[Background] Brownfield regeneration constitutes a critical avenue for revitalizing existing land resources and promoting high-quality urban development. Over the past twenty-five years, considerable scholarly contributions have emerged within the field of brownfield regeneration research in China. Nonetheless, although existing studies furnish robust micro-level empirical evidence, there is a deficiency in a systematic synthesis of the long-term, large-scale research landscape. Traditional literature reviews have predominantly relied on word-frequency statistics or qualitative summaries, falling short of revealing spatiotemporal patterns of research evolution or the connections among academic interests, policy frameworks, and economic and ecological dimensions. [Objective] This study aims to comprehensively map the knowledge landscape of brownfi eld regeneration research within China. It seeks to identify the characteristics and logical shifts of research hotspots, trace the evolutionary trajectories of research paradigms, and reveal the spatiotemporal evolution patterns of research objects. The findings are intended to inform future research directions and spatial governance practices. [Methods] Based on 2 744 relevant publications sourced from CNKI between 2000 and 2025, this study employs a scoping review methodology following the PRISMA-ScR standard, combined with VOSviewer and ArcGIS. An analytical framework is constructed spanning three dimensions: bibliometric analysis, research paradigms and key objects, and spatiotemporal evolution. Specifi cally, keyword co-occurrence networks reveal knowledge clusters; kernel density and standard deviational ellipse analyses quantify spatial distribution patterns; and nighttime light intensity, road density, and wilderness degree indices characterize the economic, social, and ecological attributes of research locations. [Results] Key fi ndings include: (1) Research hotspots demonstrate an expansion pattern from emblematic case studies toward diversifi ed governance approaches across a broader spectrum. The fi eld has evolved through four stages: emergence (2000–2010),steady growth (2011–2015), explosive expansion (2016–2020), and high-level stabilization (2021–2025), which are closely aligned with major policy milestones. Three primary clusters have been identifi ed: industrial heritage and urban renewal, abandoned mines and ecological restoration, and technical methodologies. High-profi le projects have progressively transitioned from landscape design icons to cultural and creative parks, and subsequently to exemplars of comprehensive urban governance. (2)The research paradigm has transitioned from qualitative description to quantitative and empirical analysis. Research perspectives have shifted from space-dominated to multi-dimensional collaboration encompassing ecological, economic, technical, social, cultural-artistic, and spatial perspectives. Three distinct knowledge fl ow paths emerge: culture- and society-driven spatial regeneration (industrial brownfi elds), ecology- and technology-driven remediation (mining brownfi elds), and comprehensive benefi t evaluation for decision-making. (3) The spatial distribution exhibits patterns of fl uctuating expansion, stable directional orientation, and a persistent westward shift. Projects are predominantly clustered east of the Hu Line, with signifi cant agglomerations in major city clusters, gradually expanding toward the Yellow River Basin and central-western China. The spatial center of gravity consistently migrates northwestward. Concurrently, the locational characteristics of research objects have shifted from “economic-social” centers toward “ecological” centers, refl ecting a transition from capital-driven models to territory-wide comprehensive remediation. [Conclusion] China’s brownfi eld regeneration research has achieved remarkable progress. To further support ecological civilization and promote the high-quality development of new urbanization, future research should prioritize three directions: deepening investigations of underrepresented regions such as central and western China and special brownfi eld types; establishing multi-dimensional dynamic evaluation systems and systematic collaborative governance paradigms integrating ecological restoration, social equity, and economic sustainability throughout the full life cycle; and deepening interdisciplinary integration with digital and intelligent technologies to develop smart decision-support systems and facilitate the transformation of brownfi elds from spatial liabilities to new drivers of urban productivity.