Living　vegetation　volume　(LVV)　can　objectively　and　accurately　reflect　the　urban　greenery　quality,　and　provide　a　reliable　data　foundation　for　the　quantitative　study　aiming　to　reveal　the　mechanisms　underlying　urban　greenery　ecological　functions.　According　to　the　characteristics　of　dispersion　and　small　scale　of　unit　affiliated　green　space,　we　proposed　a　LVV　estimation　scheme　for　such　urban　green　space,　which　included　data　acquisition,　processing,　entity　segmentation,　classification,　single　tree　canopy　extraction,　and　LVV　calculation.　First,　point　cloud　data　was　obtained　with　a　backpack　LiDAR　system,　and　the　ground　point　clouds　were　eliminated　by　a　multi-scale　algorithm.　Second,　the　Density　Based　Spatial　Clustering　of　Application　with　Noise　(DBSCAN)　algorithm　was　used　to　cluster　the　non-ground　point　clouds,　and　density　feature-based　competitive　algorithm　was　used　to　re-segmented　for　the　overlapping　area　to　generate　independent　objects.　Third,　the　PointNet++　network　model　was　used　to　extracted　plant　point　clouds.　Then,　the　canopy　point　clouds　were　extracted　using　the　similarity　of　principal　direction　between　neighboring　points　and　distribution　density　of　branch　and　leaf　points.　Finally,　the　LVV　of　individual　tree　canopy　was　calculated　by　the　convex　hull　method,　and　then　the　LVV　of　the　accessory　greenland　was　summed　up.　Taking　a　science　and　technology　park　as　an　example,　its　total　LVV　was　21034.95　m3,　among　which　the　number　of　mango　trees　was　the　highest,　and　the　total　LVV　was　the　largest　(4868.64　m3,　accounting　for　23.2%).　The　tree　species　with　the　largest　LVV　per　plant　was　Terminalia　neotaliala　tree,　with　an　average　of　120.37　m3　per　plant.　The　relative　error　between　LVV　of　trees　estimated　by　this　scheme　compared　with　traditional　method　and　convex　hull　method　was　10.7%-33.7%　and　2.7%-16.0%,　with　average　value　of　20.9%　and　8.7%,　respectively.　This　scheme　could　make　full　use　of　the　characteristics　of　the　three-dimensional　point　cloud　and　use　a　convex　polyhedron　to　simulate　the　original　form　of　the　tree　crown,　which　was　more　consistent　with　the　actual　situation　of　trees.　The　measurement　and　estimation　solution　of　the　LVV　provided　new　ideas　for　rapid　and　accurate　estimation　of　urban　LVV.　©　2022,　Science　Press.　All　right　reserved.