1. Choropleth maps represent data using color or shading within geographic areas, while dasymetric maps represent data more accurately by differentiating between areas that can and cannot contain the phenomena. 2. Creating choropleth maps involves determining values for each area and selecting symbols to represent categories, while dasymetric maps divide areas into higher and lower value zones. 3. Both map types can represent nominal, ordinal, and ratio data but choropleth maps are prone to oversimplification and distortion while dasymetric maps improve accuracy and visualization at finer scales though requiring more complex processing.

1. MAPPING SPATIAL VARIATIONS
CHOROPLETH AND DASYMETRIC MAP
Instructed by,
DR. MD. LATIFUR RAHMAN
SARKER

2. GROUP MEMBERS (G-07)
Suman(143)
• Hasibul(144) Shoity(147)
Rakib(145) Sumon(146)

3. CONTENT
LAYOUT
Choropleth
and
Dasymetric
map
1.What is choropleth map and
steps to create this.
2.Application of
choropleth map.
3.Limitation of
choropleth map.
4.What is dasymetric
map and steps to create
this.
6.Limitation of
dasymetric map.
5.Application of
dasymetric map.

4. CHOROPLETH MAP

5. .f CHOROPLETH MAP.
Example such as
• World population
• Vegetation
• Land use
Figure-1: World population density.
From Ancient Greek χώρα (khṓra, “location”) + πλῆθος (plêthos, “a great number”) +
English map. First proposed in 1938 by American geographer John Kirtland Wright to
mean "quantity in area," although maps of the type have been used since the early 19th
century.
A choropleth map is a type of
thematic map that uses color or
shading to represent data values of
a particular geographic area.
What is choropleth map?

6. 1
In constructing a choropleth map is to determine the appropriate
value to be associated with each area on the map.
3
Appropriate symbols and next selected to represent each of the
categories .
4
Finally, the map is drawn.
Steps to create the choropleth map.

7. Application of choropleth map

8. Type of data.
Any of the three of average may be
derived for any suitably measured set of
data, symbol of the appropriate design
selected , and result mapped.
For example,
• Agricultural land
• Annual precipitation
• Population density
Figure-2: Population density of
America.
1. The value must be independent of the size of
the area.
2. The presentation of the sample data for
choropleth mapping involves the computation of
the average harvest per unit of area.

9. Nominal data.
Nominal information is portrayed on a
choropleth map simply by placing an
appropriate symbol over the surface of each
zone. In some case, the categorization of each
data zone is obvious. For example, on a
political map the different national territories.
Nominal data.
Figure-3: World political map.
Patterns or color of a similar value or intensity
are used to symbolize different categories.
Figure-4: Population density of Bangladesh.
Care must be taken to keep read ability in
mind when selecting these symbols. Each
symbol must be distinctive enough to be read
able but, at the same time, garish or visually
irritating combinations must be avoided.

10. ►Ordinal data is a type of data that represents categorical
variables with a specific order or ranking.
Figure-4: Population
density.
The process to input ordinal or ratio data in choropleth map:
►On such maps, the mean of ratio data or the median of the
ordinal data is calculated for each data zone.
►The most common approach is to divide the data into
several categories and to assign a particular gray value to
each. This process is subject to two main considerations:
●How many categories to use
●What gray value to associate with each category.(the
shades of gray must differ from one another considerably in
order to be distinguishable on the map)
Ordinal or ratio data.

11. Ordinal or Ratio data.
►Then gray values are assigned so that the zone with the lowest average value has
the lightest value symbol and the zone with the highest average value has the
darkest value symbol.
♠ It is an attractive idea to have a large number of levels in order to present more
detail ; the greater the number of levels the less generalization involved and the
more realistic the representation.
Figure: Example of inputting Ratio data in choropleth.

12. Ordinal or Ratio data.
The use of differing patterns to indicate relative values is not
encouraged. Because, there is no particular reason for a
map reader to relate dots to low numerical values and cross-
hatching to high values.
More importantly, when the pattern are used, viewers seem
to respond to the apparent gray value and not to the pattern.
In essence, the use of varing patterns to indicate level of
density or importance is simply a means of obtaining varing
gray values.
A pattern that reads as a dark value tends to be associated with a high incidence of
the variable and one that yields a light value is associated with a low incidence-the
pattern itself is of relatively little importance.
Figure: choropleth map.

13. Ordinal or Ratio data.
Color provides a larger selection of easily distinguished
hues, chroma and values, so that more data categories
can be symbolized than by the use of gray values alone.
(High chroma mean the highest value and low chroma mean the lowest
value)
Figure : Annual of precipitatin on African continent.
Figure : Annual of precipitatin on African continent.
The use of two colors is sometimes permissible.
For example , a range of blue values is used to indicate
precipitation above some transitional amount ,and a range of
browns to indicate smaller quantities . In this case , the darker
blue is used to indicate greater moisture and lighter blue less
moisture , whereas the brown values are made darker to
indicate greater aridity.

