UREE

The construction and demolition of buildings in cities pose considerable risks in the urban environment. This study selected Fuzhou, Xiamen, and Quanzhou as three typical cases, to analyze and predict their changes on building stocks and waste generation under three alternative scenarios until the end of this century.

As the world’s top material consumer, China has created intense pressure on national or global demand for natural resources. Building an accurate material stocks and flows account of China is a prerequisite for promoting sustainable resource management. Existing material stocks and flows estimates conducted by scholars exhibit great discrepancies.

Urban Environmental Events and Tone data is collected from GDELT. This dataset  describes the environmental events of every countries and identifies the people, locations, organizations, themes, sources, emotions, counts, quotes and images driving our global environment every second of every day. Urban Environmental Events and Tone dataset stretches back to

A grid-level (~1km*1km) solid waste dataset has been created by coupling material flow analysis (MFA) and geographic information system (GIS) based on bottom-up (scaling-up) and top-down (scaling-down) approaches. The hybrid model performs well in stock and flow quantification of construction & demolition, electrical and electronic, hazardous, and municipal wastes.

We have developed a stock-driven metabolism model by coupling material flow analysis (MFA) and geographic information system (GIS) to quantify urban material stock and flows. We also create grid-level (~1km*1km) dataset including building footprint, level, height, vintage, structure, household, and construction material stock and flows.

Urban Population Dataset includes Real-time Population Density Data, etc.

Night Lights Data was collected from NASA.