GIS Data Accuracy and Precision Standards Explanation

Data Storage and Editing (17/MAY/2010) Dr. Ahmad BinTouq E-mail: abintouq@uaeu.ac.ae URL: http://faculty.uaeu.ac.ae/~abintouq GEO 321: GIS 1

Overview Accuracy vs. precision Error propagation and cascading of error in GIS Types of errors in vector GIS Types of errors in attribute data The concept of topology - what is it, what types of Relationships are stored for point, line, and poly features, why do we need it in GIS?

Introduction • Any analysis performs must be based on good data, correctly organized and in the proper format. • http://gif.berkeley.edu/documents/AccuracyVsPrecision.pdf • http://www.colorado.edu/geography/gcraft/notes/error/error.html

Accuracy • The degree to which information on a map or in a digital database matches true or accepted values • An issue pertaining to the quality of data and the number of errors contained in a data set or map • It is possible to consider horizontal and vertical accuracy with respect to geographic position • Attribute accuracy - conceptual, and logical accuracy • Level of accuracy required for particular applications varies greatly. Highly accurate data can be very difficult and costly to produce and compile • e.g., mapping standards employed by the United States Geological Survey (USGS): "requirements for meeting horizontal accuracy as 90 per cent of all measurable points must be within 1/30th of an inch for maps at a scale of 1:20,000 or larger, and 1/50th of an inch for maps at scales smaller than 1:20,000."

Accuracy Standards for Various Scale Maps • 1:1,200 ± 3.33 feet • 1:2,400 ± 6.67 feet • 1:4,800 ± 13.33 feet • 1:10,000 ± 27.78 feet • 1:12,000 ± 33.33 feet • 1:24,000 ± 40.00 feet • 1:63,360 ± 105.60 feet • 1:100,000 ± 166.67 feet

Precision • Refers to the level of measurement and exactness of description in a GIS database (e.g., number of decimal places) • Precise locational data may measure position to a fraction of a unit e.g. to the millimeter • Precise attribute information may specify the characteristics of features in great detail • Important to realize, however, that precise data--no matter how carefully measured--may be inaccurate • Level of precision required for particular applications varies greatly. Engineering projects such as road construction require very precise information measured to the millimeter. Demographic analyses of marketing or electoral trends can often make do with less, say to the closest zip code or precinct boundary

Why be concerned about error? - The Problems of Propagation and Cascading • Discussion focused to this point on errors that may be present in single sets of data • ”Doing" GIS usually involves comparisons of many sets of data. If errors exist in one or all of the data layers, the solution to the GIS problem generated from them may itself be erroneous • Inaccuracy, imprecision, and error may be compounded in GIS that employ many data sources

DIGITIZATION-continue Tic 3 2 1 4 Geographic features

Error Propagation and Cascading • Occurs when one error leads to another • Means that erroneous, imprecise, and inaccurate information will skew a GIS solution when information is combined • DeMers - "error prone data will lead to error prone analysis" • e.g., if a map registration point has been mis-digitized in one coverage and is then used to register a second coverage • Result = the second coverage will propagate the first mistake • In this way, a single error may lead to others and spread until it corrupts data throughout the entire GIS project

Entity Errors: Vector • Six categories identified by DeMers/ESRI • All entities that should have been entered are present • No extra entities have been entered • Entities are in the right place and • Entities are in the correct shape and size • Entities that are supposed to be connected to each other are all polygons have a single label point which identifies them • All entities are within the outside boundary identified

Nodes and Vertices • Specific types of entity errors in vector GIS • can involve points, lines, polygons, nodes, vertices, label points • nodes - denote ends of lines or point where polygon closes on itself • vertices - denote change or direction within a line • points -> lines -> polys • Nodes are used to show specific topological relationships, e.g.: • intersection of roads or streams • intersection between stream and lake • node errors include pseudo nodes and dangle nodes

Pseudo nodes • Occur where lines connect with itself or other line • A line connects with itself to form a polygon, a.k.a. island pseudo node (fig. 6.1a, p. 161) • Also occur where two lines intersect (rather than crossing) (fig. 6.1b) • Pseudo nodes are not necessarily errors, but indicate the potential location of errors • e.g., pseudo node in the middle of a line representing a node can be used to separate road into two different speed limit zones • Others may indicate error, (pushed wrong button when digitizing, placed cursor at wrong location)

