{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T23:14:41Z","timestamp":1771024481496,"version":"3.50.1"},"reference-count":78,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2022,4,11]],"date-time":"2022-04-11T00:00:00Z","timestamp":1649635200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U2106209"],"award-info":[{"award-number":["U2106209"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Scientific Research Program of Shanghai Science and Technology Commission","award":["21ZR1405600"],"award-info":[{"award-number":["21ZR1405600"]}]},{"name":"Scientific Research Program of Shanghai Science and Technology Commission","award":["20dz1204702"],"award-info":[{"award-number":["20dz1204702"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The spatial distribution patterns of salt marsh plant communities and their biomass provide useful information for monitoring the stability and productivity of coastal salt marsh ecosystems in space and time. However, the spatial patterns of plant vegetation and its aboveground biomass (AGB) in a coastal salt marsh remain unclear. This study mapped the spatial distributions of salt marsh communities and their AGB based on image and LiDAR data acquired by an unmanned aerial vehicle (UAV) in the Yangtze River Estuary. The differences in vegetation structure and AGB at regions located at different distances from tidal creeks were also tested. The results show that biomass estimated through a random forest model is in good agreement (R2 = 0.90, RMSE = 0.1 kg m\u22122) with field-measured biomass. The results indicate that an AGB estimation model based on UAV-LiDAR data and a random forest algorithm with high accuracy was useful for efficiently estimating the AGB of salt marsh vegetation. Moreover, for Phragmites australis, both its proportion and AGB increased, while the proportion and AGB of Scirpus mariqueter, Carex scabrifolia, and Imperata cylindrica decreased with increasing distance from tidal creeks. Our study demonstrates that tidal creeks are important for shaping spatial patterns of coastal salt marsh communities by altering soil salinity and soil moisture, so reasonable and scientific measures should be taken to manage and protect coastal ecosystems.<\/jats:p>","DOI":"10.3390\/rs14081839","type":"journal-article","created":{"date-parts":[[2022,4,12]],"date-time":"2022-04-12T02:48:59Z","timestamp":1649731739000},"page":"1839","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Assessing the Impacts of Tidal Creeks on the Spatial Patterns of Coastal Salt Marsh Vegetation and Its Aboveground Biomass"],"prefix":"10.3390","volume":"14","author":[{"given":"Ya-Nan","family":"Tang","sequence":"first","affiliation":[{"name":"Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, School of Life Sciences, Fudan University, 2005 Songhu Road, Shanghai 200438, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3412-7766","authenticated-orcid":false,"given":"Jun","family":"Ma","sequence":"additional","affiliation":[{"name":"Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, School of Life Sciences, Fudan University, 2005 Songhu Road, Shanghai 200438, China"}]},{"given":"Jing-Xian","family":"Xu","sequence":"additional","affiliation":[{"name":"Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, School of Life Sciences, Fudan University, 2005 Songhu Road, Shanghai 200438, China"}]},{"given":"Wan-Ben","family":"Wu","sequence":"additional","affiliation":[{"name":"Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, School of Life Sciences, Fudan University, 2005 Songhu Road, Shanghai 200438, China"}]},{"given":"Yuan-Chen","family":"Wang","sequence":"additional","affiliation":[{"name":"Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, School of Life Sciences, Fudan University, 2005 Songhu Road, Shanghai 200438, China"}]},{"given":"Hai-Qiang","family":"Guo","sequence":"additional","affiliation":[{"name":"Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, School of Life Sciences, Fudan University, 2005 Songhu Road, Shanghai 200438, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,11]]},"reference":[{"key":"ref_1","first-page":"315","article-title":"Species interactions modulate the response of saltmarsh plants to flooding","volume":"125","author":"Edge","year":"2020","journal-title":"Ann. Bot."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"823","DOI":"10.1007\/s11258-018-0837-z","article-title":"Plant traits shape the effects of tidal flooding on soil and plant communities in saltmarshes","volume":"219","author":"Pellegrini","year":"2018","journal-title":"Plant Ecol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3967","DOI":"10.1111\/gcb.13727","article-title":"Review of the ecosystem service implications of mangrove encroachment into salt marshes","volume":"23","author":"Kelleway","year":"2017","journal-title":"Glob. Change Biol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/21513732.2015.1006250","article-title":"Ecosystem services of wetlands","volume":"11","author":"Mitsch","year":"2015","journal-title":"Int. J. Biodivers. Sci. Ecosyst. Serv. Manag."