Selecting multiple polygons based on common field in a point file (point does not fall within polygon) to perform service area analysis

Selecting Multiple Polygons Based on a Common Field in a Point File for Service Area Analysis

Okay, so you’re diving into GIS and need to figure out service area analysis. It’s a big topic, but a super useful one when you’re trying to understand things like accessibility and coverage. Now, here’s a head-scratcher that often pops up: How do you pick out a bunch of polygons based on something they share with a point file, especially when those points aren’t even inside the polygons? Sounds tricky, right? Turns out, with a clever combo of attribute and spatial selection, you can totally nail this and get some seriously insightful service area analyses going.

Think of it this way: Imagine you’ve got customer locations (points) and sales territories (polygons). Ideally, each customer dot would be neatly tucked inside its territory. But hey, real life happens! Maybe the GPS on your customer’s phone was a little off, or the data’s been simplified. The point is, those customer dots might be wandering outside their lines. But you know each customer belongs to a specific territory, thanks to a territory ID that’s in both your customer list and your territory map. So, how do you connect the dots (pun intended!) and select the right territories?

The trick is to use a two-step process: first, link the data based on that shared territory ID, and then use that link to make your spatial selection.

Here’s the breakdown:

How you actually do this depends on the GIS software you’re using, but the general idea is the same.

• ArcGIS: Look for the “Join Field” tool to do the attribute join. Then, “Select By Attributes” to grab the right customers, and finally, “Select By Location” to snag the territories.
• QGIS: QGIS has you covered with “Join attributes by field value” for the join, and “Select by expression” and “Select by Location” for the selections.

A few things to keep in mind:

• Garbage In, Garbage Out: Your results are only as good as your data. Double-check that territory ID field! A typo there can throw everything off.
• Coordinate Clarity: Make sure your customer map and territory map are speaking the same language – that is, they’re in the same coordinate system. Otherwise, things will get wonky fast.
• Join Wisely: Pay attention to the “join type.” Most of the time, a simple one-to-one join is what you want. But if a customer could potentially belong to multiple territories (unlikely, but hey, it could happen!), you might need a one-to-many join.
• Big Data? Buckle Up: If you’re dealing with a ton of customers and territories, these joins and selections can take a while. Make sure your data is organized and indexed to keep things running smoothly.

At the end of the day, being able to select polygons based on shared info with a point file – even when those points aren’t neatly inside – is a seriously powerful GIS skill. It lets you do service area analysis with confidence, knowing you’re working with the right data. And that, my friends, is how you turn data into decisions.