Abstract
Understanding the spatio-temporal dynamics of volumes of construction materials is becoming crucial for environmental sustainability and achieving long-term development goals. Whilst direct data collection is always the preferable option it is not always practical. This study presents a new methodology for quantifying national-scale material stocks in Malaysia using high-resolution Earth Observation (EO) data. The study includes construction materials; sand, crushed rock / gravel, bricks, tiles, and cement but particular focus is given to sand as it generates the greatest risks to the supply chain, the most significant environmental and social impacts and exhibits the most persistent data gaps. The study integrates EO-derived building footprint and elevation data with deep learning-based classification of building types and ages. Material Intensity coefficients, adapted from regional literature, are applied to estimate material volumes across ~ 9.1 million buildings. Results reveal that modern Malaysia’s building stock has consumed approximately 5.8 billion tonnes of construction materials. Modelled sand consumption shows a good correlation to reported national level production but only when the full value chain for sand, including transport and major infrastructure projects, are factored in. Demonstrating requirements for location specific knowledge when modelling for construction material use and the deficiencies of using simple proxies based on limited parts of the supply chain. This methodology offers a scalable mechanism for capturing data for construction material flows with a high spatial and temporal resolution when directly collected data is not available. It supports evidence-based policymaking for resource governance, circular economy planning, and mitigation of impacts from primary resource consumption.