A GIS problem-solving workflow provides a structured approach to answering spatial questions, moving logically from an initial idea to a final, actionable result. Following these steps ensures the analysis is repeatable, defensible, and clearly addresses the core problem.
Here is a typical GIS problem-solving workflow.
Source: https://www.saddhussein.com/gis-workflow/
This is the most critical step. You must clearly define the question you are trying to answer and the criteria for success. Vague questions lead to vague answers.
Bad question: "Where are good places for a new park?"
Good question: "Where are the residential areas with the highest population of children under 10 that are more than a half-mile walk from an existing park and are on city-owned vacant land?"
This step involves identifying the project's goals, scope, and the specific spatial relationships you need to investigate.
Once you know your question, you can identify the necessary data. This stage involves finding, collecting, and preparing your geospatial and tabular data for analysis.
Data Acquisition: This involves searching for existing data from sources like government portals (e.g., USGS, Census Bureau), university archives, or commercial vendors. If data doesn't exist, you may need to create it through methods like digitizing, GPS surveying, or field data collection.
Data Preparation (Pre-processing): Raw data is rarely ready for analysis. This step includes crucial tasks like:
Projection & Reprojection: Ensuring all data layers share the same coordinate reference system (CRS).
Data Cleaning: Correcting errors, removing duplicates, and addressing missing values.
Formatting & Conversion: Changing file types (e.g., converting a CSV to a shapefile) or joining tabular data to spatial features.
Subsetting/Clipping: Extracting only the data within your specific area of interest to improve performance.
This is the core of the workflow where you use GIS tools to manipulate the data and uncover new insights. The specific analysis you perform is dictated by the question you defined in the first step.
Common analysis methods include:
Proximity Analysis: Using tools like buffers to find features within a certain distance of other features.
Overlay Analysis: Combining multiple data layers to find where they intersect. Tools like Intersect or Union are used to find areas that meet several criteria at once.
Network Analysis: Calculating routes and service areas along transportation networks (e.g., finding the best route for an ambulance).
Raster Analysis: Performing calculations on grid-based data, such as deriving slope from an elevation model or performing a suitability analysis.
The analysis itself only produces more data. In this step, you interpret what the results mean and communicate your findings effectively. The primary output is often a map, but it can also be a chart, graph, report, or an interactive web application.
Key considerations include:
Cartography: Designing clear, uncluttered, and aesthetically pleasing maps with essential elements like a legend, scale bar, and north arrow.
Visualization: Choosing the right symbols, colors, and classification methods to accurately represent your data and tell a compelling story.
Communication: Explaining the results, the methods used, and any limitations or uncertainties in your analysis. Your audience should be able to understand your findings and how you arrived at them.
Finally, it's important to review your work. Does the result actually answer the question from Step 1? Did you use the correct data and methods? Often, the initial results will reveal new questions or highlight issues with the data, leading you to refine your approach and repeat parts of the workflow. This iterative process is key to producing a robust and reliable final product.
References:
https://learn.arcgis.com/en/related-concepts/spatial-problem-solving-approach.htm
https://www.saddhussein.com/gis-workflow/
https://share.google/bYuI182RduZsePrz3
Somers, R. M. (2009). GIS Project Planning and Implementation. Advanced Geographic Information Systems, 19-31.
