The first strategy in the stratified classification
was to spatially partition the entire landscape into urban and rural
subsets to be processed separately. The goal here was to suppress
the spectral confusion between urban impervious surfaces and
agricultural land that was fallowed or at a certain growth stage. The
landscape partition was done by using an urban mask created
through the use of road density. Specifically, we firstly generated
the road intersection density surfaces using road intersections
extracted from the street centerline data. Note that the road data
for 2000 and 2010 were derived from the ARC 2007 street centerline
data which were adjusted with the reference of the satellite
images acquired at the two years. Secondly, we determined the
threshold values iteratively that can mostly single out the urban
built-up area from the rural part for each road intersection density
surface. Any area with density values greater than the thresholds
was then grouped into the urban portion. Finally, we combined the
generated urban portion with street centerline buffers with varying
distance values by road levels to create the complete urban masks.
The area outside the urban mask boundary was defined as the rural
subset.