Essential Spatial Data Infrastructure (SDI) Interview Preparation Guide

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Conflation is formally defined as the procedure of reconciling the positions of corresponding features in different data layers. More commonly this is referred to as sliver removal. Often two layers that contain the same feature, e.g. soils and forest stands both with a specific lake, do not have exactly the same boundaries for that feature, e.g. the lake. This may be caused by a lack of coordination or data prioritization during digitizing or by a number of different manipulation and analysis techniques. When the two layers are combined, e.g. normally in polygon overlay, they will not match precisely and small sliver polygons will be created. Conflation is concerned with the process for removing these slivers and reconciling the common boundary.

Edge matching is simply the procedure to adjust the position of features that extend across typical map sheet boundaries. Theoretically data from adjacent map sheets should meet precisely at map edges. However, in practice this rarely occurs. Misalignment of features can be caused by several factors including digitizing error, paper shrinkage of source maps, and errors in the original mapping. Edge matching always requires some interactive editing. Accordingly, GIS software differs considerably in the degree of automation provided.

Interactive graphic editing functions involve the addition, deletion, moving, and changing of the geographic position of features. Editing should be possible at any time. Most graphic editing occurs during the data compilation phase of any project. Remember typically 60 to 70 % of the time required to complete any project involves data compilation. Accordingly, the level of sophistication and ease of use of this capability is vitally important and should be rated highly by those evaluating GIS software. Many of the editing that is undertaken involves the cleaning up of topological errors identified earlier. The capability to snap to existing elements, e.g. nodes and arcs, is critical.

Map Projection Transformations functionality concerns the transformation of data in geographic coordinates for an existing map projection to another map projection. Most GIS software requires that data layers must be in the same map projection for analysis. Accordingly, if data is acquired in a different projection than the other data layers it must be transformed. Typically 20 or more different map projections are supported in a GIS software offering.

Geometric transformations function is concerned with the registering of a data layer to a common coordinate scheme. This usually involves registering selected data layers to a standard data layer already registered. The term rubber sheeting is often used to describe this function. Rubber sheeting involves stretching one data layer to meet another based on predefined control points of known locations. Two other functions may be categorized under geometric transformations. These involve warping a data layer stored in one data model, either raster or vector, to another data layer stored in the opposite data model. For example, often classified satellite imagery may require warping to fit an existing forest inventory layer, or a poor quality vector layer may require warping to match a more accurate raster layer.

Coordinate thinning involves the weeding or reduction of coordinate pairs, e.g. X and Y, from arcs. This function is often required when data has been captured with too many vertices for the linear features. This can result in redundant data and large data volumes. The weeding of coordinates is required to reduce this redundancy.

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False

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1. DNF
2. GML
3. HTML
4. SDTS
5. DNF

GML

1. 25
2. 15
3. 30
4. 20
5. 24

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1. IKONOS
2. GPESKI
3. GLASNOST
4. GLONASS

GLONASS

1. Geographical Point Software
2. Global Point Selection
3. Global Positioning System
4. Geographical Position System

Global Positioning System

1. the smallest feature that can be mapped or measured
2. the smallest unit or measurement into which data can be disaggregated
3. the overall quality of a data set
4. the size of the smallest recording unit
5. the accuracy and precision of the data

The size of the smallest recording unit
the smallest feature that can be mapped or measured

1. Interval
2. Ordinal
3. Ratio
4. Nominal

Ratio

1. Postal area
2. Postal district
3. Postal sector
4. Unit postcode

Postal sector

1. Universal Transverse Mercator
2. Lambert Conformal Conic
3. Alber's Equal Area
4. Interrupted Goode Homolosine

Universal Transverse Mercator

1. Azimuthal
2. Cylindrical
3. Geographic
4. Conic

Geographic

1. Annotation
2. Scale bar or ratio
3. Map features (points, lines, areas, surfaces)
4. Projection information
5. Pictures and anecdotal evidence

Projection information
Annotation
Map features (points, lines, areas, surfaces).
Scale bar or ratio.

1. The lines on a map representing north-south and east-west directions
2. The ratio of a distance on a map to the corresponding distance on the ground
3. An indication of how big an object represented on the map is on the ground
4. The order of magnitude or level of generalization at which phenomena exist or are perceived or observed
5. A conversion factor used to transform map projections.

The order of magnitude or level of generalization at which phenomena exist or are perceived or observed
An indication of how big an object represented on the map is on the ground
The ratio of a distance on a map to the corresponding distance on the ground