With the world’s second largest population and its enormous urban growth, India is facing a great number of challenges, such as overcrowding, environmental pollution and depletion of resources. The engineering, architecture and urban planning sectors are growing in importance to foster sustainable development and, as a result, mapping technologies are also playing a crucial role.
Geospatial information is a valuable source of data to develop rigorous and cost-effective topographic mapping and 3D modeling of buildings and cities, for urban development applications. Better mapping results in better urban management by helping detect infractions, improving accountability and streamlining planning processes. Digital Elevation Models (DEMs) and 3D models are key tools for hydrological modeling, topographic mapping and terrain stability assessment, allowing to monitor urban growth and surface movements and changes and supporting the prevention and quick detection of undesired effects deriving from constructions. DEMs are also very useful for risk and vulnerability to extreme weather events assessment, and for the identification of the most appropriated locations for new buildings and infrastructures.
Flood risk in Hyderabad
Spread over 650 square kilometers along the Musi River banks, Hyderabad grew from about 1 million inhabitants in 1951 to about 10.2 million in 2016, becoming India’s fourth most crowded city. As population continues rising, the shortage of planned affordable housing have forced thousands of people to live in unauthorized housing. Moreover, rapid urbanization has altered the natural drainage patterns, leading to flooding and waterlogging even after mild showers.
The Earth Observation Company Deimos Imaging carried out a multi-scale and multi-temporal urban analysis of Hyderabad’s metropolitan area, to evaluate its urban structure and environment and to identify trends and patterns that would assist in developing new strategies for sustainable urban development.
In particular, a multitemporal analysis of Deimos-1 and Landsat-5 data ranging from 1988 to 2017, enabled to monitor the entire metropolitan area and its extension detecting where the main changes occurred. Then, the Very High Resolution (VHR) Satellite Deimos-2, was used to provide highly detailed information on the structural characteristics of the urban morphology. And last, but not least, Deimos Imaging’s DEM provided essential information on terrain elevation, useful for topographic mapping and hydrological modeling.
Understanding urban sprawl
Deimos-1, the very first Earth Observation Spanish satellite, has been continuously providing data since 2009. With a spatial resolution of 22 m, a 650 km swath and a 3 days revisit frequency, it enables to timely monitor urban sprawl and the spatial direction of urban development on large metropolitan areas. The satellite’s 3 spectral channels (red, green, NIR) were designed to be compatible with the ones of the Landsat series, allowing full compatibility and, therefore, enabling a seamless analysis of extended time series.
In this study, Deimos-1 data of Hyderabad from the years 2011 and 2017 were used together with resampled 22 m Landsat 5 data from 1988 and 1999. The images were processed combining the near infrared, red and green bands. In this band combination, vegetation appears red, allowing an easy differentiation between vegetation-covered soil and urbanized land. Figure 1 shows: Landsat 5 images for the years 1988 (a), 1999 (b); Deimos-1 images for the years 2011 (c) and 2017 (d). A careful image analysis was carried out to detect the main areas of changes of the city from 1988 to 2017. In particular, significant new infrastructures, including the Rajiv Gandhi International Airport on the bottom left side of the images, the Outer Ring Road around the city and the new urban areas in the western metropolitan area, were detected.
After that, Deimos-2 Very High Resolution (VHR) 75 cm imagery was used to identify small-scale changes and heterogeneous urban structures of Hyderabad, enabling a highly detailed analysis of the urban morphology, including the detection of single houses and infrastructure networks.