How do we work with spatial data?
In GIS, we work with our spatial data in layers. Layers are features on a map that represent the real world. Examples of this include:
- Lines that represent streets, sidewalks, or bike lanes.
- Points that represent the location of libraries, hospitals, or schools.
- Polygons (shapes) that represent lakes, buildings, or an area of land.
- Pixels that represent elevation, precipitation levels, or temperature.
Types of GIS layers. Image from USGS
How do we use geospatial data?
By analyzing the features in our layer, or by analyzing multiple layers together, we can work to answer many types of spatial questions and identify countless spatial patterns, including:
- Proximity: How many schools are located within 0.5 miles of a park with a playground?
- Suitability: Where in Hartford should we put a new gorcery store?
- Vulnerabilty: What areas in Cape Cod are most at risk of infrastructure damage due to rising sea levels?
- Clustering and Patterns: Where on I84 are the most crashes between cars and motorcycles occuring?
Test your spatial thinking: Pick one of these questions above. What information (spatial data) would you need to answer this question? How might you use this spatial data to answer this question?
Exploring different types of spatial analysis
We can use spatial statistics to identify and measure distribution, patterns, processes, and relationships that occur in space. For example, by identifying and measuring clusters, we can locate patterns in our spatial data and evaluate the strength and frequency of these patterns. Cluster analysis methods are common ways to measure phenomena such as:
- The prevelance of crime.
- Motor vehicle crashes.
- The location and prevelance of a demographic group.
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We can use network analysis to evaluate the relationship and connectivity between systems. This type of analysis is commonly used to evaluate transportation networks, where we can measure the relationship between time, distance, and navigation. Some examples of this might include:
- Identifying dorms at UConn that are less than a 10 minute walk from the UConn Dairy Bar.
- Finding the shortest walking route to the UConn Dairy Bar from Homer Babbidge Library.
- Selecting the dorm that has the shortest walk to the UConn Dair Bar.
Types of Network Analysis Layers, From ArcGIS ArcMap
These types of analysis combine several geospatial data layers together in order to identify and measure an area's characterists as it relates to our spatial question.
- We use suitability analysis to find the most ideal locations based on our criteria.
- We use vulnerability analysis to identify places most at risk, based on our criteria.
Some examples of a suitability analysis include:
- Finding the best location for vacation, based on your vacation preferences, such as climate, amount of people, afforability, and proximity to beaches.
- Identifying the most ideal park to put a new playground in, based on available space, buildable land, proximity to residents with kids under 10, and lack of other playgrounds in the area.
Some examples of vulnerability analysis include:
- Finding places where the population might be the most at risk to lead exposure based on house age, water infrastructure, and proximity to roads.
- Evaluating a area's flood risk based on rainfall, elevation, population density, and amount of non-pourous surface.
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