each cell calculated from origin of grid: two down, three over (usually from upper left, but lower left in ARCVIEW) industrial Res. public Called raster cells or pixels (picture elements) raster data often called image data Attributes are recorded by assigning each cell a single value based on the majority feature (attribute) in the cell, such as land use type Representing Data using Raster Model Easy to do overlays/analyses, just by combining corresponding cell values: crime index = juvenile + adult crime rate (I think it s potentially improper ) why raster is faster, at least for some things commercial industrial Res. Res. public Simple data structure: directly store each layer as a single table analogous to a spreadsheet ) no computer database management system (DBMS) required although GIS systems incorporate them 5

16 //07 6

17 //07 Raster representation Each color represents a different value of a nominal-scale field denoting land cover class Legend Mixed conifer Douglas fir Oak savannah Grassland Raster Data Sets: Data Landsat TM(99) & ETM+ (00) 7/ 7/ 0/0/99 0/06/00 7

18 //07 Classified Data: Vector Data Used to represent points, lines, and areas All are represented using coordinates One per point Areas as polygons Straight lines between points, connecting back to the start Point locations recorded as coordinates Lines as polylines Straight lines between points 8

19 //07 Representing Data using the Vector Model: General concept The fundamental concept of vector GIS is that all geographic features on the earth s surface (or on a map) can be represented either as: points (no area): trees, sample locations, crime locations, rocks, manhole covers lines (arcs): streets, sidewalks, transmission lines, streams areas (polygons): cities, counties, buildings, states, ponds and lakes, land uses, land covers Which is used in a particular instance depends on scale, among other things: for example Leonard Hall may be a point or polygon Because representation depends on shape, ArcView refers to files containing spatial data as shapefiles. Representing Data using the Vector Model: Point (node): 0 dimension one x,y coordinate pair zero area tree, oil well, label location Line (arc): dimension two (or more) connected x,y coordinates road, stream Polygon : dimensions four or more ordered and connected x,y coordinates first and last x,y pairs are the same encloses an area census tracts, county, lake y= x= Latitude = Y Longitude = X Point: 7, Line: 7, / 8, Polygon: 7, / 8, / 7, / 7, 9

20 //07 Latitude is the Y axis, longitude is the X axis Latitude lines run east west. They are parallel to each other. The further north you go is determined by latitude. And latitude values (Yvalues) range between 90 and +90 degrees Longitude lines run north south. They converge at the poles. And X coordinates are between 80 and +80, which are called longitudes. Attribute data on the right are linked to spatial data by the label ID of map features 0

21 //07 Representing Data using the Vector Model: Data implementation Features in the theme (coverage) have unique identifiers--point ID, polygon ID, arc ID, etc Usually referred to as the Feature ID (FID) Y 5 Common identifiers provide link to: coordinates table (for where) attributes table (for what or when) X Coordinates Table Point ID x y 5 Point ID Crime time robbery 9:0 assault :0 drug 5:00 robbery :0 5 b & e :00 Concepts are those of a relational data base, which is really a prerequisite for the vector model (or need object-oriented computing environment) (Vector) Topology: What is it? Programmed rules in GISs like ArcGIS that establish spatial relationships between features (points, lines, polygons) Spatial Relationships each arc has a beginning and ending node arcs connect to other arcs at nodes connected arcs form polygon boundaries arcs have polygons on their left and right containment Spatial Properties length, directionality of arc connectivity area, perimeter of polygons adjacency or contiguity point or line in polygon

22 //07 The Vector Data Model: Topological vs. Non topological Spatial Data Topological Vector Data contains data regarding the (spatial) relationships between features Ex. ArcGIS coverages, geodatabases Non topological no data regarding spatial relationships is recorded or stored Ex. ArcGIS shapefiles Point (node): 0-dimension single x,y coordinate pair zero area (Example: tree, oil well, label location) The data structure of a point data model (,9) Point List ID X,Y Y (,),9,, (,) (6,) 6, (0,0) X

