Pixels on target
How many sensor pixels a coyote covers at a given distance. More pixels mean a clearer shape and a surer call on what you are looking at.
What it means
A digital or thermal image is made of pixels. An animal far away covers only a few of them; the same animal close up covers many. Pixels on target is that count. It turns three specs, pixel pitch, focal length and distance, into the question a hunter actually has: how big will the coyote be on my screen?
The math, simply
Each pixel sees a small angle of the scene: pixel pitch divided by focal length. A 12 µm sensor behind a 35 mm lens gives about 0.34 milliradians per pixel, which at 100 yards is a patch about 1.2 inches across. A coyote’s shoulder, about 22 inches tall, covers roughly 18 of those patches at 100 yards, 9 at 200 and 6 at 300. Double the distance and the count halves.
Notice what is missing: sensor resolution. A 384 and a 640 with the same pitch and lens put the same number of pixels on the coyote. The 640 shows more ground around it.
What it changes in the field
At around 18 pixels tall you see a clear coyote shape: ears, tail, the way it carries its head. At 6 you see a warm shape that could be a coyote, a fox or a big house cat. That difference decides whether you can shoot.
How we use it on this site
Each model page shows the coyote at 100, 200 and 300 yards with the shoulder height in pixels. The drawing is to scale, using a 36-inch coyote from nose to base of the tail. For digital night vision the same math works from field of view divided by sensor width, since makers rarely publish pitch.
Its limits
This is geometry, the best case. It assumes a broadside animal standing in the open, sharp focus, steady hands and good heat contrast. Fog, humidity, a warm night, brush, image processing and a coarse display all lower what you actually see. On digital night vision at night, sensor noise and the reach of the IR illuminator usually matter more than pixel count.