1. Research question and project goals. What is the purpose of the project? What is the research question? What is the spatial extent (total area) and grain size (ground resolution) of the study? Even a soils map is the answer to the question, “What is the spatial distribution of soils in California?” Identify the information needs: What type of spatial data do you need to achieve your goals? What are the sources of these data, and what are the appropriate types of data to answer these questions?
2. Methodology. Constructing a logical spatial analysis flow chart that details the project steps will make the success of the analysis more likely. What types of analyses will you perform? Overlays? Multivariate regressions? Spatial interpolations? The spatial analysis flow diagram should include:
o An outline of the procedures required for the data
o A logical sequence of procedures to be performed
o A list of all the data required for each step
3. Data. Before you embark on your project, you should do an inventory of the data requirements and sources of information. Even with the widespread availability of digital data on the Internet, many GIS projects are mired in data collection, input, and integration. Check if the data are already in digital format. Will you have to scan in paper maps or input data from statistical yearbooks?
4. Analysis and accuracy assessment. Often you will find that once you start the project, there is a need to revise the procedures originally intended. Once the analysis is complete, you should evaluate the accuracy and validity of the results. Fieldwork may be required.
5. Presentation. The results will have to be presented in a format suitable for the audience, and this can include a poster-sized map, journal paper, PowerPoint presentation, etc.
No comments:
Post a Comment