Digitization errors- Pseudo node (Diamond) Pseudo node connects two and only two arcs Pseudo node Not representing a serious errors Pseudo node Error

Dangle nodes • A single node connected to a single line • Again, not necessarily and error, but may be • Can result from three possible mistakes: (fig. 6.2, p. 162) • Failure to close a polygon • Undershoot • Overshoot • Sometimes result from incorrect placement, sometimes from fuzzy tolerance and snapping distance • One method of general error detection is comparing digitized to original document at equivalent scales good for broad scale obvious errors, not for finer scale errors

DIGITIZATION • For linear features such as rivers, roads, railways it is important to digitize each section separately (start node and end node at a specified section) or use Route latter Node

Digitization errors - Dangle Error(square) Dangle error Road Overshoot Closed polygon Undershoot Natural feature Acceptable dangle node e.g. end of roads

Label point and sliver errors • Polygon label point errors ( points -> lines -> polys) • Label point is used to associate a polygon with attributes • If label point is missing, or there are more than one, indicates error e.g., fig. 6.4, p. 163 • Sliver polygon errors • Commonly result from incorrect practice of double digitizing • Can also result from overlay or merging operations which join coverages from different sources • Can be removed manually or by dissolving polygons less than a certain area and/comparing intended number of polys with actual number (Fig. 6.5, p.164)

Digitization errors-Labels • Missing labels or too many labels too many labels missing labels

Sliver polygon errors

Topology • Topology is the process of projecting complex surfaces to a simple ones • Topology is a procedure for explicitly defining spatial relationships connecting adjacent features (e.g., arcs, nodes, polygons, and points). • Different types of spatial relationships are expressed as lists of features e.g. • An area is defined by the arcs comprising its border • An arc is defined by set of points (X,Y)

Topology-Main Concepts • The three major topological concepts are: • Connectivity: Arcs connected to each other at nodes • Contiguity/Adjacency: Arcs have direction and left and right sides • Area Definition:: Arcs connected to surround an area define a polygon (area)

Spatial Relationships(Topology) Area Definition Connectivity Adjacency

PolygonTopology

Advantages of Topology Check for digitization errors (overshoot, undershoot, unclosed polygon, missing labels, too many labels) Store data more efficiently (eliminate data redundancy-normalization) Make spatial analysis more faster

Topology • Topological data structures dominate GIS software. • Topology allows automated error detection and elimination. • Rarely are maps topologically clean when digitized or imported. • A GIS has to be able to build topology from unconnected arcs. • Nodes that are close together are snapped. • Slivers due to double digitizing and overlay are eliminated.

Attribute Errors: Raster and Vector • Attribute errors generally more difficult to detect • Types include: • Missing attributes perhaps only kind of attribute error traceable without comparison to source material e.g., plot all polygons and color them according to a certain attribute, if color is missing, attribute is missing • Incorrect attribute values or text more difficult to detect one method is to plot all polygons and color them according to a certain attribute, if only one polygon has a certain attribute and there should be other, it may stick out, in general, involves direct comparison with source material)

Dealing With Projection Changes • Often times, regardless of input method, separate GIS data input for a project will be based on different projection systems • Necessary to transform all data to common system before use in integrated modeling • examples in ArcMAP • Joining Adjacent Coverages: Edge Matching (Union) • Joining two adjacent coverages (usually of the same theme) together to produce a single data set that covers a broader region edge matching also done in raster systems

Conflation and Rubber Sheeting • Conflation and Rubber Sheeting: Refers to the registration (georeferencing) of two maps (vector or raster) in a non-linear way (Ovelay two maps) • Used to make maps of different sources spatially correspond with one another. Most often used in raster data using ground control points (GCPs). Conflation and rubber sheeting are synonymous terms according to DeMers (Figure 6.1, p. 174) • The need to geo-reference internal objects themselves not just the map corners (Rubber Sheeting) • Templating: " cookie cutting" • If you have multiple coverage of different extents, the template is used to "cookie cut" them all to the same extent

Exercise • Error propagation and cascading of error in GIS • Types of errors in vector GIS • Types of errors in attribute data • The concept of topology - what is it, what types of Relationships are stored for point, line, and poly features, why do we need it in GIS?

GIS Data Accuracy and Precision Standards Explanation