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.ecss.2013.11.022","article-title":"The value of carbon sequestration and storage in coastal habitats","volume":"137","author":"Beaumont","year":"2014","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Pendleton, L., Donato, D.C., Murray, B.C., Crooks, S., Jenkins, W.A., Sifleet, S., Craft, C., Fourqurean, J.W., Kauffman, J.B., and Marb\u00e0, N. (2012). Estimating global \u201cblue carbon\u201d emissions from conversion and degradation of vegetated coastal ecosystems. PLoS ONE, 7.","DOI":"10.1371\/journal.pone.0043542"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.5194\/bg-2-1-2005","article-title":"Major role of marine vegetation on the oceanic carbon cycle","volume":"2","author":"Duarte","year":"2005","journal-title":"Biogeosciences"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"552","DOI":"10.1890\/110004","article-title":"A blueprint for blue carbon: Toward an improved understanding of the role of vegetated coastal habitats in sequestering CO2","volume":"9","author":"Mcleod","year":"2011","journal-title":"Front. Ecol. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1007\/s11273-009-9169-z","article-title":"Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: A review","volume":"18","author":"Adam","year":"2010","journal-title":"Wetl. Ecol. Manag."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"6497","DOI":"10.1080\/01431160902882496","article-title":"Estimating aboveground biomass of grassland having a high canopy cover: An exploratory analysis of in situ hyperspectral data","volume":"30","author":"Chen","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1109\/JSTARS.2018.2886046","article-title":"Evaluation on spaceborne multispectral images, airborne hyperspectral, and LiDAR data for extracting spatial distribution and estimating aboveground biomass of wetland vegetation suaeda salsa","volume":"12","author":"Du","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Wang, J., Liu, Z., Yu, H., and Li, F. (2017). Mapping Spartina alterniflora biomass using LiDAR and hyperspectral data. Remote Sens., 9.","DOI":"10.3390\/rs9060589"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Bertness, M.D., and Pennings, S.C. (2002). Spatial Variation in Process and Pattern in Salt Marsh Plant Communities in Eastern North America. Concepts and Controversies in Tidal Marsh Ecology, Springer.","DOI":"10.1007\/0-306-47534-0_4"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2539","DOI":"10.1890\/03-0745","article-title":"Physical and biotic drivers of plant distribution across estuarine salinity gradients","volume":"85","author":"Crain","year":"2004","journal-title":"Ecology"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"e2019JG005217","DOI":"10.1029\/2019JG005217","article-title":"Salinity Affects Topsoil Organic Carbon Concentrations Through Regulating Vegetation Structure and Productivity","volume":"125","author":"Xue","year":"2020","journal-title":"J. Geophys. Res. Biogeosciences"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1111\/j.1365-2745.2004.00959.x","article-title":"Plant zonation in low-latitude salt marshes: Disentangling the roles of flooding, salinity and competition","volume":"93","author":"Pennings","year":"2005","journal-title":"J. Ecol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"12287","DOI":"10.1038\/ncomms12287","article-title":"Salt marsh vegetation promotes efficient tidal channel networks","volume":"7","author":"Kearney","year":"2016","journal-title":"Nat. Commun."},{"key":"ref_18","first-page":"1021","article-title":"Distribution pattern of plant community in new-born coastal wetland in the Yellow River Delta","volume":"35","author":"Wang","year":"2015","journal-title":"Sci. Geogr. Sin."},{"key":"ref_19","first-page":"1855","article-title":"The relationship between the spatial distribution of vegetation and soil environmental factors in the tidal creek areas of the Yellow River Delta","volume":"19","author":"Zhao","year":"2010","journal-title":"Ecol. Environ. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/0272-7714(83)90137-3","article-title":"The influence of mosquito control recirculation ditches on plant biomass, production and composition in two San Francisco Bay salt marshes","volume":"16","author":"Balling","year":"1983","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.rse.2014.04.003","article-title":"Evaluation of sensor types and environmental controls on mapping biomass of coastal marsh emergent vegetation","volume":"149","author":"Byrd","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1023\/A:1020908432489","article-title":"Satellite remote sensing of wetlands","volume":"10","author":"Ozesmi","year":"2002","journal-title":"Wetl. Ecol. Manag."