Given data points with longitude, latitude, and a third property value of this point. How can I cluster points into groups (geographical sub-regions) based on the property value? I searched by google and figured out that this problem seems to be called "spatial constrained clustering" or "regionalizing". However, I am not familiar with handling geographical data and haven't get an idea about what kind of algorithms are good, and which python/R packages are good for this task.
To give a more intuitive idea about what I want, let's say my data scatter plots are as following: 
So each dot is a point, x is longitude, y is latitude, and colormap shows whether the value is big or small. I want to divide those points into sub regions/groups/clusters based on location and similarity of values. Like the following (it is not exactly what I want, just to show a intuitive idea.): 
So how can I achieve this?
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