{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T21:42:51Z","timestamp":1771105371253,"version":"3.50.1"},"reference-count":48,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2018,11,7]],"date-time":"2018-11-07T00:00:00Z","timestamp":1541548800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Street trees are an important part of urban facilities, and they can provide both aesthetic benefits and ecological benefits for urban environments. Ecological benefits of street trees now are attracting more attention because of environmental deterioration in cities. Conventional methods of evaluating ecological benefits require a lot of labor and time, and establishing an efficient and effective evaluating method is challenging. In this study, we investigated the feasibility to use mobile laser scanning (MLS) data to evaluate carbon sequestration and fine particulate matter (PM2.5) removal of street trees. We explored the approach to extract individual street trees from MLS data, and street trees of three streets in Nantong City were extracted. The correctness rates and completeness rates of extraction results were both over 92%. Morphological parameters, including tree height, crown width, and diameter at breast height (DBH), were measured for extracted street trees, and parameters derived from MLS data were in a good agreement with field-measured parameters. Necessary information about street trees, including tree height, DBH, and tree species, meteorological data and PM2.5 deposition velocities were imported into i-Tree Eco model to estimate carbon sequestration and PM2.5 removal. The estimation results indicated that ecological benefits generated by different tree species were considerably varied and the differences for trees of the same species were mainly caused by the differences in morphological parameters (tree height and DBH). This study succeeds in estimating the amount of carbon sequestration and PM2.5 removal of individual street trees with MLS data, and provides researchers with a novel and efficient way to investigate ecological benefits of urban street trees or urban forests.<\/jats:p>","DOI":"10.3390\/rs10111759","type":"journal-article","created":{"date-parts":[[2018,11,7]],"date-time":"2018-11-07T10:32:07Z","timestamp":1541586727000},"page":"1759","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":49,"title":["Evaluating Carbon Sequestration and PM2.5 Removal of Urban Street Trees Using Mobile Laser Scanning Data"],"prefix":"10.3390","volume":"10","author":[{"given":"Yingyi","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0866-6678","authenticated-orcid":false,"given":"Qingwu","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"},{"name":"Nanjing Institute of Environmental Sciences, Ministry of Environmental Protection, Nanjing 210042, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6634-9593","authenticated-orcid":false,"given":"Haidong","family":"Li","sequence":"additional","affiliation":[{"name":"Nanjing Institute of Environmental Sciences, Ministry of Environmental Protection, Nanjing 210042, China"},{"name":"Key Laboratory for National Geography State Monitoring (National Administration of Surveying, Mapping and Geoinformation), Wuhan University, Wuhan 430079, China"}]},{"given":"Shaohua","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}]},{"given":"Mingyao","family":"Ai","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,11,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1081","DOI":"10.1007\/s11252-017-0655-4","article-title":"Correlation between the geometrical characteristics of streets and morphological features of trees for the formation of tree lines in the urban design of the city of Orestiada, Greece","volume":"20","author":"Rantzoudi","year":"2017","journal-title":"Urban Ecosyst."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1016\/S0269-7491(01)00214-7","article-title":"Carbon storage and sequestration by urban trees in the USA","volume":"116","author":"Nowak","year":"2002","journal-title":"Environ. Pollut."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/S0169-2046(98)00113-3","article-title":"A planning strategy to augment the diversity and biomass of roadside trees in urban Hong Kong","volume":"44","author":"Jim","year":"1999","journal-title":"Landsc. Urban Plan."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1007\/s00704-015-1409-y","article-title":"Temperature and human thermal comfort effects of street trees across three contrasting street canyon environments","volume":"124","author":"Coutts","year":"2016","journal-title":"Theor. Appl. Climatol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.rse.2014.03.018","article-title":"Urban tree species mapping using hyperspectral and lidar data fusion","volume":"148","author":"Alonzo","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1016\/j.ufug.2015.06.006","article-title":"Assessing street-level urban greenery using Google Street View and a modified green view index","volume":"14","author":"Li","year":"2015","journal-title":"Urban For. Urban Green."},{"key":"ref_7","first-page":"43","article-title":"Urban street tree plantings: Identifying the key requirements","volume":"156","author":"Pauleit","year":"2003","journal-title":"Proc. Inst. Civ. Eng.-Munic. Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.landurbplan.2017.05.010","article-title":"Green streets\u2212Quantifying and mapping urban trees with street-level imagery and computer vision","volume":"165","author":"Seiferling","year":"2017","journal-title":"Landsc. Urban Plan."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.landurbplan.2011.07.003","article-title":"Estimating the removal of atmospheric particulate pollution by the urban tree canopy of London, under current and future environments","volume":"103","author":"Tallis","year":"2011","journal-title":"Landsc. Urban Plan."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1016\/j.scitotenv.2015.06.142","article-title":"Assessing visual green effects of individual urban trees using airborne Lidar data","volume":"536","author":"Chen","year":"2015","journal-title":"Sci. Total Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.landurbplan.2010.11.004","article-title":"A framework for developing urban forest ecosystem services and goods indicators","volume":"99","author":"Dobbs","year":"2011","journal-title":"Landsc. Urban Plan."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1016\/j.ufug.2015.02.013","article-title":"Efficiency differences of roadside greenbelts with three configurations in removing coarse particles (PM10): A street scale investigation in Wuhan, China","volume":"14","author":"Chen","year":"2015","journal-title":"Urban For. Urban Green."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1016\/j.envpol.2013.03.050","article-title":"Modeled PM2.5 removal by trees in ten US cities and associated health effects","volume":"178","author":"Nowak","year":"2013","journal-title":"Environ. Pollut."},{"key":"ref_14","first-page":"36","article-title":"The role of ecosystem services in climate and air quality in urban areas: Evaluating carbon sequestration and air pollution removal by street and park trees in Szeged (Hungary)","volume":"23","author":"Kiss","year":"2015","journal-title":"Morav. Geogr. Rep."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1016\/j.ufug.2016.04.010","article-title":"Air pollution removal by trees in public green spaces in Strasbourg city, France","volume":"17","author":"Selmi","year":"2016","journal-title":"Urban For. Urban Green."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1080\/10549811.2016.1265455","article-title":"Urban forest assessment in Bangkok, Thailand","volume":"36","author":"Intasen","year":"2017","journal-title":"J. Sustain. For."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.envpol.2013.03.019","article-title":"Carbon storage and sequestration by trees in urban and community areas of the United States","volume":"178","author":"Nowak","year":"2013","journal-title":"Environ. Pollut."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"347","DOI":"10.48044\/jauf.2008.048","article-title":"A ground-based method of assessing urban forest structure and ecosystem services","volume":"34","author":"Nowak","year":"2008","journal-title":"Arboric. Urban For."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1016\/j.isprsjprs.2014.12.021","article-title":"Effects of LiDAR point density and landscape context on estimates of urban forest biomass","volume":"101","author":"Singh","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.rse.2017.12.030","article-title":"An above-ground biomass map of African savannahs and woodlands at 25m resolution derived from ALOS PALSAR","volume":"206","author":"Bouvet","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.rse.2015.02.023","article-title":"Estimating aboveground biomass and leaf area of low-stature Arctic shrubs with terrestrial LiDAR","volume":"164","author":"Greaves","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"546","DOI":"10.1016\/j.ufug.2013.06.002","article-title":"Tree mapping using airborne, terrestrial and mobile laser scanning\u2014A case study in a heterogeneous urban forest","volume":"12","author":"Holopainen","year":"2013","journal-title":"Urban For. Urban Green."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1016\/j.biombioe.2015.07.015","article-title":"Estimation of pruning biomass of olive trees using airborne discrete-return LiDAR data","volume":"81","author":"Estornell","year":"2015","journal-title":"Biomass Bioenergy"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"7110","DOI":"10.3390\/rs6087110","article-title":"Using small-footprint discrete and full-waveform airborne lidar metrics to estimate total biomass and biomass components in subtropical forests","volume":"6","author":"Lin","year":"2014","journal-title":"Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Cao, L., Gao, S., Li, P., Yun, T., Shen, X., and Ruan, H. (2016). Aboveground biomass estimation of individual trees in a coastal planted forest using full-waveform airborne laser scanning data. Remote Sens., 8.","DOI":"10.3390\/rs8090729"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.rse.2017.03.017","article-title":"Area-based vs tree-centric approaches to mapping forest carbon in Southeast Asian forests from airborne laser scanning data","volume":"194","author":"Coomes","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"626","DOI":"10.1016\/j.rse.2016.09.006","article-title":"Large-scale estimation of aboveground biomass in miombo woodlands using airborne laser scanning and national forest inventory data","volume":"186","author":"Ene","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.rse.2017.12.020","article-title":"Large-area mapping of Canadian boreal forest cover, height, biomass