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Miller, G.J., Morris, J.T., and Wang, C. (2019). Estimating aboveground biomass and its spatial distribution in coastal wetlands utilizing planet multispectral imagery. Remote Sens., 11.","DOI":"10.3390\/rs11172020"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Lumbierres, M., M\u00e9ndez, P.F., Bustamante, J., Soriguer, R., and Santamar\u00eda, L. (2017). Modeling biomass production in seasonal wetlands using MODIS NDVI land surface phenology. Remote Sens., 9.","DOI":"10.3390\/rs9040392"},{"key":"ref_25","first-page":"100457","article-title":"Modelling above ground biomass of Indian mangrove forest using dual-pol SAR data","volume":"21","author":"Vaghela","year":"2021","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"108694","DOI":"10.1016\/j.ecolind.2022.108694","article-title":"Aboveground biomass of typical invasive mangroves and its distribution patterns using UAV-LiDAR data in a subtropical estuary: Maoling River estuary, Guangxi, China","volume":"136","author":"Tian","year":"2022","journal-title":"Ecol. Indic."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"025012","DOI":"10.1088\/1748-9326\/aa9f03","article-title":"Estimating mangrove aboveground biomass from airborne LiDAR data: A case study from the Zambezi River delta","volume":"13","author":"Fatoyinbo","year":"2018","journal-title":"Environ. Res. Lett."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Guo, M., Li, J., Sheng, C., Xu, J., and Wu, L. (2017). A review of wetland remote sensing. Sensors, 17.","DOI":"10.3390\/s17040777"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1109\/JSTARS.2009.2037523","article-title":"Analysis on the use of multiple returns LiDAR data for the estimation of tree stems volume","volume":"2","author":"Dalponte","year":"2009","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Hsu, A.J., Kumagai, J., Favoretto, F., Dorian, J., Guerrero Martinez, B., and Aburto-Oropeza, O. (2020). Driven by Drones: Improving Mangrove Extent Maps Using High-Resolution Remote Sensing. Remote Sens., 12.","DOI":"10.3390\/rs12233986"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"107968","DOI":"10.1016\/j.geomorph.2021.107968","article-title":"Effects of the 2017\u20132018 winter freeze on the northern limit of the American mangroves, Mississippi River delta plain","volume":"394","author":"Cohen","year":"2021","journal-title":"Geomorphology"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Laporte-Fauret, Q., Marieu, V., Castelle, B., Michalet, R., Bujan, S., and Rosebery, D. (2019). Low-cost UAV for high-resolution and large-scale coastal dune change monitoring using photogrammetry. J. Mar. Sci. Eng., 7.","DOI":"10.3390\/jmse7030063"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Fabbri, S., Grottoli, E., Armaroli, C., and Ciavola, P. (2021). Using High-Spatial Resolution UAV-Derived Data to Evaluate Vegetation and Geomorphological Changes on a Dune Field Involved in a Restoration Endeavour. Remote Sens., 13.","DOI":"10.3390\/rs13101987"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Rende, S.F., Bosman, A., Di Mento, R., Bruno, F., Lagudi, A., Irving, A.D., Dattola, L., Giambattista, L.D., Lanera, P., and Proietti, R. (2020). Ultra-high-resolution mapping of Posidonia oceanica (L.) delile meadows through acoustic, optical data and object-based image classification. J. Mar. Sci. Eng., 8.","DOI":"10.3390\/jmse8090647"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1260","DOI":"10.2112\/JCOASTRES-D-15-00005.1","article-title":"Coastal and environmental remote sensing from unmanned aerial vehicles: An overview","volume":"31","author":"Klemas","year":"2015","journal-title":"J. Coast. Res."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1139\/juvs-2014-0006","article-title":"Remote sensing of the environment with small unmanned aircraft systems (UASs), part 1: A review of progress and challenges","volume":"2","author":"Whitehead","year":"2014","journal-title":"J. Unmanned Veh. Syst."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"022204","DOI":"10.1117\/1.JRS.14.022204","article-title":"Estimation of secondary forest parameters by integrating image and point cloud-based metrics acquired from unmanned aerial vehicle","volume":"14","author":"Xu","year":"2019","journal-title":"J. Appl. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.rse.2017.06.023","article-title":"Structure from motion will revolutionize analyses of tidal wetland landscapes","volume":"199","author":"Kalacska","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Doughty, C.L., and Cavanaugh, K.C. (2019). Mapping coastal wetland biomass from high resolution unmanned aerial vehicle (UAV) imagery. Remote Sens., 11.","DOI":"10.3390\/rs11050540"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"111916","DOI":"10.1016\/j.rse.2020.111916","article-title":"Quantifying expansion and removal of Spartina alterniflora on Chongming island, China, using time series Landsat images during 1995\u20132018","volume":"247","author":"Zhang","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_41","first-page":"114","article-title":"The determination of sedimentation rates in various vegetational zones of Chongming tidal flat of the Changjiang Estuary","volume":"34","author":"Jiang","year":"2012","journal-title":"Acta Oceanol. Sin."