The UBASE project is a novel partnership that aims to transform our understanding of the Indian urban landscape.
By 2030, 60% of India’s population (590 million people) will be living in cities, putting immense pressure on urban infrastructure systems and requiring the construction of an additional 20 billion m2 of residential and 4 billion m2 of commercial accommodation.Understanding India’s urban building stock and its energy demands are critical to ensuring that carbon emissions are managed through this period of dramatic change.
Benchmarking is a crucial element of understanding the building stock energy consumption and its potential for improvement. Its correct application requires information about the characteristics of individual buildings, such as age, use type, and building materials. Such data exists in contextual data sets like those held for property taxation.
A lack of a consistent geo-coded address system makes it difficult to link these data to spatial datasets such as building geometries and locations. The UBASE project proposes a novel partnership to transform our understanding of the urban landscape. UBASE applies address disambiguation to geolocate ~1million addresses in Ahmedabad’s municipal property tax records. This data will be linked with the iNUMBER ultra-high-resolution 3D model of the city to classify the urban building stock by floor area, use type, age, and model energy consumption. In parallel, UBASE will work with commercial partners to develop a graduated benchmarking system to identify and prioritize critical decarbonization pathways for Ahmedabad.
The challenge of addressing disambiguation is common in all cities, and the methods developed in this project will apply to the whole country. In addition, the potential value of a data-rich 3D model of the city extends far beyond energy consumption. It has enormous potential for transport planning, emergency response planning, and pandemic management. Working with C40 Cities, we explore the potential for application to other cities across India.
Work package lead. Design and implementation of the database structure for the project, including liaison with Bentley Systems. Development of joining algorithms for municipal and geospatial datasets, including liaison with Delhivery Ltd. (SE). Classification of the building stock by age, use type, construction type to enable benchmarking processes in WP1
Energy modeling supports the development of priority decarbonization pathways
Work package lead. Co-development and delivery of a module on urban building energy modeling