and other structural attributes using Landsat composites and lidar plots","volume":"209","author":"Matasci","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.isprsjprs.2012.10.003","article-title":"Individual tree biomass estimation using terrestrial laser scanning","volume":"75","author":"Kankare","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1864","DOI":"10.3390\/rs2081864","article-title":"From TLS to VLS: Biomass estimation at individual tree level","volume":"2","author":"Lin","year":"2010","journal-title":"Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.isprsjprs.2015.04.011","article-title":"Street environment change detection from mobile laser scanning point clouds","volume":"107","author":"Xiao","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"7892","DOI":"10.3390\/rs70607892","article-title":"Individual tree segmentation from LiDAR point clouds for urban forest inventory","volume":"7","author":"Zhang","year":"2015","journal-title":"Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.isprsjprs.2017.03.012","article-title":"SigVox\u2013A 3D feature matching algorithm for automatic street object recognition in mobile laser scanning point clouds","volume":"128","author":"Wang","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"584","DOI":"10.3390\/rs5020584","article-title":"A voxel-based method for automated identification and morphological parameters estimation of individual street trees from mobile laser scanning data","volume":"5","author":"Wu","year":"2013","journal-title":"Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.isprsjprs.2014.10.005","article-title":"Hierarchical extraction of urban objects from mobile laser scanning data","volume":"99","author":"Yang","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Zhang, W., Qi, J., Wan, P., Wang, H., Xie, D., Wang, X., and Yan, G. (2016). An easy-to-use airborne LiDAR data filtering method based on cloth simulation. Remote Sens., 8.","DOI":"10.3390\/rs8060501"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1579","DOI":"10.1080\/01431160701736406","article-title":"Automatic forest inventory parameter determination from terrestrial laser scanner data","volume":"29","author":"Maas","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.isprsjprs.2010.08.003","article-title":"Predicting individual tree attributes from airborne laser point clouds based on the random forests technique","volume":"66","author":"Yu","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"476","DOI":"10.1109\/34.765658","article-title":"Direct least square fitting of ellipses","volume":"21","author":"Fitzgibbon","year":"1999","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_40","first-page":"76","article-title":"Modeled PM2.5 removal by urban forest in Shanghai","volume":"34","author":"Cao","year":"2016","journal-title":"J. Shanghai Jiaotong Univ. Agric. Sci."},{"key":"ref_41","first-page":"504","article-title":"Estimating leaf area and leaf biomass of open-grown deciduous urban trees","volume":"42","author":"Nowak","year":"1996","journal-title":"For. Sci."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.isprsjprs.2016.07.009","article-title":"A dual growing method for the automatic extraction of individual trees from mobile laser scanning data","volume":"120","author":"Li","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.isprsjprs.2015.10.007","article-title":"Segmenting tree crowns from terrestrial and mobile lidar data by exploring ecological theories","volume":"110","author":"Tao","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1226","DOI":"10.1109\/TGRS.2015.2476502","article-title":"Object classification and recognition from mobile laser scanning point clouds in a road environment","volume":"54","author":"Jaakkola","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.ufug.2016.02.010","article-title":"The feasibility of remotely sensed data to estimate urban tree dimensions and biomass","volume":"16","author":"Lee","year":"2016","journal-title":"Urban For. Urban Green."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.ufug.2016.04.003","article-title":"Mapping urban forest structure and function using hyperspectral imagery and lidar data","volume":"17","author":"Alonzo","year":"2016","journal-title":"Urban For. Urban Green."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/j.ufug.2016.08.011","article-title":"Estimation of urban tree canopy cover using random point sampling and remote sensing methods","volume":"20","author":"Parmher","year":"2016","journal-title":"Urban For. Urban Green."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.scitotenv.2014.08.070","article-title":"Mapping carbon storage in urban trees with multi-source remote sensing data: Relationships between biomass, land use, and demographics in Boston neighborhoods","volume":"500\u2013501","author":"Raciti","year":"2014","journal-title":"Sci. Total Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/11\/1759\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:28:28Z","timestamp":1760196508000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/11\/1759"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,11,7]]},"references-count":48,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2018,11]]}},"alternative-id":["rs10111759"],"URL":"https:\/\/doi.org\/10.3390\/rs10111759","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,11,7]]}}}