Lecture 4: GIS Data Input Methods and Techniques. GE 118: INTRODUCTION TO GIS Engr. Meriam M. Santillan Caraga State University

Transcription

1 Lecture 4: GIS Data Input Methods and Techniques GE 118: INTRODUCTION TO GIS Engr. Meriam M. Santillan Caraga State University

2 Geographic Data in GIS Can be obtained from various sources in different formats Can be inputted into a GIS using different methods

3 Some Sources of Data for GIS Maps Census and Survey Data Aerial Photographs Satellite Images Ground/Land Survey Data GPS Data

4 Map

5 Census and Survey Data May be spatial in character if each item Gender Quickstat has a spatial reference, allowing its location on the Earth to be identified Usually in tabular format (An Update REFof NSO's Most Requested Sexdisaggregated Statistics) INDIC ERE NCE as of 1st BotQuarter DATA 2005 ATOR PERI h Pe Pe Nu NuMale Nu Female OD Sex rc rc Year mbe Total DEMOGRAPHY (Source: es mb mb 76,5 38,5 Census enof Population 37,9 en r er 0-9,66 4,95 50 er 4,71 49 Popul and Housing) May 04,0 24,2 t 5-9,69 4, ,8 t 4, ,50 1, ,94 4, ,57 4, ,78 2, ,01 4, ,76.8 years ation , ,61 1, ,06 3, ,41.8 years 1 3 3, ,29 7, ,07 3, ,46.3 years 4 7 3, ,40 2, ,54 2, ,88.9 years 8 0 2, ,08 3, ,90 2, ,47.2 years 3 8 2, ,29 4, ,16 2, ,77.7 years 9 6 2, ,02 6, ,33 1, ,20.4 years 4 2 1, ,49 0, ,62 1, ,18.1 years 3 1 1, ,05 6, , ,34.1 years , ,63 943, 8, , 3,68.0 years , years 65-1, , , , years , , , 8, years 0 361, , years , 218, , years 490, 195, , 60 and years over Examples: population census, employment data, agricultural census data, marketing data

6 Aerial Photographs First method of remote sensing A snapshot of the Earth at a particular instant in time May be used as a background or base map for other data in a GIS Provides spatial context and aids in interpretation Versatile, relatively inexpensive and detailed source of data for GIS Disadvantage: not spatially referenced; should be spatially referenced using other data (ex. Maps, GPS data, Land survey data)

7 Important Characteristics of Aerial Photos for GIS (Curran 1989) Wide availability Low cost compared with other remotely sensed images Wide area views Time-freezing ability High spectral and spatial resolution Three-dimensional perspective

8 Satellite Images Collected by sensors on board a satellite, which are then relayed to ground stations and then computer-processed to produce images Can be used to detect features not readily apparent to the naked eye (ex. Sedimentation, moisture content, ground temperature variations) Processing is needed for data reduction, georeferencing, enhancing, and data integration Examples: Landsat, SPOT, Ikonos, Quickbird, AVHRR

9 Advantages of Satellite Images Easy to transfer/transport -- always available in digital form Specific features can be highlighted by manipulating the displayed wavebands Repeated converage of the Earth important for temporal analysis and continuous monitoring Large coverage area useful for regional or national mapping applications Low cost compared with other data sources Ability to acquire current/timely images Accurate and complete Uniform standards across areas

10 Ground/Land Surveying Data Using tapes, transits, theodolites, total stations, etc. Used to collect field data such as coordinates, elevations, and distances Data collected are in analog format (written down in paper) which still need to be transformed to digital format for use in GIS

11 GPS (Global Positioning Systems) Data Relatively new technique of field data collection Radio waves/signals from GPS satellites are used to pinpoint location Originally designed for real-time navigation Can store collected coordinates and associated attribute information, which may be downloaded directly into a GIS database Accuracy ranges from 100 meters to a few centimeters

12 Categories of Geographic Data Acquisition Primary collected through first-hand observation Secondary data collected by another individual or organization; most are published data

13 Primary Raster and Vector Data Raster Data satellite images scanned aerial photographs Vector Data Land survey points GPS observation data

14 Methods of Data Acquisition 1. Raster Data Acquisition Scanning Photogrammetry Remote sensing 2. Vector Data Acquisition Manual digitizing Computer-assisted digitizing Field surveying GPS surveying 3. Attribute Data Acquisition Keyboard entry

15 Scanning Most commonly used method when raster data is required Accuracy depends on the scanner quality (resolution), quality of the image processing software used to process the scanned data, and quality/complexity of source document

16 Manual Digitizing Most common method of encoding geographic features from paper maps to vector GIS Used when topology of features is important May be used for extraction of spatial features from maps and aerial photos Uses a Table Digitizer which is linked to a computer

17 Manual Digitizing One of the main sources of positional error in GIS Accuracy depends on scale/resolution of source map and quality of equipment and software used Errors are usually due to: Incorrect registration of map features on the digitizer table ( hand-wobble ) Lack of experience of the digitizer Time-consuming and tedious, especially for a large amount of data

