Urbanization is arguably the most dramatic form of highly irreversible land transformation. While urbanization is a worldwide
phenomenon, it is exceptionally dynamic in India, where unprecedented urban growth rates have occurred over the last 30 years. In
this uncontrolled explosive situation city planning lacks of data and information to measure, monitor, understand urban sprawl
processes. The analysis of such changes has become an important use of multitemporal remote sensing data. Using a time-series of
Landsat data to classify the urban footprints since the 1970s enables detection of temporal and spatial urban sprawl, redensification
and urban development in the explosively growing large urban agglomerations of the mega cities Mumbai, Delhi and Kolkata in
India. Combining gradient analysis with landscape metrics the spatiotemporal pattern of urbanization are quantified. Spatial
parameters are the absolute areal growth, urbanization rates, built-up densities, landscape shape index, edge density, patch density,
or largest patch index. The study aims to detect analogies and differences for spatial growth in Indian mega cities, cities in the same
cultural area at about the same development stage regarding absolute population. The results paint a characteristic picture of spatial
pattern gradients and landscape metrics of the three Indian mega cities