},{"key":"ref_42","first-page":"32","article-title":"A study of coastal morphodynamics on the muddy islands in the Changjiang River estuary","volume":"15","author":"Shilun","year":"1999","journal-title":"J. Coast. Res."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"704","DOI":"10.17521\/cjpe.2015.0067","article-title":"Spatial distribution of species and influencing factors across salt marsh in southern Chongming Dongtan","volume":"39","author":"Ding","year":"2015","journal-title":"Chin. J. Plant. Ecol."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/j.ecss.2006.04.016","article-title":"Multi-seasonal spectral characteristics analysis of coastal salt marsh vegetation in Shanghai, China","volume":"69","author":"Gao","year":"2006","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"ref_45","first-page":"1097","article-title":"Succession character of salt marsh vegetations in Chongming Dongtan wetland","volume":"18","author":"Yan","year":"2007","journal-title":"J. Appl. Ecol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/S0034-4257(01)00295-4","article-title":"Status of land cover classification accuracy assessment","volume":"80","author":"Foody","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1037\/0033-2909.101.1.140","article-title":"Diversity of decision-making models and the measurement of interrater agreement","volume":"101","author":"Uebersax","year":"1987","journal-title":"Psychol. Bull."},{"key":"ref_48","first-page":"1449","article-title":"The determination of optimal threshold levels for change detection using various accuracy indexes","volume":"54","author":"Tung","year":"1988","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_49","first-page":"397","article-title":"Accuracy assessment: A user\u2019s perspective","volume":"52","author":"Story","year":"1986","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_50","first-page":"1","article-title":"Multiple linear regression","volume":"5","author":"Tranmer","year":"2008","journal-title":"Cathie Marsh Cent. Census Surv. Res. (CCSR)"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/S0304-3800(02)00204-1","article-title":"Generalized linear and generalized additive models in studies of species distributions: Setting the scene","volume":"157","author":"Guisan","year":"2002","journal-title":"Ecol. Model."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"802","DOI":"10.1111\/j.1365-2656.2008.01390.x","article-title":"A working guide to boosted regression trees","volume":"77","author":"Elith","year":"2008","journal-title":"J. Anim. Ecol."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Zhang, Z. (2018). Artificial Neural Network. Multivariate Time Series Analysis in Climate and Environmental Research, Springer.","DOI":"10.1007\/978-3-319-67340-0"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"2275","DOI":"10.1109\/TSP.2004.830985","article-title":"The kernel recursive least-squares algorithm","volume":"52","author":"Engel","year":"2004","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.agrformet.2018.04.005","article-title":"Annual Forest aboveground biomass changes mapped using ICESat\/GLAS measurements, historical inventory data, and time-series optical and radar imagery for Guangdong province, China","volume":"259","author":"Shen","year":"2018","journal-title":"Agric. For. Meteorol."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"110070","DOI":"10.1016\/j.jenvman.2020.110070","article-title":"The size and distribution of tidal creeks affects salt marsh restoration","volume":"259","author":"Wu","year":"2020","journal-title":"J. Environ. Manag."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"669","DOI":"10.2307\/2260075","article-title":"Plant zonation in an Alaskan salt marsh: II. An experimental study of the role of edaphic conditions","volume":"7","author":"Snow","year":"1984","journal-title":"J. Ecol."},{"key":"ref_59","first-page":"4919","article-title":"Vegetation zonation related to the edaphic factors in the East headland of Chongming Island","volume":"30","author":"He","year":"2010","journal-title":"Acta Ecol. Sin."},{"key":"ref_60","first-page":"1081","article-title":"Relationship between soil characteristics and halophytic vegetation in coastal region of North China","volume":"40","author":"Li","year":"2008","journal-title":"Pak. J. Bot."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"2471","DOI":"10.1890\/0012-9658(2001)082[2471:CASMPZ]2.0.CO;2","article-title":"Competition and salt-marsh plant zonation: Stress tolerators may be dominant competitors","volume":"82","author":"Emery","year":"2001","journal-title":"Ecology"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1071\/BT96105","article-title":"Shoot population dynamics of Carex kobomugi on a coastal sand dune in relation to its zonal distribution","volume":"46","author":"Ishikawa","year":"1998","journal-title":"Aust. J. Bot."