Getting surrounding pixel coordinates from ee.Geometry.Point

Decoding Pixel Neighborhoods: Getting Cozy with Surrounding Pixels in Google Earth Engine

Google Earth Engine (GEE) is seriously cool. Think of it as this giant brain in the cloud packed with satellite images and tools – basically, a remote sensing playground. Now, say you’ve got a specific spot on the map – maybe it’s your hometown, a research site, or just some random place that caught your eye. Wouldn’t it be awesome to peek at what’s around that spot? That’s where grabbing the coordinates of the surrounding pixels comes in handy. This post is all about how to do just that using ee.Geometry.Point in GEE.

First, A Little Background…

Before we jump into the code, let’s make sure we’re all on the same page.

• ee.Geometry.Point: This is GEE’s way of saying, “Hey, I’ve got a point on Earth!” You give it the longitude and latitude, and boom, you’ve got your spot.
• Pixels and Coordinates: Satellite images are made of pixels, right? Each one is like a little square on the ground, and it has its own address (geographic coordinates). The image resolution tells you how big each square is.
• Neighborhood: This is just a fancy way of saying “the pixels around my point.” Usually, we’re talking about a little window, like a 3×3 grid, with our point smack-dab in the center.

Cracking the Code: How to Snag Those Surrounding Pixel Coordinates

Okay, so GEE doesn’t have a big red button that says “Gimme surrounding pixels!” But, with a little cleverness, we can totally make it happen. Here are a couple of tricks I’ve used:

1. The Buffer-and-Reproject Shuffle

This is like drawing a circle around your point, turning it into a square-ish shape, and then asking GEE to give you all the pixel coordinates inside.

• Buffering: Use the buffer() command to draw that circle. The size of the circle depends on how big you want your neighborhood to be and the image resolution. Imagine you want a 3×3 window on an image where each pixel is 30 meters wide. You might buffer by 45 meters (1.5 pixels in each direction).
• Polygon Conversion: Now, we need to turn that circle into something GEE can easily work with – a polygon.
• Pixel Coordinate Image: This is where we create an image that stores the longitude and latitude of every single pixel. We use ee.Image.pixelLonLat() for this.
• Reduce Region: Finally, we use reduceRegion() to grab the latitude and longitude values from our pixel coordinate image, but only for the area inside our buffered polygon. Think of it as saying, “Hey GEE, give me the coordinates of all the pixels within this shape!”

2. The Manual Calculation Hustle (Python Style)

If you’re a Pythonista, you can get your hands dirty and calculate those coordinates yourself.

• AOI Definition: First, you define an Area of Interest (AOI) around your point. This is basically the square where you want to find the surrounding pixels.
• Coordinate Adjustment: Then, you do a little math. You tweak the latitude and longitude values based on the image’s pixel size to figure out the exact corners of those surrounding pixels.
• Polygon Creation: Finally, you create an ee.Geometry.Polygon object using those adjusted coordinates.

Let’s See It in Action (JavaScript)

Here’s that buffer-and-reproject method in JavaScript code:

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