Classification of natural environments to assess positive health effects of exposure in different regions of Europe

Abstract

Background: Indications exist that close contact with nature brings benefits to human health and well-being. The PHENOTYPE project will investigate the interconnections between exposure to natural outdoor environments and human health and wellbeing in North West, South and East Europe. Inconsistency and variation in indicators for green or natural space have often made it difficult to compare results from different studies, and to translate research to better integrate human health needs into land use planning and green space management. Aims: Create a consistent classification of natural environments across partner countries by combining conventional mapping with remote sensing data and aerial photography, and using considerable stakeholder engagement to minimize the potential inconsistencies. Exposure indicators will be linked with participant data to explore health effects of different types of natural environment (in different populations) and underlying mechanisms related to stress reduction/restorative function, physical activity, social interaction/cohesion and exposure to environmental hazards. Methods: The classification of natural environments will be conducted at three levels: 1. Europe-wide, using secondary data and remote sensing analysis. 2. Within participating countries, using locally-held secondary data: a. A metadata collection exercise to identify consistent classifications. b. A review of existing classifications used by stakeholders. c. Derived GIS measures. 3. ‘Quality’ audit of natural environments (primary data) Results and conclusions: The provisional hierarchical classification of natural environments (both green and blue) comprises four levels of typology, which can be further differentiated by the size, purpose, presence of water and level of access. It can also be combined with ‘quality’ items derived from a natural space audit tool and existing local data such as traffic [...].