The First Week of GEOS419
Obsidian
Last semester I toyed around with taking my notes in an application known as Obsidian. I decided that it had merit and would allow me to easily generate flashcards and more clearly organize my notes. If you have watched any school or study tutorials you might have come across this as a tool, but you are more likely to have come across a tool called Notion.
Obsidian isn't as flashy as Notion, and it takes a little work to get it to work with the cloud, but it is a very capable hyperlinked markdown editor with the low low price of free and has a pretty active community.
Obsidian isn't as flashy as Notion, and it takes a little work to get it to work with the cloud, but it is a very capable hyperlinked markdown editor with the low low price of free and has a pretty active community.
Intro to GIS
The first aspect of the reading is all about GIS, when ESRI was founded, what makes data spatial or aspatial. It was in essence a pretty high-level overview of what GIS is and its history.
Answering the GIS Question
Starting out we read the introduction to Mastering ArcGIS Pro, went through a slide show on projects, and read a couple of websites including the Geographic Approach by Jack Dangermond of ESRI. I also watched a couple of YouTube videos on the subjects of framing a GIS project and choosing a Project. In general, the articles and readings all share a pretty similar set of steps, although sometimes the order is a little juggled.
1. Determine the problem
In this step, we are asking clear questions that have easily definable answers. Broad overarching questions can't be answered. This falls right into basic problem-solving ideas, where we are breaking down large issues into smaller easily challenged chunks
2. Determine how you will solve the problem
Once you know the question or questions you need to answer you can give some thought to what processes and data might be required to achieve that outcome. Document these methods so others can repeat the work to verify it if needed.
3. Get the data
Once we have an idea as to what data is needed we can set about souring it and determining if it is useful and useable, or if we might need to acquire it through some fieldwork.
Some of the things that we should look into to see if a data set it useful are:
Some of the things that we should look into to see if a data set it useful are:
The format the data is in?
How old is the data?
What scale is the data in?
What coordinate system is it in?
Does it have the attributes we need?
Does the dataset's geometry support the analysis?
Does it have any access constraints?
(Price, 2019)
2 or 3 first?
The two aspects of these steps that I see switched around are acquiring the data and determining the methods. When we see acquiring the data first there is some level of belief that with the question framed properly you will have a basic understanding of the answer you need, and so will be able to go out and find the data to support it, once that is done you can codify and document the methods.
When determining the method is done first we are documenting how and what is needed to answer the questions we are asking. Once we have that we can set out to get the data. In both cases, I believe that we need to have some idea of what data is required to answer the question, even if we haven't actually acquired it before we create our analysis method.
Our instructor walked through the slide packs prepared for the course in a lecture format and identified a couple of different concepts between an academic project and an industry project. He has stated that in academic projects it is often the case that they dive right into the creation of the methods working under the assumption that the data is available (SAIT, 2021). Either way it is important to remember that the process, although laid out in a linear fashion is in fact iterative.
4. Analyze the Data
Once we have the data and the analysis methods all that is left to do is to do the work to create our answers. At this point, we should look at the results and make sure they make some level of sense before doing any in-depth quality checking.
We should also note that these three steps: Determine Methodology, Get the Data and Analyze the data can be iterative steps, as we learn more and gain insight into the data we may come up with a better way to answer our questions.
5. Show your results
Finally without actually sharing your work, doing it is next to useless. We need to determine if the work is best suited to be shown on a map, shared as digital data, or perhaps an interactive web platform. Either way without this step no one can look at the data and use it to make decisions.
Works Cited
Price, M. (2019). Mastering
ArcGIS Pro (1st ed.).
SAIT. (2021, September 3). Introduction
to GIS Projects. Fall 2021 - GIS Data Analysis & Output (GEOS-419-O2A).
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