Higher speed impacts penetrate deep, but also cause the rock to melt. This fills in deeper craters, limiting the max depth a crater can be. There are still very deep huge craters, but these look more like big depressions than craters, because of how big they are. They are also themselves covered with craters usually, making their size and shape harder to see.
Because the diameter of the moon is 3474km, a difference of several kilometers would only amount to a fraction of a percent. So even though one crater is for example 10km deeper than another, relative to the size of the moon this is practically nothing. When viewing pics like these where the whole moon is visible, this matters.
The moon is a very uniform gray color and lacks the indicators our brain use to gauge depth. This makes it very hard to guess how deep the different craters are. You can see some craters have more shadows where others don't, but they are also different shapes and sizes and the lighting is different so it's hard to see.
There is also probably some part of the speeds of incoming stuff being within a certain range and the moonrocks being relatively uniform in materials, so the range of craters than can exists is probably limited. But I'm not certain how big of an factor this is and what the range is.
There are plenty of missions right now. China has landed a rover on the moon this month. And multiple countries have satellites in orbit around the moon. Nasa has their Lunar Reconnaissance Orbiter which takes very high resolution images of the moon all the time and these are publiced on their website.
This image does a good job at making me realize we have explored basically nothing on the moon. SO much more to explore, yet we act like there's no point trying to send more astronauts to the moon for decades. Please, increase NASA budget more.
Yeah. I'm half-drunk but the first thing that I thought was, "I could use some gyros. Preferably with a buttload of tzatziki". (The video is about gyroscopes though. Also cool. But not edible.)
This is what machine learning is useful for. Not to try to convince you that oranges are active and potatoes are passive, or to give you a thumbs up with 7~8 fingers. But to detect patterns and allow automation of repetitive tasks.
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