[defrost]

If I skimmed the linked source and https://hls.gsfc.nasa.gov/algorithms/ correctly the models are trained on 10m x 10m ( ~ 30 ft x 30 ft ) cells.

That may not be fine enough resolution in the source data to resolve parking lots Vs undeveloped areas to the degree you require.

The alternatives are to use the nature of the models (trained to lock in on multispectral signatures) on finer source data - which may limit your options about the globe, OR

to use urban data from city land agencies which have maps from low level air photo surveys with resolution down to 10 cm (+/-) and GIS land boundaries which are often classified via metadata.

Air photos are not multispectral (usually) so you won't have access to IR bands etc.

You can get coarse city growth figures globally from sat data going back to TERRA (launched 1999 IIRC) and fine grained air photo data from well off cities going back to (say) the mid 80s (and longer for wet negatives).