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18-Geom-A7 Geospatial Information Systems · May 2017

Question 2 of 15: Raster versus vector data — advantages and limitations

Nivaar worked solution (AI-drafted; not reviewed by a licensed engineer)

Notes on this paper

National Exams — May 2017 — 04-Geom-A7 Geospatial Information Systems. Closed-book; any non-communicating calculator permitted. Format: fifteen questions of varied value totalling 100 marks; fifteen questions constitute a complete paper and all fifteen are solved in full below. Most answers are required in essay form. Datum and coordinate conventions follow the Canadian spatial reference framework — NAD83(CSRS) horizontally and CGVD2013 vertically.

Reference texts: P. A. Longley, M. F. Goodchild, D. J. Maguire & D. W. Rhind, Geographic Information Systems and Science (4th ed., Wiley, 2015); P. Bolstad, GIS Fundamentals: A First Text on Geographic Information Systems (6th ed., XanEdu, 2019); P. A. Burrough, R. A. McDonnell & C. D. Lloyd, Principles of Geographical Information Systems (3rd ed., Oxford, 2015); M. Worboys & M. Duckham, GIS: A Computing Perspective (2nd ed., CRC, 2004); H. Samet, The Design and Analysis of Spatial Data Structures (Addison-Wesley, 1990); ISO 19115 Geographic information — Metadata.

Question 2: Raster versus vector data — advantages and limitations (10 marks)

Question text not reproduced: the examination questions are © Engineers and Geoscientists BC. Open the official past paper (linked at the top of this page) to read the question, then follow the worked solution below.

The two models represent geographic space in fundamentally different ways: vector stores discrete features as points, lines and polygons built from explicit coordinates (with topology), while raster stores space as a regular grid of cells, each holding one value, with location implicit from the row/column index and the grid origin and cell size.

VectorRasterpolygon (nodes + arcs)
Figure — the same area feature as a vector polygon (exact boundary from nodes and arcs) and as a raster grid (feature approximated by cells; boundary fidelity set by cell size).
AspectVectorRaster
Data model / structureDiscrete points/lines/polygons with explicit coordinates and topology; complex structure.Regular cell matrix; simple, uniform structure; location implicit.
Collection & storageDigitizing, survey/GNSS, COGO; compact for discrete features.Scanning, imagery, DEMs; large files (every cell stored), but compressible (RLE, quad-tree).
Attribute handlingRich, multiple attributes per feature via linked tables.Normally one value per cell; multiple themes need multiple grids.
Processing & analysisPrecise network, adjacency and topological analysis; overlay is computationally heavier.Fast map-algebra and surface/proximity analysis; ideal for continuous fields.
Output qualitySharp, cartographic, scale-independent lines and boundaries.Blocky, resolution-limited edges; excellent for imagery and continuous shading.

In summary, vector excels where features are discrete and boundaries and connectivity must be exact (cadastre, roads, utilities), offering compact storage, rich attributes and crisp output, at the cost of a more complex structure and heavier overlay. Raster excels for continuously varying phenomena and imagery (elevation, temperature, land cover), offering a simple structure and very fast overlay/map-algebra, at the cost of large storage, resolution-limited precision, blocky boundaries and no inherent topology. The correct choice matches the model to the phenomenon and the analysis.