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Quantification of Map informations

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#1
hotshot

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I'm a grad student in Urban Planning and we have a report on Planning Intelligence and Presentation of Land Use Information.

Wanna ask about quantification of mapped information. I searched several books and I'm still not enlighted with the topic.

Please enlighten me with the following topics.

- Qualitative Info
- Ordered Info
- Quantitative Info
- Interval Measurement Scale
- Ratio Measurement Scale
a.] Absolute Quantities
b.] Relative Quantities


Thanks in advance! More power to Cartotalk! :D

#2
Hans van der Maarel

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I'm a grad student in Urban Planning and we have a report on Planning Intelligence and Presentation of Land Use Information.

Wanna ask about quantification of mapped information. I searched several books and I'm still not enlighted with the topic.

Please enlighten me with the following topics.

- Qualitative Info
- Ordered Info
- Quantitative Info
- Interval Measurement Scale
- Ratio Measurement Scale
a.] Absolute Quantities
b.] Relative Quantities


Thanks in advance! More power to Cartotalk! :D


Well, first of all welcome to Cartotalk.

I'm no expert on this matter, but here goes...

Quantitative information is information that can be expressed in numbers (e.g. "average rainfall is 300mm/year", "population density is 29 people per square km"). It can be measured.

Qualitative information is information that can't really be measured. It's got more to do with how people feel about something (e.g. "quality of living in this place is good", "Amsterdam is a cool place" and "puppies are cute")

Ordered information is, I guess, information with a certain "x is better here than there" component.

The type of information in turn dictates what kind of maps can be made with it.

Anyway, this is for starters. Tell us, what did you find out? ;)
Hans van der Maarel - Cartotalk Editor
Red Geographics
Email: hans@redgeographics.com / Twitter: @redgeographics

#3
P Riggs

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- Qualitative Info
- Ordered Info
- Quantitative Info
- Interval Measurement Scale
- Ratio Measurement Scale
a.] Absolute Quantities
b.] Relative Quantities


Quantitative information is information that can be expressed in numbers (e.g. "average rainfall is 300mm/year", "population density is 29 people per square km"). It can be measured.

Qualitative information is information that can't really be measured. It's got more to do with how people feel about something (e.g. "quality of living in this place is good", "Amsterdam is a cool place" and "puppies are cute")

Ordered information is, I guess, information with a certain "x is better here than there" component.


I agree,but usually see the categories broken down differently:

-Qualitative (or Categorical): Information classified into categories with no category inherently ordered more than another. Example... land cover. Forest is not quantitatively more than Urban. In my statistics class we also deal with True/False and Yes/No which are keyed in as 1/0. Even though it is numerical, True (1) is not quantitatively more than No (0). So they are numerical qualitative, or categorical, data. Same for the National Land Cover Dataset (NLCD). Land cover categories are assigned numerical categories, but still Forest (40) is not numerically greater than Urban Developed (20). I've also seen data have decimal points, so don't assume if data have decimal points they are automatically real quantitative data.

-Quantitative: Information where numbers actually mean something relative to each other...
a. Ordered: 2 is greater than 1, and 3 is less than 4. However, not by the same amounts. In other words, the difference of 1 between 2 and 1 is not the same as the difference of 1 between 3 and 4. Example... Cities with populations < 500 are coded as 1, cities with populations 500-1000 are coded 2, 1000-50,000 coded 3, and > 50,000 coded 4. The differences between city codes 2 and 1 are not the same as between 3 and 4. I've also seen ordered data contain decimal points.
b. Interval: Same as Ordered, but the differences of 1 are the same. You can also think integer data. Example... Actual population numbers. There are no half people, quarter people, etc. Only whole numbers. And a one person difference is quantitatively the same as any other one person difference.
c. Real (or Ratio): Has decimal values. 1.1, 2.345, 100.0402. And the decimal differences (0.2 and 0.1 compared to 0.001 and 0.002) mean something relative to each other on a number line. Example... Area of forest versus area of Urban in acres (notice the inclusion of units).

Relative: The 0 value doesn't have a real meaning.
Absolute: The 0 value has a real meaning.
Example... Temperature. 0 degrees F and 0 degrees C have different meanings, but aren't related to an true temperature of 0, the absence of heat. 0 degrees Kelvin, however, does mean the absence of heat. So F and C are relative. Kelvin is absolute.
Philip Riggs
Decorative-Maps.com

#4
Matthew Hampton

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Those are pretty basic concepts and since you are a Grad Student - I would point you to "Spatial information systems: design, modelling, and use in planning" by P Nijkamp, HJ Scholten - in the International Journal of Geographical Information Science, 1993 - informaworld.com

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