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Chapter 6 Using GIS for Spatial Analysis
(relating locations of cholera deaths to the positions of water pumps) was
innovative for the mid-nineteenth century, but commonplace today—with
GIS, these types of spatial analysis problems can be easily addressed.
Other common forms of spatial analysis questions are some of the
following:
a How many objects are within a certain distance of a particular location?
All manner of these types of questions can be answered, including marketing topics such as, ‘‘How many fast food restaurants are within one
mile of an interstate exit?”; real estate topics regarding how many rental
properties are within two blocks of a house that is for sale; or planning
topics to determine the acreage of wetland threatened with removal by a
new proposed development plan.
a How do you choose the most suitable location based on a set of criteria?
Many different types of questions related to this topic can be answered,
such as those involving where to locate new commercial developments,
new real estate options, or the best places for animal habitats.
This chapter examines how GIS can be used with spatial data to answer
questions like these in the context of spatial analysis. Keep in mind the two
ways that GIS is used to model real-world data from the previous chapter—
vector and raster. Due to the nature of some of these properties, some types of
spatial analysis are best handled with vector data and some with raster data.
How Can Data Be Retrieved
From a GIS for Analysis?
One type of analysis would be finding which areas or locations meet particular
criteria—for instance, being able to take a map of U.S. Congressional Districts
and identify which districts had a Democratic representative and which had
a Republican representative. Alternatively, you might have a map of all residential parcels and would want to see which houses have been sold in the last
month. In both of these examples, you would perform a database query to
select only those records from the attribute table (see Chapter 5) that reflect
the qualities of the objects you want to work with.
In other cases, before beginning the analysis, you may only want to utilize
a subset of your GIS data. For instance, rather than dealing with all Congressional Districts in the entire United States, you might want to examine only
those in Ohio. Or in the housing example, if you have a dataset of all residential parcels in a county (which is likely thousands of parcels), you may only
want to do analysis related to one (or a handful) of the parcels, rather than
examining all of them. You’d want to go into the dataset and select only those
parcels required for your study. In these cases, the query would again only
select the records you want to deal with.
In GIS, queries are composed in the Structured Query Language (SQL)
format, like a mathematical function. SQL is a specific format that is used for
query the conditions
used to retrieve data
from a database.
SQL the Structured
Query Language—a
formal setup for
building queries.
Chapter 6 Using GIS for Spatial Analysis
(relating locations of cholera deaths to the positions of water pumps) was
innovative for the mid-nineteenth century, but commonplace today—with
GIS, these types of spatial analysis problems can be easily addressed.
Other common forms of spatial analysis questions are some of the
following:
a How many objects are within a certain distance of a particular location?
All manner of these types of questions can be answered, including marketing topics such as, ‘‘How many fast food restaurants are within one
mile of an interstate exit?”; real estate topics regarding how many rental
properties are within two blocks of a house that is for sale; or planning
topics to determine the acreage of wetland threatened with removal by a
new proposed development plan.
a How do you choose the most suitable location based on a set of criteria?
Many different types of questions related to this topic can be answered,
such as those involving where to locate new commercial developments,
new real estate options, or the best places for animal habitats.
This chapter examines how GIS can be used with spatial data to answer
questions like these in the context of spatial analysis. Keep in mind the two
ways that GIS is used to model real-world data from the previous chapter—
vector and raster. Due to the nature of some of these properties, some types of
spatial analysis are best handled with vector data and some with raster data.
How Can Data Be Retrieved
From a GIS for Analysis?
One type of analysis would be finding which areas or locations meet particular
criteria—for instance, being able to take a map of U.S. Congressional Districts
and identify which districts had a Democratic representative and which had
a Republican representative. Alternatively, you might have a map of all residential parcels and would want to see which houses have been sold in the last
month. In both of these examples, you would perform a database query to
select only those records from the attribute table (see Chapter 5) that reflect
the qualities of the objects you want to work with.
In other cases, before beginning the analysis, you may only want to utilize
a subset of your GIS data. For instance, rather than dealing with all Congressional Districts in the entire United States, you might want to examine only
those in Ohio. Or in the housing example, if you have a dataset of all residential parcels in a county (which is likely thousands of parcels), you may only
want to do analysis related to one (or a handful) of the parcels, rather than
examining all of them. You’d want to go into the dataset and select only those
parcels required for your study. In these cases, the query would again only
select the records you want to deal with.
In GIS, queries are composed in the Structured Query Language (SQL)
format, like a mathematical function. SQL is a specific format that is used for
query the conditions
used to retrieve data
from a database.
SQL the Structured
Query Language—a
formal setup for
building queries.