18 Manual Digitizing Procedures 1. Preparation 2. Creation of a digitizing template 3. Map digitizing 4. Post digitizing data processing

19 Preparation Getting the map and digitizer ready Check quality of map/s to be digitized, identifying control points for georeferencing, checking/calibrating digitizer Establish specifications of feature codes, line types, and approaches to data capture, according to acceptable data standards

20 Creation of a Digitizing Template Digitizing template contains tic marks, neat lines, and graphical elements common to all layers (ex. Boundaries and water bodies) Enables multiple layers to be registered perfectly with each other Minimizes amount of work

21 Map Digitizing Begins by registering map mounted on the digitizing table to the digital map on the computer screen Not necessary to follow a particular sequence for digitizing graphical elements No need to digitize points at which lines intersect Intersecting lines will be automatically broken down into line segments during topology building

22 Using a Manual Digitizing Table 1. Registration map is fixed firmly on the table; five or more control points are identified on the map, their coordinates are noted, and they are digitized 2. Digitizing point, line, and polygon features 3. Adding attribute information to be linked to the digitized features

23 Post Digitizing Data Processing Checking for errors/omissions done in the digitizing process When errors/omissions are detected, it is sometimes necessary to go back to the digitizing process Map must remain in its original position to retain the registration previously made

24 Modes for Manual Digitizing 1. Point Mode A start and end node is recorded to define a line Points between the start and end nodes are recorded for more complex lines/curves More popular because it allows more operator control Results in a smaller data file 2. Stream Mode Requires more skill than point mode digitizing Generates larger files compared to point mode The digitizer is set to record points according to a predetermined time interval or distance interval Generation of points begins upon the recording of the start node and terminates once the end node is recorded Number of points is determined by the speed at which the mouse cursor is moved over a line/feature

25 Computer-Assisted Digitizing Heads-up or On-screen digitizing May be automatic or semi-automatic Used instead of manual digitizing when a large number of complex maps is to be digitized in a short period of time Popularity has grown considerably due to improved hardware design, software capabilities, and data-compression techniques Very efficient and time-saving Proprietary hardware and software are required very expensive

26 Semi-Automatic Digitizing Process 1. Scanning map to the computer (raster format) 2. Operator moves cursor to a position at the start of a line/contour and activates the software 3. Software automatically converts the raster data to vector by following the pixels until it encounters a break 4. Operator moves the cursor to another position

27 Keyboard Entry/Keycoding Used for entering tabular/attribute data, which are commonly only available in paper form, into the GIS database Examples: vegetation classes, polygon identifiers, soil types, topographic detail, etc. May involve numeric, alphanumeric, or logical data May be done through keyboard entry or text scanning (OCR) Manageable for a small amount of data Disadvantages: Not feasible for a large amount of data Prone to typographical errors

28 Electronic Data Transfer Used when data is already in digital form Usually followed by data conversion, particularly when the transferred data is in a different format than what is required

29 Data Editing Errors and inaccuracies during data acquisition and input translate into errors in the GIS Before further analyses are made, these errors should be corrected to prevent the errors from propagating to generated information

30 Common Errors in Geographic Data Error Missing entities Duplicate entities Mislocated entities Missing labels Description Missing points, lines or boundary segments Features that have been digitized twice Features digitized in the wrong place Unidentified polygons

31 Common Errors in Geographic Data Error Duplicate labels Digitizing artifacts Noise Description Two or more identification labels for a single polygon Undershoots, overshoots, misplaced nodes, loops and spikes Irrelevant data entered during digitizing, scanning or data transfer

32 Raster Data Editing Refers to correcting specific contents of raster images To produce a clean raster image which will meet data-processing standards Can better be done using digital image processing packages, instead of GIS packages

33 Raster Data Editing Functions Filling holes and gaps Edge smoothing and boundary simplification remove or fill single-pixel irregularities along line edges Deskewing rotate the image by a small angle to align with axis to be used Speckle removal or filtering remove noise or random pixels

34 Raster Data Editing Functions Erase or delete manually removing unwanted pixels/speckles Thinning reduce the width of linear features to a single cell Clipping/Subsetting cut/remove a specific portion of the image to have a new, smaller image Drawing and Rasterization add vector graphics or text to a raster image and convert them to a raster form

35 Common Raster Editing Functions for GIS

36 Vector Data Editing Post digitizing process designed to ensure integrity of the data before using them in the GIS

37 Steps in Vector Data Editing 1. Setting the editing environment 2. Topology building 3. Data editing and error correction 4. Joining adjacent layers

38 Setting the Editing Environment Defining standards for editing, such as tolerance Edit tolerance cursor is able to select a point when it is clicked within the defined tolerance Weed tolerance digitized arcs shorter than weed tolerance are filtered/removed Grain tolerance digitized points too close to one another are removed

