Pearson correlation of two 1D array in Earth Engine

Unlocking Insights: Pearson Correlation in Google Earth Engine, Made Easy

Ever wondered how to measure the relationship between two sets of data in Google Earth Engine (GEE)? Well, the Pearson correlation coefficient is your friend! It’s a nifty tool that helps you understand how closely two things move together. Think of it as a way to see if your hunch about two datasets being related actually holds water. Let’s dive into how you can use it with GEE.

So, what exactly is this Pearson correlation thing? Simply put, it’s a number that tells you how strong and in what direction two sets of numbers are related. This number, often called “r,” always falls somewhere between -1 and +1. A +1 means they’re perfectly in sync – as one goes up, the other goes right along with it. Zero? That means there’s no linear relationship at all; they’re doing their own thing. And a -1? That’s a perfect opposite relationship; when one rises, the other falls like a stone.

But it’s not just about the extremes. Numbers in between tell you how strong the connection is. Generally, anything above 0.5 or below -0.5 is considered a pretty solid link. Between 0.3 and 0.5 (or -0.3 and -0.5), you’ve got a moderate connection. Anything weaker than that, and the relationship is, well, pretty weak.

Now, a word of caution: just because two things are correlated doesn’t mean one causes the other. This is a classic trap! You might find that ice cream sales and crime rates rise together, but that doesn’t mean ice cream makes people commit crimes (or vice versa!). There might be a third factor at play, like warmer weather.

Okay, enough theory. Let’s get practical with Google Earth Engine. GEE uses these things called ee.Array to handle lists of numbers. Think of them as columns in a spreadsheet. Now, GEE has built-in tools to find correlations between images, but what if you just want to compare two simple lists of numbers? That’s where things get interesting.

Here’s the deal: GEE doesn’t have a one-click button for Pearson correlation between two ee.Array objects. But don’t worry, we can build our own! It’s like making your own sandwich when the deli is closed. You just need to follow the recipe:

First, make sure your data is in the form of two ee.Array objects, and that they have the same number of entries. You can’t compare apples and oranges, right?

Next, here’s the code snippet to make the magic happen:

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