Component-Level Residential Building Material Stock Characterization Using Computer Vision Techniques.

Residential building material stock constitutes a significant part of the built environment, providing crucial shelter and habitat services. The hypothesis concerning stock mass and composition has garnered considerable attention over the past decade. While previous research has mainly focused on the spatial analysis of building masses, it often neglected the component-level stock analysis or where heavy labor cost for onsite survey is required. This paper presents a novel approach for efficient component-level residential building stock accounting in the United Kingdom, utilizing drive-by street view images and building footprint data. We assessed four major construction materials: brick, stone, mortar, and glass. Compared to traditional approaches that utilize surveyed material intensity data, the developed method employs automatically extracted physical dimensions of building components incorporating predicted material types to calculate material mass. This not only improves efficiency but also enhances accuracy in managing the heterogeneity of building structures. The results revealed error rates of 5 and 22% for mortar and glass mass estimations and 8 and 7% for brick and stone mass estimations, with known wall types. These findings represent significant advancements in building material stock characterization and suggest that our approach has considerable potential for further research and practical applications. Especially, our method establishes a basis for evaluating the potential of component-level material reuse, serving the objectives of a circular economy.

The intrinsic cybernetics of large complex systems and how droughts turn into floods.

The cyber-physical nature of engineering systems requires the smooth integration of decision making across soft and hard infrastructure. This need is common to any systems where decision making considers multiple complex systems such as the climate, the natural and built environment, and the dynamics of large organisations. As an example, in the Anthropocene, acute droughts and floods cannot only be imputed to more extreme variations of the climate patterns, but also to the alteration of the habitable environment and of the resources that support it, hence to their governance and management. In this discussion paper we present arguments about the extent to which the natural environment is modified to support urbanisation. We expose the cyber-physical nature of large infrastructure systems taking as an example the events of the 2011 Brisbane flood and the operations of the damming system of the river Brisbane. Using literature resources and data, we show how flood defence devices had to provide for a population of almost 2 million people, while being engineered when the population was less than one million, with increase in water withdrawal mainly due to residential utilities. We show how the cyber-physical aspects of the problem materialised in moth-long delays in the governance and management structure and made the flood event transcend the boundary of a purely climatic or engineering incident. Looking beyond the Brisbane example, our conclusions point at overcoming the discontinuity between operation, management and political layers when operating on cyber-physical systems such as freshwater networks.

On the use of random graphs in analysing resource utilization in urban systems.

Urban resource models increasingly rely on implicit network formulations. Resource consumption behaviours documented in the existing empirical studies are ultimately by-products of the network abstractions underlying these models. Here, we present an analytical formulation and examination of a generic demand-driven network model that accounts for the effectiveness of resource utilization and its implications for policy levers in addressing resource management in cities. We establish simple limiting boundaries to systems' resource effectiveness. These limits are found not to be a function of system size and to be simply determined by the system's average ability to maintain resource quality through its transformation processes. We also show that resource utilization in itself does not enjoy considerable size efficiencies with larger and more diverse systems only offering increased chances of finding matching demand and supply between existing sectors in the system.