The project EAST-CITIES develops strategies and planning tools for the sustainable development of an urban system. EAST-CITIES offers a systemic understanding of the dependencies between different settlement types and their resource consumption. Based on a data-driven analyses, (im-)material flows of resources can be optimized. The LUH-led subproject "Data" aims at providing a joint knowledge base (for example using methods of web mining and machine learning) to facilitate the usage by the interdisciplinary research communities in EAST-CITIES.

EAST-CITIES pursues the integrated analysis of settlement patterns, traffic networks, infrastructural systems, value creation, energy-, resource and land consumption, land use and planning systems in an integrated, regional, functional and systemic way. The project EAST-CITIES builds on seven subprojects (SP). Each SP will be carried out by a Chinese-German cooperation.

SP NETWORK guarantees project continuity, local presence and knowledge transfer.

SP TOPOI identifies and typifies existing and planned settlement types and patterns which will be successively enriched.

SP MOBILITY analyses cross-scale, mobility dependencies between settlement types and different usage scenarios.

SP LAND develops productive land uses in peri-urban areas in order to balance the advantages and disadvantages between urban and rural areas, the mitigation of climate change, the production of food and the preservation of cultural identity.

SP LABOUR investigates the possibilities of local recycling management by means of urban factories. SP WATER addresses the use of substances bound in (waste) water in local recycling management.

In SP RESSOURCES, the resource requirements of the different settlement types are identified in their multiple dependencies. TP SCENARIO integrates the various findings into scenarios across scales and sectors.

SP DATA acts as cross-cutting work package providing the means to gather, extract, link, process and analyze required urbanization data of all SPs. Thus, throughout initial stages of the project, the focus is on understanding data needs as well as analytical questions to be answered by the data. Throughout later stages, techniques from web mining will be deployed to enrich these data. Data fusion and integration will facilitate a coherent view on heterogeneous data while machine learning models will facilitate the analysis and evaluation according to research questions relevant to EAST-CITIES.