Finding Vector data that is in the area of a specific value of Raster data

Digging Deep: Finding Vector Gold Inside Raster Data

Okay, so you’re working with maps and GIS, right? You’ve got your raster data – think of it like a digital photo, a grid of values showing things like elevation or forest type. Then you have vector data: these are your points, lines, and polygons representing actual things on the ground, like buildings, roads, and property lines. The real magic happens when you start combining them. Ever needed to find all the houses sitting on land above a certain elevation? Or maybe pinpoint roads snaking through a specific kind of forest? That’s where this gets interesting.

Let’s break it down. Raster and vector data, while both map-related, are fundamentally different. Imagine raster data as a detailed, but somewhat blocky, painting. Each tiny square (or pixel) has a color representing a value. Great for showing continuous stuff like temperature changes or how high the land is. Vector data, on the other hand, is more like a precise line drawing. It uses shapes to mark distinct things. Think of it this way: raster is the landscape, vector is what you build on it.

So, how do we actually find those vector features hiding within specific raster values? Turns out, there are a few cool tricks up our sleeves.

First up: Overlay Analysis (aka Extract by Mask). This is like using a stencil. You take your vector data and use it to “cut out” a piece of your raster data. Want to see just the elevation data underneath the city limits? Boom, overlay analysis. To find vectors within a specific raster value, you’d first need to isolate that value on the raster – maybe reclassifying it. Then, use that as your stencil to extract the vector features.

Then we have Zonal Statistics. This one’s a bit more statistical, as the name suggests. Imagine dropping a bunch of pins (your vector data) onto a map and then asking, “Okay, what’s the average elevation around each pin?” Zonal stats does exactly that. It crunches the numbers to summarize the raster values within each vector zone. If you’re trying to find all the parcels with an average temperature above a certain point, zonal statistics is your friend.

Raster to Vector Conversion is another option. Sometimes, you just need to turn that raster data into vector data. Convert those raster cells into polygons, and suddenly you can use all sorts of vector-based tools to find overlaps and intersections. It can be handy, especially with complex rasters.

Finally, there’s the direct approach: Spatial Queries. This is where you ask your GIS software a direct question, like “Show me all the vector points that fall inside raster cells with a value of X.” Most GIS programs have tools like “Select by Location” that let you do this easily.

Now, what tools can you use for this? Well, there are a few big players in the GIS world.

• ArcGIS Pro: This is like the Swiss Army knife of GIS software. It’s got everything, including all the tools we’ve talked about.
• QGIS: The best part? It’s free and open source. Don’t let the price fool you, it’s incredibly powerful and can do almost anything ArcGIS Pro can.
• GRASS GIS: Another open-source option, GRASS is a powerhouse for raster processing.
• Global Mapper: This one’s great for general GIS tasks, including converting between raster and vector formats.

Okay, let’s get our hands dirty. Here’s an example of how to extract raster values to vector data using Zonal Statistics as Table in ArcGIS Pro :

So, there you have it. Finding vector data within specific raster values might sound complicated, but with the right tools and techniques, it’s totally doable. Whether you’re analyzing elevation, land cover, or anything in between, these methods will help you unlock the hidden connections in your spatial data. Now go forth and map!