This could be a great opportunity to focus on learning a specific skill such as python or another relevant programming language. So even if you are doing work that has been done before or you have chosen a topic that you are not particularly passionate about, using new tools and learning new skills to complete the project and recreate the spatial analysis and produce some sort of cartographic output of your work, might just give you the drive you need. If you are not inspired by a particular spatial problem, geographic topic or spatial dataset just pick anyone and add your own twist by using different GIS tools.
If you are passionate about a particular environmental issue now is your chance to take a deep dive and try to make a difference. If you already have knowledge of a particular niche, this could be a geographic area or a topic area such as urban planning, try to find some data that relates to that and start asking questions!Why are things located where they are?
GIS projects should be seen as a chance to gain experience so if you don’t have any ideas of what you want to work on try asking yourself where you want to be and if doing a specific kind of project on a specific topic could help you get there. For example, if you want to work for the local municipality or get an internship with a particular government organization, contact them and ask if there is something you could help them work on. It might be a really good idea to already have an understanding of what they might need or the projects they might already be working on where you think you can add value. Getting your foot in the door with an organisation that you one day hope to work for by combining your GIS project with their needs is a smart move!
If you are doing this as part of your final project at a university or college, consider asking one of your lecturers if they need help with anything they are working on. The opportunity to work closely with a staff member might give you some real work experience which would look great on your resume and it might also increase the likelihood of a favourable testimonial later on. Don’t limit yourself to just the staff members in your own department, you might be able to add more value to another staff member in another department. This is also a great opportunity to apply geographical knowledge to different disciplines.
What problem needs solving?
Is there a geospatial problem that you can solve? This could be an analysis problem such as
Where is the best place for the ….
Why is this not a good location for the ...
This could be a process problem:
How can this be done? Perhaps the specific function doesn’t exist for your specific problem?
How can I do this faster? Is there something you can improve?
How can I make this repeatable? Can you model the process, add different variables, repeat?
Once you have considered these questions it's time to find some data and think about what the primary output or result of your GIS project needs to be.
Do you have to create static maps? If not consider creating a web map will visualise your results differently depending on the scale
Maybe it makes sense to display our findings as a 3D map by either adding elevation into the mix or by extruding your results based on a numerical attribute in the data.
Perhaps it maps sense to show change over time? In this case you could output your results as animations.
Maps are not the only answer when visualizing results of spatial analysis, so think about your audience. What message are you trying to get them to understand? Is a map the best way of doing this? Here is a podcast episode that talk about this in more depth.
Oftentimes you won’t get the spatial analysis right the first time or you might want to recreate the anayaliss again just with other parameters to see how this affects the results. This can be a time consuming process and without good data management practices you will quickly lose track of the exact steps in your process. Consider building a model of our process right from the start. Many GIS desktop environments offer built- in graphical model builders. If you are not already familiar with them it may take you more time at the start but the ability to quickly rerun a process based on new information or parameters plus the fact that the model in itself is documentation of the process far exceeds the perceived disadvantages of having to learn how this graphical programming interfaces work. Not only will you be learning a valuable skill, how to automate workflows, but you will also be able to export the graphical model to a programming language ( probably python ) and include the resulting script as documentation in your final report.
Most GIS desktop applications have the ability to create a map book or atlas. Basically what this does is export maps at different locations and scales based on parameters that you define. For example, let us imagine that you needed to map a wind farm. Displaying the entire wind farm, the position of each wind turbine, on a map gives context to the wind farm as a whole but because of the scale we lose the detail of what is located around each individual wind turbine. This is a great use case for the map book or atlas function. Using this tool you can export a map of the entire area and a separate map of each wind turbine location at the push of a button. This offers all the same advantages of the building graphical models in that if something changes you can easily run the process again and recreate all your maps without needing to spend hours and hours creating individual maps.
Can you recreate that?
Prove it wrong or confirm that it is correct?
What about using the same data and just looking at it from a different perspective?
Can you take the same methodology and apply it to another data set?
What other variable could you take into account?
Try looking through the tools you have available in your desktop GIS application. Click on the ones that sound interesting and read the description. These tools often have detailed descriptions and examples of how they should be used and what the end result is. Perhaps you will find some inspiration here.
Access to elevation data is becoming easier and easier and adding topography to geospatial data makes your maps and visualizations more realistic. Once you have an elevation data set you can calculate different attributes for vector features which might lead to some interesting analysis ideas.