14. Data classes is an important part of the design of choropleth map that shows
statistical information. Using some of these statistical process we can divide data into
four classes. Such as
♠Quintiles
♠Equal interval
♠Natural breaks
♠Mean and Standard deviation
Data classes.
Quintiles : When the values for an indicator are divided into four
equal groups, each grouping is a known as a quintile . Each
quintile represents 25% of the range of values for the indicator.
The first quintile represents the lowest 1/4 of values from 0-25%
of the range, second quintile represents 25-50%,third and fourth
quintile represent in some respects 50-75% and 75-100%.75-
100% is the upper quintile.
Figure : Quintiles map

15. Data classes.
Equal interval: The equal interval classification divides
the classes into equal group (e.g. 4-8,8-12,12-16).This
means that equal interval choropleth maps almost
always result in an unequal count(e.g. 113 in group
1,41 in group 2).This process is useful to highlight
changes in the extremes.
Figure : Equal interval map.
Natural breaks: The features are divided into classes
whose boundaries are set where there are relatively
big differences in the data. Natural breaks is an
optimise method for choropleth map which arranges
each grouping so there is less variation in each class.
Figure : Natural breaks map.

16. Standard deviation: Standard deviation is a statistical
technique type of map based on how much the data
differs from the mean. Frist the mean and standard
deviation are measured then each standard deviation
becomes a class in choropleth map.
Figure : Standard deviation map
Data classes.

17. DASYMETRIC MAP

18. What is dasymetric map.
Figure-8: Dhaka population
density.
A dasymetric map is a type of thematic map that
represents data in a more accurate and precise
manner than traditional choropleth maps. Unlike
choropleth maps, which divide geographic areas into
uniform regions regardless of their actual
composition.
For example
• Population density
• Annual precipitation
• Crime severity
• Vagetation
• Agricultureal area

19. Steps to create a dasymetric map.
1. To produce a dasymetric map, the total area can be divided into two
parts. One is the total value of phenomena and other that does not.
Example : The map shows the agricultural production of a county
dividing urban and agricultural area.
2. The phenomena occurs into areas of higher and lower values.
Example : divide the agricultural productive area high low productive
zone.

20. Steps to create a dasymetric map.
4.Finally, selecting appropriate symbols to
represents a dasymatric map to draw the map
by using appropriate symbols.

21. APPLICATION OF DASYMETRIC
MAP

22. Type of data.
Population density: In dasymetric
mapping, as it can be used to allocate
data values to subareas based on the
number of people living within each
subarea.
Example such as
• Land use
• Vegetation cover
• Socioeconomic characteristic
In a dasymetric map, there could be
nominal, ordinal and others are
represented
Figure-9: Population density.

23. Nominal data.
Types of land use: This could include
categories such as residential, commercial,
industrial, or agricultural.
Example such as
• Type of crime
• Type of business
• Type of natural features
In this datatype, here the name of any thing
which could be able to represent in the map
are shown.
Figure-10: Land use dasymetric
map.

24. Ordinal data.
Health status: Health data could be categorized by
levels of health status, such as excellent, good, fair, or
poor.
Example such as
• Income level
• Crime severity
• Education level
Figure-11: Social heath
status of Bangladesh.
Ordinal data is a type of categorical data in statistics
that represents data with discrete categories or groups
that can be ordered or ranked in a meaningful way.
Ordinal data provides information about the relative
magnitude or position of the values within the dataset.

25. Advantages and disadvavtages of choropleth map.
Advantage Disadvantage
1.Easy to understand 1. Oversimplification
2. Clear patterns and
trends
2. Distortion
3. Geographic context 3. Misleading
comparisons
Figure-12:Health facilities in
Bangladesh.

26. 1. Easy to understand: Choropleth maps use colors or patterns to
show data values in different regions. This makes it easy to see and
understand the data quickly.
2. Clear patterns and trends: Choropleth maps highlight patterns
and trends in the data. Colors or shades represent higher or lower
values, making it easy to identify areas with different characteristics.
3. Geographic context: Choropleth maps provide a geographic
context for data analysis. They show how data is distributed across
regions, helping to understand the relationship between the data and
the location.
Advantages

27. 1. Oversimplification: Choropleth maps can oversimplify complex data by
aggregating information at a coarse level, such as by country, state, or
administrative boundaries. This can lead to a loss of detail and nuances present
within smaller geographic units.
2. Distortion: Choropleth maps can introduce distortion in the interpretation of
data due to the unequal sizes and shapes of geographic regions. Larger regions
may dominate the map visually, giving the impression of higher or lower values
compared to smaller regions. This distortion can misrepresent the spatial
distribution of the data and lead to a biased interpretation.
3. Misleading Comparisons: Choropleth maps can mislead viewers when
making comparisons between regions. If regions have different sizes or
populations, the visual representation may inaccurately suggest that regions with
larger areas or populations have higher values.
Disadvantages

28. Advantages and disadvantages of dasymetric map.
Advantages Disadvantages
1. Improved accuracy 1. Complexity
2. Better
representation of data
2. Scale
3. Enhanced
visualization
3. Data availability
4. Improved decision-
making
4. Subjectivity
Figure-13:Annual rainfall of
Bangladesh.

29. Advantages

30. 1. Complexity: Decimeter-scale maps can be more complex to create and
understand compared to coarser-scale maps. The high level of detail requires
advanced processing and specialized knowledge.
2. Scale limitation: Decimeter-scale maps cover smaller areas compared to
coarser-scale maps. This can be a drawback when studying large-scale phenomena
or needing a broader spatial context.
3. Data availability: Acquiring high-resolution data at the decimeter scale can be
challenging and costly. Limited data availability may restrict the creation and usage
of decimeter-scale maps
Disadvantages

31. THE END