A Spatial Sufficiency Multifunctionality Framework for Sustainable Neighborhood Land Governance
Year: 2026
Type: article
Abstract: Urban sustainability governance has long been dominated by growth-oriented metrics that measure aggregate improvement without establishing whether neighborhoods provide enough for all residents without continuous territorial expansion or resource-intensive redevelopment. Drawing on the post-growth planning, sufficiency theory, spatial justice, land governance, and the adaptive planning literature, this paper proposes a Spatial Sufficiency Multifunctionality Framework (SSMF). SSMF is a provisional conceptual framework requiring empirical validation and aiming to reorient neighborhood land assessment from growth optimization to sufficiency thresholds. The framework organizes planning around five interconnected dimensions: social sufficiency, economic resilience without growth dependence, ecological resilience, spatial governance and land-use sufficiency, and institutional and participatory capacity. Each is operationalized through illustrative indicators, thresholds, and linked governance instruments. SSMF asks whether per-capita land use remains within ecological capacities and whether access to services, green space, and affordable space is equitably distributed. The framework is developed through a systematic scoping review of the literature on urban sustainability, land governance, and post-growth planning, and provides a diagnostic logic and a menu of governance instruments. By shifting the evaluative focus from “more” to “enough, equity distributed within neighborhood capacities,” SSMF offers a provisional architecture for understanding post-growth principles at the neighborhood scale.
Source: Land
DOI: 10.3390/land15081527
Author: Najmeh Mozaffaree Pour
Institutions: Tallinn University of Technology, University of Stavanger
Language: English
Subfield: Urban Studies
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W7203881248