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"917","DOI":"10.1007\/s11258-013-0218-6","article-title":"Plant responses to increased inundation and salt exposure: Interactive effects on tidal marsh productivity","volume":"214","author":"Janousek","year":"2013","journal-title":"Plant Ecol."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"703","DOI":"10.2307\/2261333","article-title":"Spatial and temporal dynamics of mycorrhizas in Jaumea carnosa, a tidal saltmarsh halophyte","volume":"84","author":"Brown","year":"1996","journal-title":"J. Ecol."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1086\/283290","article-title":"The nature of growth forms in the salt marsh grass Spartina alterniflora","volume":"112","author":"Valiela","year":"1978","journal-title":"Am. Nat."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1016\/S0304-3770(02)00022-0","article-title":"The relation between vegetation zonation, elevation and inundation frequency in a Wadden Sea salt marsh","volume":"73","author":"Bockelmann","year":"2002","journal-title":"Aquat. Bot."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1111\/1365-2745.13229","article-title":"Manipulating saltmarsh microtopography modulates the effects of elevation on sediment redox potential and halophyte distribution","volume":"108","author":"Mossman","year":"2020","journal-title":"J. Ecol."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"e03755","DOI":"10.1002\/ecs2.3755","article-title":"Salt marsh establishment in poorly consolidated muddy systems: Effects of surface drainage, elevation, and plant age","volume":"12","author":"Cao","year":"2021","journal-title":"Ecosphere"},{"key":"ref_69","first-page":"101986","article-title":"Estimating aboveground biomass of the mangrove forests on northeast Hainan Island in China using an upscaling method from field plots, UAV-LiDAR data and Sentinel-2 imagery","volume":"85","author":"Wang","year":"2020","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2021.3091771","article-title":"Exploration of glacial landforms by object-based image analysis and spectral parameters of digital elevation model","volume":"60","author":"Janowski","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"2954","DOI":"10.1080\/01431161.2017.1285083","article-title":"An integrated UAV-borne lidar system for 3D habitat mapping in three forest ecosystems across China","volume":"38","author":"Guo","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"111599","DOI":"10.1016\/j.rse.2019.111599","article-title":"Soybean yield prediction from UAV using multimodal data fusion and deep learning","volume":"237","author":"Maimaitijiang","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Xu, J.-X., Ma, J., Tang, Y.-N., Wu, W.-X., Shao, J.-H., Wu, W.-B., Wei, S.-Y., Liu, Y.-F., Wang, Y.-C., and Guo, H.-Q. (2020). Estimation of Sugarcane Yield Using a Machine Learning Approach Based on UAV-LiDAR Data. Remote Sens., 12.","DOI":"10.3390\/rs12172823"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.rse.2012.07.006","article-title":"Forest biomass estimation from airborne LiDAR data using machine learning approaches","volume":"125","author":"Gleason","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"e7593","DOI":"10.7717\/peerj.7593","article-title":"Estimation of maize above-ground biomass based on stem-leaf separation strategy integrated with LiDAR and optical remote sensing data","volume":"7","author":"Zhu","year":"2019","journal-title":"PeerJ"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"106900","DOI":"10.1016\/j.ecss.2020.106900","article-title":"Distribution of organic carbon storage in different salt-marsh plant communities: A case study at the Yangtze estuary","volume":"243","author":"Yuan","year":"2020","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1016\/S0304-3800(01)00253-8","article-title":"A simple empirical model of salt marsh plant spatial distributions with respect to a tidal channel network","volume":"139","author":"Sanderson","year":"2001","journal-title":"Ecol. Model."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"340","DOI":"10.1016\/j.ecss.2019.01.002","article-title":"Carbon outwelling and emissions from two contrasting mangrove creeks during the monsoon storm season in Palau, Micronesia","volume":"218","author":"Call","year":"2019","journal-title":"Estuar. Coast. Shelf Sci."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/8\/1839\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:52:03Z","timestamp":1760136723000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/8\/1839"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,11]]},"references-count":78,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2022,4]]}},"alternative-id":["rs14081839"],"URL":"https:\/\/doi.org\/10.3390\/rs14081839","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,11]]}}}