Changing climate (desertification) and economic conditions have meant that a lot of people have given up their nomadic lifestyle and moved to cities or their outskirts (mostly Ulaanbaatar). They often are reluctant to do so, it's a big step, and they often hope it is a temporary one.

They set up their yurts not only because of housing shortages, but many are also hesitant to move into apartments or other permanent structures as it's seen as the last step in giving up this nomadic lifestyle. Often they are setting up their yurts next to permanent structures, either because they are living in the 'yard' of relatives or to expand their residences and stay connected to their culture.

You can see examples of this in the first images.

https://taginfo.geofabrik.de/asia:mongolia/tags/building=ger

I'm also guessing your model doesn't handle yurts that are on the border of a tile.

Finally, that's a much smaller number than I expected for a country of 3 million.

I'm curious what the topology/architecture of the DL model is like. And are there better ways to approach this problem?

For that money, you get a well-isolated easily movable tiny house in a country where you are allowed to settle everywhere (but if you have 2000 sheep with you, you should better discuss the usage of the pastureland with the locals) without paying rent (outside the city).

Choosing a ger for housing is not only about tradition and culture. It is quite rational in that situation.

This is anti-information. People reading this uncritically will come away with completely wrong ideas about the number of yurts in Mongolia, about machine learning algorithms, about data science in general.