Urban　open　spaces　provides　various　benefits　to　citizens,　but　the　thermal　environment　under　this　space　is　being　affected　by　the　accelerated　urbanization　and　global　warming.　Based　on　this,　this　paper　is　dedicated　to　conducting　research　on　improving　the　attractiveness　of　outdoor　environmental　spaces　and　improving　outdoor　thermal　comfort.　The　main　work　of　this　paper　is　first　to　propose　a　street　comfort　model　by　considering　both　environmental　and　climatic　factors,　which　is　trained　to　learn　using　indirect　data.　Secondly,　the　comfort　level　of　each　street　is　combined　with　the　frequency　of　non-motorized　trips　on　that　street　to　obtain　the　urgency　index　of　rectification　for　that　street　and　to　achieve　accurate　recommendations　for　urban　planning.　Considering　the　public　accessibility　of　the　data　in　the　paper　in　cities　across　China,　this　study　can　be　easily　deployed　to　other　cities　to　support　urban　planning　and　provide　useful　recommendations　for　improvement　of　urban　open　spaces.　©　2023,　The　Author(s),　under　exclusive　license　to　Springer　Nature　Switzerland　AG.