<b>Roadside Trees Species Selection Model for Environmental Health and Public Safety in MalaysiaRoadside Trees Species Selection Model for Environmental Health and Public Safety in Malaysia</b>

Selecting right tree species for roadside planting is crucial to balance environmental health with public safety concerns. Roadside trees as a part of urban green infrastructure have the potential to cope with some of these problems in urban environment and provide an array of services such as shade provision and aesthetic creation. Unfortunately, roadside trees are also acknowledged to render disservices. Damaged road surface, pedestrian walkway and underground utilities are a few instances of this. The wrong tree species planted at the wrong place can lead to significant environmental, social and economic consequences. The aim of this study is to develop roadside tree species selection model for reference to the local authorities. Two objectives are to determine additional attributes in urban roadside tree species selection and to examine the relationship between additional and similar attributes in landscape practices. This research employs mixed methods approaches consisting of both qualitative and quantitative approaches. An in-depth interview was conducted in four selected local authorities, namely Kuala Lumpur City Hall, Petaling Jaya City Council, Selayang Municipal Council, and Subang Jaya Municipal Council. The findings are validated by five registered landscape architects, revealing ten (10) additional attributes of root invasiveness and behavior, wood brittleness and branch drop risk, allergenic potential, growth rate and canopy management, compatibility with urban infrastructure, drought and pollution tolerance, fire resistance and flammability, wildlife attraction and pest management, aesthetic consistency and public perception, structural stability and wind resistance that influences the selection of roadside tree species in urban areas. These attributes were integrated into the roadside tree species selection model.