Planning a GIS project

STEP ONE
Define problem and project goals
Consider the following questions
• What is the problem to be solved? How is it to be solved? Are there alternative ways to
solve it using GIS? Will the data be used for other purposes?
• What are the final products of the project – reports, working maps, presentation-quality
maps?
• Who is the intended audience of these products –the public, planners, technicians, officials
etc
• Will the data be used for other purposes? What are the requirements for these?
Step one is important because the answers to the questions determines the scope of the project as
well as how the analysis is implemented.

STEP TWO
Develop methodology and analysis flow

• Create a project database (is critical and time consuming part of the project)
• Designing the database includes identify spatial data based on the requirement of the analysis, determine the required feature attributes, setting the study area boundary and choosing the coordinate system to use.
• Automating the data involves digitizing or converting data from other systems and formats into usable formats as well as verifying the data and correcting errors.
• Managing the database involves verifying the coordinate systems and joining adjacent layers. The completeness and accuracy of the data used in the analysis determines the accuracy of the results.
• Data inventory, input, manipulation and management

STEP THREE
Analyzing the data
Analysis and accuracy assessment. Analyzing GIS data ranges from simple mapping to complex spatial models. Analysis methodology and list the major steps in the process. Create a systematic diagram of the process as a guide.
Definition of a model: a model is a representation of reality, used to simulate a process, predict an outcome or analyze a problem. A spatial model involves applying one or more of three categories of GIS functions to some spatial data:

• Geometric modeling functions: calculating distances, generating buffers and calculating areas and perimeters.
• Coincidence modeling functions: overlaying datasets to find places where values coincide
• Adjacency modeling functions: allocating, pathfinding and redistricting.

STEP FOUR
Presentation of the results

• Poster-sized map
• Charts and reports of selected data are two ways of presenting the results
• Journal paper
• Powerpoint presentation