Structural Urban Plans in five cities of Mozambique

TSPA, together with Vocação Técnica Lda, developed a Structural Urban Plan (Plano De Estrutura Urbana) a territorial management instrument that defined spatial organisation for the five municipalities of Alto Molocue, Boane, Gurue, Nhamatanda and Milange.

The project responded to the institutional decentralisation Mozambique undertook in 2014 in a context of rapid demographic growth and scarce institutional control on regulated land ownership.

Three of the project cities – Alto Molocue, Gurue, Milange – are located in one of the poorest and least developed provinces in the country, Zambezia. While Nhamatanda, situated in the Sofala province, was dramatically affected by a cyclone, and Boane, located within the region of the capital Maputo, recently sprawled encroached on Boane municipality forming the largest conurbation in the country.

This spatial planning tool, similar to our previous project PEU Sussundenga, employed a collaborative and participative decision-making process, enabling cooperation across private and the public stakeholders. The result of this approach led to empirical findings and more direct engagement of public institutions.

Shortage of existing planning material and the fragility of the local institutions posed additional challenges to plan future development based on the municipalities’ current dynamics. To address these challenges, the collection of comprehensive information relied mostly on the remote recruitment of open spatial data and in situ data collection through workshops and questionnaires.

The project developed a spatial data repository from open-source data from the international organisations The World Bank and UN-Habitat; the volunteering open data libraries, OSM and the intergovernmental space agencies NASA, ESA.

TSPA classified and analysed data retrieved from satellite images and geographic information tools producing not only a cognitive instrument but also development scenarios and design solutions. This data-driven approach encouraged the development of predictive models, then translated into tangible spatial solutions.