23 //07 Line (arc): -dimension From Nodes (points) T Nodes (points) x,y coordinate pair(s) depend # of Nodes and vertices zero area (Example: tree, oil well, label location) The data structure of a line data model The data structure of an area (polygon) data model

24 //07 GIS Data Models: Raster vs. Vector Raster data model location is referenced by a grid cell in a rectangular array attribute is represented as a single value for that cell many data comes in this form images from remote sensing (LANDSAT, SPOT, QuickBird) scanned maps elevation data from USGS best for continuous features: elevation temperature soil type land use Vector data model location referenced by x,y,z coordinates, which can be linked to form lines and polygons attributes referenced through unique ID number to tables many data comes in this form DIME and TIGER files from US Census DLG from USGS for streams, roads, etc census data (tabular) best for features with discrete boundaries property lines political boundaries transportation Vector and Raster Comparison and Conversion

25 //07 Do you see a pattern here? 5

26 //07 Review: Representing Geography When representing real world geographic objects in a digital form, there are governing principles:. The representations in a GIS have spatial coordinates. The characteristics of the representations are selective (based on what attributes we wish to represent), and therefore incomplete The world is infinite and the computer is finite. We use models to represent the real world in two ways: As clearly defined, discrete objects with known shapes or boundaries (represented as vector data models) As continuous data that extends over space, that we think of as fields (represented as raster data models) Environmental Systems Research Institute Arc Geographic Information Systems v. 0 Today: Licensing options ArcView ArcEditor ArcInfo GUI description Components of ArcGIS ArcMap ArcCatalog ArcToolbox Setting up your project Data organization / workspace Geodatabases Project files (.mxd) Relative & absolute paths Data Frame Properties 6

27 //07 ArcGIS Desktop license levels ArcGIS Desktop is available in different levels, each with additional functionality The levels are:. ArcView BASIC. ArcEditor STANDARD. ArcInfo ADVANCED ArcView ArcEditor ArcInfo ArcGIS Desktop ArcView With ArcView, you can Author maps and interact with your data by generating reports and charts and printing and embedding your maps in other documents and applications ArcInfo Use map templates to create consistent style in your maps ArcEditor Build process models, scripts, and workflows to visualize and analyze your data ArcView Read, import, and manage more than 70 different data types and formats including demographics, facilities, CAD drawings, imagery, Web services, multimedia, and metadata Print, publish, and share GIS data Use tools such as Find, Identify, Measure, and Hyperlink 7

28 //07 ArcGIS Desktop ArcEditor With ArcEditor, you can Have multiple users to simultaneously modify and edit data Build and maintain spatial relationships between features using topology rules and a process called validation Support multiple workflows, manage work order processing, and implement QA procedures for validating edits ArcView ArcEditor ArcInfo Monitor the database over time and evaluate what if scenarios Perform raster to vector conversion and create data from scanned maps ArcGIS Desktop ArcInfo With ArcInfo, you can Perform advanced GIS data analysis and modeling Use tools designed for overlay analysis, proximity analysis, surface analysis, and raster processing and conversion Publish and convert data in many formats Create and manage personal geodatabases, multiuser geodatabases, and feature datasets ArcView ArcEditor ArcInfo Use high end cartography tools to generate professional quality, publication ready maps Design customized symbols and place sophisticated annotation and labels on your maps 8

29 //07 ArcGIS How is it Structured? Mapfile What is it? Document that Data Frame What is it? Organizational entities Data Layer What is it? Spatial data sets ArcGIS Mapfile 9

30 //07 ArcGIS Mapfile How do mapfiles work? They contain pointers to spatial and non spatial data (not the data itself) You save them as.mxd files and as long as they have access to the base data, you are in good shape Example H:\introgis\streams.shp or E:\assignment\streams.shp Mapfile Example 0

31 //07 ArcGIS: Data Frames and Data Layers What is the Difference? Data Frames Represent some domain in space that can have some properties (that you can assign) Scale, coordinate system, labeling, etc. Contain data layers that occur within this domain that are in the same coordinate space ArcGIS: Data Frames and Data Layers What is the Difference?

