The authors argue that linking in time and space data on search queries and discussions in social networks with remote sensing data and municipal statistics provides valuable information about actual problems in urban agglomeration development. Examples of models for an analysis of such information and model-aided results related to recreational needs and environment pollution confirmed usefulness of linking data for evidence-based policy making in agglomeration development. As a result of the implementation of the models, three goals were achieved: the working ability of the general approach for environmental assessment of agglomerations was tested; new informative results were obtained, characterizing the dynamics of ecological-economic objects of the coastal areas of the Gulf of Finland and the relationship between indicators of the state of these objects; new approaches to integrating data that were not previously used together (remote sensing data, official data from municipal statistics, environmental monitoring data, as well as online population activity data) were tested.