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[[File:Portland3HullsLowest.png|right|300px]] An obvious alternative approach is to use the first time (lowest level) that there are three hulls. There is a big difference in the layer numbers for this. See the queries below. Essentially, the HCA algorithm often takes an original hull apart and then takes the resulting hulls apart, giving a quadratic for hull count again layer. But, as is apparent in the image, this leads to big areas that would only be good for overlap analysis and not for identifying individual clusters.
 
--Lowest,highest, and lowest-highest, and first-after-peak level where there are three hulls
print myDict["Houston_TX"];
[-95.836717, -95.014608, 29.515925, 30.155908]
 
Useful place data:
*The Sears Building is at 29.8055662,-95.7145812 [https://www.google.com/maps/place/Sears/@29.8055662,-95.7145812,10z/data=!4m8!1m2!2m1!1ssears+building+Houston,+TX!3m4!1s0x8640bf70f4999093:0xedfec0ea6b614672!8m2!3d29.7342449!4d-95.3822737]
*The four corners of the innovation corridor are:
**100 Hogan St Houston, TX 77009 29.774004, -95.367127
**Second Ward Houston, TX 29.759421, -95.346044
**Orange Lot Houston, TX 77054 29.682241, -95.403403
**Buffalo Speedway Houston, TX 77025 29.695301, -95.426753
===Image Analysis===

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