Metropolitan Cartography: An Inventive Practice Tool for Caring Metropolitan Landscapes

To focus on issues of the resilient city on the metropolitan scale, it is important to understand the metropolitan city as a system that uses complementary actions to work with local projects for maintenance to preserve, improvement to increase, and transformation to grow, increasing the scale of local projects. Metropolitan City is a system that allows places to relate to each other in order to implement and care for metropolitan landscapes and their resources. To outline and give a spatial image to these relationships, the maps of Metropolitan Cartography are projects that identify the spatial components that make the landscapes dynamic, order spatial categories according to a new taxonomy for mapping the urban-rural interdependence of spaces, and structure gradients of tonal rhythms of landscapes that can be reprogrammed for new inventive patterns of land-use. Metropolitan Cartography (MC) is therefore, a methodology capable of interpolating spatial data in a new synthetic map for digital design practices. With MC maps, it is possible to spatialize new land-use patterns from the global to local scales by mapping open-source data obtained through data mining, data settings, and data semiotics following the metropolitan architecture design process. In particular, the Metropolitan Cartography experiment allows us to contextualize qualitative and quantitative open-source data, finding and highlighting implicit relationships between heterogeneous informative layers, which help to characterize the state of care and neglect of metropolitan landscapes at ‘southern latitudes’. Thus, the operational findings of Metropolitan Cartography maps for caring metropolitan landscapes are outlined as methodological steps that make visible spatial relationships not yet detectable on the ground, which can be shaped by interpolating geographical, social, and economic factors. The maps allow for stages of project design and practices through repeatable and scalable open-data processing, which allows and supports sequences of logical choices for metropolitan architecture projects.