Urban　green　space　equity　relates　to　the　efficient　allocation　of　natural　resources　and　the　equalization　of　public　service　facilities.　Street　(road)　greenery　provides　substantial　ecological,　social　and　cultural　benefits.　Thus,　in　this　study,　a　subdistrict-level　evaluation　framework　for　the　fairness　of　the　spatial　distribution　of　street　greenery　was　proposed,　taking　a　case　study　within　the　Third　Ring　Road　of　Fuzhou　City　in　Fujian,　China.　Street　view　images　may　capture　the　green　information　in　a　vertical　dimension　for　the　indirect　representation　of　people＇s　perspective　on　the　ground.　The　green　view　index,　which　was　estimated　based　on　Baidu　Street　View　images,　was　employed　to　represent　the　urban　street　greenery,　and　the　results　were　combined　using　deep　learning　technology.　The　Gini　coefficient,　share　index　and　location　entropy　were　used　as　evaluation　indicators　for　the　fairness　of　the　spatial　distribution　of　the　street　green　view　index.　Furthermore,　this　framework　combined　socioeconomic　data　and　population　census　data　to　explore　the　correlation　among　socioeconomic　status,　age,　and　evaluation　index　at　the　subdistrict　level.　In　addition,　we　analyzed　street　greenery　distribution　inequalities　from　the　perspective　of　socioecological　justice.　The　results　showed　that　in　Fuzhou,　there　is　a　significant　correlation　among　the　Gini　coefficient,　green　view　index　and　socioeconomic　status.　In　addition,　subdistricts　with　a　lower　green　view　index　have　a　less　equitable　street　greenery　distribution,　people　with　low　socioeconomic　status　may　suffer　from　green　injustice,　and　seniors　have　a　lower　accessibility　to　street　green　space　than　people　with　the　average　social　status.　Our　analytical　approach　is　applicable　for　other　cities,　and　the　findings　are　useful　for　greenery　spatial　planning　processes　and　evaluating　construction　effects.