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Representing Scale on Maps Definition: The scale of a map is ratio between distances on the map and the corresponding distances in the real world.

Scale Scale representation on the map: Representative fraction (RF): “1:100,000”, “1 to 100,000”, or “1/100,000” Verbal: 1 inch is equal to 50 miles Graphic: Scale bar 10 miles

Scale is a ratio Scale of a map is a ratio It is unit-independent 1/1000 > 1\100,000 (1/100 is greater than 1/100,000) Thus 1:1000 is a large scale map, showing a smaller region but magnified 1/100,000 is a small scale map, showing a larger region

General Classification of Scale Remember that the notions of small and large are reversed from our conventional thinking when we talk about scale  large scale refers to looking at a smaller area in detail. Here are some scale guidelines: Large scale  1:400 to 1:50,000 Intermediate scale  1:50,000 to 1:250,000 Small scale  1:250,000 and beyond

Scale and Map Projections The representative fraction of a map does not tell us the scale everywhere on the map! Transformations due to projecting maps introduce distortion RF is only accurate along standard lines or points

Scale Varies on a Map Does the same length measured on the map at the Equator and near the pole represent the same distance? Standard lines The map scale (RF) is only valid along these standard lines

Scaling Up Data created for local areas can be used for larger (regional or national) areas.

Maps and GIS - Scaling Up The river network shown here on a national scale was produced at a much larger scale, and it contains a great deal of detail that cannot be seen here … zooming in …

Maps and GIS - Scaling Up This level of detail is not necessary or useful at the national scale. All the detail that is encoded in this river network data is really only visible and useful when operating at more local scales. Vector data such as this river may need to be smoothed for scaling up.

Maps and GIS - Scaling Up Scale Effect on Mapping White pine Lodgepole rice wheat White pine Lodgepole rice wheat Scaling up (aggregating) What should we call these cells? Raster data may need to be generalized. An aggregation algorithm must be chosen.

Maps and GIS - Scaling Down Large-scale data contains more detail than small-scale data When using small-scale data (data collected at a small scale) for a purpose that is larger-scale than it was intended for a different kind of problem occurs…

Maps and GIS - Scaling Down Let’s take a look at Pamlico Sound on the coast of NC. The background data is a XXX-scale coverage of North Carolina, with the counties. The red line is the outer boundary of another vector coverage of North Carolina, but this one is XX-scale. What differences do you notice? Here we can see a national scale coastline (shown in red) superimposed over local scale data, we can clearly see the generalization and lack of detail

Intended use Scale of your data must be chosen based on: Your data needs The intended use of the existing data

Examples Your data options are: What data source do you use when: Landsat TM data (30 meter resolution) SPOT satellite imagery (5 meter resolution) Ikonos satellite data (1 meter resolution) What data source do you use when: You’re building a nuclear power plant on a site near a lake, and need to plan the location of each component of the plant Some illegal cutting of small patches of forest is going on in a national park in the Brazilian Amazon. We want to map where the cuts have occurred throughout the park.