New dimensions of urban landscapes: The spatio-temporal evolution from a polynuclei area to a mega-region based on remote sensing data

• Turning the qualitative descriptions of the mega-region concept into a spatial one.
• EO-based large area and long-time multi-temporal classifications of urban patterns.
• Spatial metrics for measuring spatial patterns at three spatially different levels.
• Characterization of the evolution of a mega-region pattern by spatial features.
• Proofing the mega-region Hong Kong–Shenzhen–Guangzhou outdraws growth in mega-cities.

Currently our world is facing a migration process of a huge dimension – from rural to urban areas. In 1975 37.7% of the global population were urban dwellers, 1990 already 43%, today little over 50%, and in 2050 the expected number is 67.2%. This great process shapes new spatial urban landscapes, in dimension and pattern. In this study we aim at analyzing the spatial evolution of a once polynuclei urban area to a mega-region in a 35 years time frame. Using multi-temporal and multi-source satellite data we classify urban footprints of a mega-region – the Hong Kong–Shenzhen–Guangzhou mega-region in Southern China – for the years 1975, 1990, 2000 and 2011. Based on this geospatial data set we aim at turning the qualitative and fuzzy definitions of mega-regions into a physical concept. Furthermore, we suggest a set of spatial features potentially characteristic for the evolution of mega-regions. In particular we apply and develop a multiude of spatial metrics at three spatial levels, namely the entire mega-region, the hinterlands between different cities and the cities themselves. The result is a novel spatial approach to capture, measure and analyze new shapes of urban landscapes.