Rapid urban expansion is a complex phenomenon that propels social, economic, resource and environmental footprints. Local governments face many challenges towards sustainable urban neighbourhood development. Sustainable development was popularized as a concept by the Brundtland Commission to “meets the needs of the present without compromising the ability of future generations to meet their[s]” Since then many notable efforts have been made to develop strategies for sustainable development like the “2030 Agenda” that specifies 17 Sustainable Development Goals (SDGs) to ensure social cohesion, environmental protection, and worldwide prosperity. However, success of these strategies largely depends on local governments’ polices and planning towards sustainable development. Since 21st century, many Neighbourhood Sustainability Assessment (NSA) tools like Leadership in Energy and Environmental Design for Neighbourhood Development (LEED-ND) and Building Research Establishment Environmental Assessment Method Communities (BREEAM Communities) have been developed and applied by many developed countries. Focus has now shifted from evaluating single buildings (micro-scale) to neighbourhoods and cities (meso and macro scale) using multi criteria assessments. Existing NSA tools use traditional triple bottom line approach and are non-spatial. This study explores the possibility of assessing neighbourhoods by linking five capitals model (FCM) to sustainable development goals (SDGs). FCM based NSA considers maintenance of five major stocks (natural, social, human, financial and manufactured) in a neighbourhood and evaluates flow of these stocks using indicators that are used to achieve SDGs. Geographic information systems (GIS) is integrated to collect high resolution data and discover spatial differences on heat maps. The developed method was applied to Sha Tin neighbourhood in Hong Kong. Results highlight that central parts of Sha Tin show poor performance while northern parts show high performance and an apparent distinction between private and public housing was found. Heat maps generated using ArcGIS identified priority intervention areas in the neighbourhood that need much attention.