32 //07 ArcGIS: Data Frames and Data Layers What is the Difference? Data layers are graphic representations of spatial data layers (in a map file) They are accessed by adding data to a mapfile the data will then appear in the table of contents Data layers also have properties that are separate and distinct from those of data frames sometimes this is hard to keep track of but we ll manage ArcGIS Data Layers

33 //07 Organization of your data/workspace Workspaces are the directories, databases, and file folders on disk that hold numerous datasets, including geodatabases, as well as external datasets in many file formats for example, folders containing shapefiles, JPEG images, DXF CAD files, dbase tables, or Excel spreadsheets You can create and manage your workspaces in ArcCatalog as well as make connections to other workspaces Your workspaces may consist of a single file folder containing many datasets and other related documents that are organized around themes or projects Organization of your data/workspace You can organize projects by layer type such as workspaces for roads, water, parcels, administrative boundaries, and so forth For example, the Shopping Mall Project workspace organizes datasets in folders by the theme of the data

34 //07 Organization of your data/workspace In other situations, you may want to organize workspaces around a project such as a road development project or new power plant project You can also organize workspaces within workspaces The New Power Plant workspace below contains sub workspaces for each element of the major development project Proper organization of your data and workspace results in a logical catalog tree

35 //07 Graphical User Interface (GUI) / ArcMap Display Interface Setting up your Project File (.mxd) File Map Document Proper es Go to Pathnames and click Store relative pathnames to data sources 5

36 //07 Setting up your Project File (.mxd) First thing to do is to tell.mxd/project file which coordinate system, projection, and datum to use in the data frame Go to the View pull down menu and navigate to Data Frame Properties In the Data Frame Properties click the Coordinate System tab Now what??? 6

37 //07 Querying the database, Boolean Operators, AND Topological OVERLAY FUNCTIONS IN gis (or, Geoprocessing ) Multiple Layer Operations How can we conceptualize multiple layer operations? Kinds: Those that do not change the geometry of spatial data Those that do change the geometry of spatial data, necessitating changes and updates to (vector) shapes 7

38 //07 Multiple Layer Operations Multiple layer operations that do not change the geometry of spatial data Select by Location Spatial relationship is specified, spatial features are selected, but spatial data is not geometrically altered Spatial Join Data is appended from a source spatial data table to a destination spatial data table based on common location, again spatial data is not altered Select by Location Relationships between layers (that you can specify): Intersect within distance of Completely contain Are completely within Have their center in Touch the boundary of 8

39 //07 The GIS Data Model: Geographic Integration of Information Data is organized in layers, coverages or themes (synonymous 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 9

40 //07 Queries Aspatial Queries Querying the attribute data using commands Spatial Queries Querying the attribute data using the geography of other data Aspatial Query in ArcGIS Select by Attributes Build the SQL statement by simply clicking and doubleclicking Check you SQL statement with the Verify button Click Apply then OK 0

41 //07 Query asking a question of the attribute data Standard Query Language (SQL) is used to query the data There are basic statements used to get information from (or more) datasets AND if you are desiring the subset of each dataset that is true of both datasets OR if you are desiring the subset of each dataset that is true of either one or both datasets NOT if you are desiring the subset of one dataset that is only true of one dataset OR, BUT NOT BOTH (XOR) if you are seeking the subset of data that is true of one and another dataset, but not both datasets Boolean Operators: AND A AND B = True if Both A B

42 //07 Boolean Operators: AND A AND B = True if Both Boolean Operators: OR A OR B = True if one or other A A B

43 //07 Boolean Operators: OR A OR B = True if one or other A Boolean Operators: NOT A NOT B = True if Neither A B

44 //07 Boolean Operators: NOT A NOT B = True if Neither A Boolean Operators: A XOR B A OR B, but not both (XOR) A B