39 Topology Building Most important process in graphical data editing A repetitive process a layer can only have a complete and final topology building when there are no more errors Builds the topological structure and relationships for the graphical elements on a layer By assigning an internal identifier to each identified graphical element and creating an associated attribute table Important for error identification and automating corrections Errors are highlighted by the topology building commands and may be corrected automatically

40 Data Editing and Error Correction Includes selecting, deleting, copying and adding graphical elements, as well as changing their properties Important in topology building Error-prone and time-consuming process

41 Joining Adjacent Layers Needed when there are multiple map sheets to be used Ensures that all layers form a continuous geographic database when joined together

42 Attribute Data Editing Attribute errors most difficult to detect since the GIS doesn t know which attributes are correct and incorrect Usually involves missing attribute values, incorrect attribute values, or misplaced attribute values Generally done manually

43 Data Conversion After input and editing of individual datasets, it is usually necessary to process the data before integrating them all into a single GIS Process of converting data on one form to a more useful format for the specific GIS application One of the most tedious, time-consuming, and error-prone processes in GIS

44 Digital Data Conversion Process 1. Acquisition digitizing existing maps, purchasing ready-made products, collecting new data using field surveying, GPS, photogrammetry, or remote sensing 2. Editing cleaning acquired digital data to meet certain specifications 3. Formatting/Translating converting digital data into the specific physical database format of the GIS 4. Linking associating attribute data with the graphical data

45 Raster to Vector Conversion Vectorization Converting scanned raster images to vector features (point, line, or polygons) Results are visually problematic most of the time

46 Vectorization Process 1. Raster Line-Thinning 2. Vector Line Extraction 3. Topological Reconstruction 4. Line Smoothing

47 Raster Line Thinning skeletonizing Process of reducing raster linear features into unit width

48 Vector Line Extraction 4-connect reconstruction -- search the 4 surrounding cells and join center points if present 8-connect reconstruction -- search the 8 surrounding cells and join center points if present 8-connect w/ redundancy elimination -- draw diagonal from 8- cell search only if not already connected by orthogonal from 4-cell search

49 Topological Reconstruction involves the creation of nodes at line junctions, construction of arcs, and polygon definition

50 Line Smoothing Employed to make the resulting vectors more visually appealing during raster to vector conversion, the results are usually jagged/crooked (especially for diagonal lines)

51 Vectorization Methods 1. Manual user selects and picks out features to be converted 2. Automatic entire raster image is converted by the computer software without user intervention 3. Semi-automatic combination of manual point picking and computerized line tracing produces best results

52 Post Scanning Processing 1. Raster to vector conversion 2. Raster text conversion 3. Raster symbol conversion 4. Graphical data editing 5. Attribute data tagging

53 Raster to Vector Conversion Changing raster images into vector graphics May be done manually, automatically, or semi-automatically Major limiting factor is the map quality

54 Raster Text Conversion Characters in the raster image are converted to alphanumeric data using character recognition (ex. OCR) Involves a large amount of manual verification of the results and correction of errors

55 Raster Symbol Conversion Cartographic symbols in the raster image are converted to alphanumeric codes Largely a manual task Automated symbol recognition is a much more difficult task than character recognition No available standards in the form, size, and codes of cartographic symbolss

56 Graphical Data Editing Cleaning graphics by removing data conversion errors

57 Attribute Data Tagging Adding attribute data (e.g., feature identifiers, feature codes, and contour labels) to the graphical data

58 Vector to Raster Conversion Rasterization process of converting vector data (points, lines and polygons) into raster data (series of cells each with a discrete value) Produces visually satisfactory results May be problematic in terms of the attributes assigned to pixels Most evident along edges/boundaries (partial cells)

59 Rasterization Process 1. Superimpose a grid (cell values initially zero) on the vector map 2. Code/assign a value to the cells based on the contained feature (whether point, line, or polygon) 3. Fill the interior of the polygon outline with the corresponding polygon value assigned to the boundary

60 Rasterization of Lines

61 Data Integration Combining data from various sources and in various formats to be able to extract more/better information

62 Two types of spatial data integration: 1. Horizontal Integration tiling ; merging of adjacent data sets 2. Vertical Integration map overlay; stacking of data sets/layers

63 Map Overlay

64 Examples of Adjustments Required for Data Integration Mathematical Transformations translation, scaling, rotation, or skewing Rectification rearrangement of the location of objects to correspond to a specific (geodetic) reference system Registration rearrangement of the location of objects of one set so they correspond with those of another, without referring to a specific reference system Rubber Sheeting data set/layer is differentially stretched so that tic points on the layer are moved to approximate the location of the corresponding ground control points or corresponding tic points in another layer Edge Matching employed to properly connect or line-up corresponding features in adjacent map sheets to create a seamless model

65 translatio n differentia l scaling rotation skewing ground control Mathematical Transformations map locations GIS file Rubber Sheeting POEC 1359 Introduction to GIS by Ron Briggs

66 Thank you!