Map Analysis in GIS

ANALYSIS - What & Why? :
The heart of GIS is the analytical capabilities of the system. What distinguish the GIS system from other information system are
its spatial analysis functions. Although the data input is, in general, the most time consuming part, it is for data analysis that
GIS is used. The analysis functions use the spatial and non-spatial attributes in the database to answer questions about the real
world. Geographic analysis facilitates the study of real-world processes by developing and applying models. Such models
illuminate the underlying trends in geographic data and thus make new information available. Results of geographic analysis can
be communicated with the help of maps, or both.

The organization of database into map layers is not simply for reasons of organizational clarity, rather it is to provide rapid access
to data elements required for geographic analysis. The objective of geographic analysis is to transform data into useful information
to satisfy the requirements or objectives of decision-makers at all levels in terms of detail. An important use of the analysis is the
possibility of predicting events in another location or at another point in time.

●ANALYSIS -How?
Before commencing geographic analysis, one needs to assess the problem and establish an objective. The analysis requires
step-by-step procedures to arrive at the conclusions. The range of geographical analysis procedures can be subdivided into the
following categories.

o Database Query. o Overlay. o Proximity analysis.

o Network analysis. o Digital Terrain Model. o Statistical and Tabular Analysis.

● Use of Spatial Analysis: It helps us to:

o Identify trends on the data.

o Create new relationships from the data.

o View complex relationships between data sets.

o Make better decisions.


●Geographic Analysis:
It is the analysis of problems with some Geographic Aspects.

o Alternatives are geographic locations or areas.

o Decisions would affect locations or areas.

o Geographic relationships are important in decision-making or modeling.

Some examples of its applications:
o Nearest Neighbour.
o Network distances.
o Planar distances.

 
source