45 //07 Boolean Operators: A XOR B A OR B, but not both (XOR) Polygon on Polygon Vector Overlay Operations INPUT LAYER INPUT LAYER OUTPUT LAYER CLIP SELECT (NOT) Cuts out a piece of layer using layer as cookie cutter [ AND ] Erases (deletes) part of layer using layer [ NOT ] SPLIT Splits into many layers based on XOR Layer or, but not both [ XOR ] UNION INTERSECT Overlays polygons and keeps all of both [ OR ] Overlays but keeps only portions of layer that fall within layer [ AND ] 5

46 //07 Point in Polygon Vector Overlay Operations Also called the even-odd rule algorithm Line in Polygon Vector Overlay Operations INPUT LAYER INPUT LAYER INPUT LAYER INPUT LAYER Minimum Bounding Box Minimum Bounding Box OUTPU T LAYER Even or Zero intersects to each side = NO OUTPU T LAYER Even or Zero intersects to each side = NO Odd intersects to each side = YES Odd intersects to each side = YES Multiple Layer Operations Types of geoprocessing operations Dissolve Append (spatial join) Clip Intersect Union Buffer 6

47 //07 Dissolve Operation Change in geometry based on common attribute values Clip Operation The Clip feature is used as a cookie cutter 7

48 //07 Buffer Operation Proximity is measured from target features Union 8

49 //07 Union Union and Intersect 9

50 //07 Union is an AND operation that produces a rd output dataset A C B Data Capture Primary Sources Secondary Sources Vector Raster 50

51 //07 Overview Introduction Primary data capture Secondary data capture Data transfer Capturing attribute data Managing a data capture project Data Collection One of most expensive GIS activities Many diverse sources Two broad types of collection Data capture (direct collection) Data transfer Two broad capture methods Primary (direct measurement) Secondary (indirect derivation) 5

52 //07 Data Collection Techniques Primary Secondary Raster Digital remote sensing images Digital aerial photographs Scanned maps DEMs from maps Vector GPS measurements Survey measurements Topographic surveys Toponymy data sets from atlases Stages in Data Collection Projects Planning Evaluation Preparation Editing / Improvement Digitizing / Transfer 5

53 //07 Primary Data Capture Capture specifically for GISci use Raster remote sensing e.g. SPOT and IKONOS satellites and aerial photography Passive and active sensors Resolution is key consideration Spatial Temporal Spectral Vector Primary Data Capture Surveying Locations of objects determines by angle and distance measurements from known locations Uses expensive field equipment and crews Can also be performed on an airborne platform LiDAR, Radar, etc. Most accurate method for large scale, small areas GPS Collection of satellites used to fix locations on Earth s surface Differential GPS used to improve accuracy 5

54 //07 Total Station 5

55 //07 55

56 //07 Secondary Geographic Data Capture Data collected for other purposes can be converted for use in GIS Raster conversion Scanning of maps, aerial photographs, documents, etc Important scanning parameters are spatial and spectral (bit depth) resolution Vector Secondary Data Capture Collection of vector objects from maps, photographs, plans, etc. Digitizing Manual (table) Heads-up and vectorization Photogrammetry the science and technology of making measurements from photographs, etc. COGO Coordinate Geometry 56

57 //07 Scanner The most prevalent way To capture nondigital raster data Scanners are: Flatbed Scrolling Drum Vector Over Raster Heads-up data capture means the by-hand digitization of objects in vector format from a raster data source i.e., tracing by hand- 57

58 //07 Digitizer Types of human errors in digitizing: (A) undershoots and overshoots (B) invalid polygons (C) sliver polygons 58

59 //07 Error induced by data cleaning Mismatches of adjacent spatial data sources that require rubber sheeting Rubber-sheeting is a procedure for adjusting the coordinates of all the data points in a dataset that allow a more accurate match between known locations and a few data points within a dataset Rubber-sheeting preserves the Interconnectivity between points and objects through stretching, or reorienting their interconnecting lines Object edges don t align Object edges align after rubbersheeting, but sometimes it causes problems elsewhere 59