{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T20:02:23Z","timestamp":1792699343879,"version":"4.5.0"},"reference-count":57,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2017,5,26]],"date-time":"2017-05-26T00:00:00Z","timestamp":1495756800000},"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>Above ground biomass (AGB) is a parameter commonly used for assessment of grassland systems. Destructive AGB measurements, although accurate, are time consuming and are not easily undertaken on a repeat basis or over large areas. Structure-from-Motion (SfM) photogrammetry and Terrestrial Laser Scanning (TLS) are two technologies that have the potential to yield precise 3D structural measurements of vegetation quite rapidly. Recent advances have led to the successful application of TLS and SfM in woody biomass estimation, but application in natural grassland systems remains largely untested. The potential of these techniques for AGB estimation is examined considering 11 grass plots with a range of biomass in South Dakota, USA. Volume metrics extracted from the TLS and SfM 3D point clouds, and also conventional disc pasture meter settling heights, were compared to destructively harvested AGB total (grass and litter) and AGB grass plot measurements. Although the disc pasture meter was the most rapid method, it was less effective in AGB estimation (AGBgrass r2 = 0.42, AGBtotal r2 = 0.32) than the TLS (AGBgrass r2 = 0.46, AGBtotal r2 = 0.57) or SfM (AGBgrass r2 = 0.54, AGBtotal r2 = 0.72) which both demonstrated their utility for rapid AGB estimation of grass systems.<\/jats:p>","DOI":"10.3390\/rs9060531","type":"journal-article","created":{"date-parts":[[2017,5,30]],"date-time":"2017-05-30T04:35:42Z","timestamp":1496118942000},"page":"531","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":108,"title":["Examination of the Potential of Terrestrial Laser Scanning and Structure-from-Motion Photogrammetry for Rapid Nondestructive Field Measurement of Grass Biomass"],"prefix":"10.3390","volume":"9","author":[{"given":"Sam","family":"Cooper","sequence":"first","affiliation":[{"name":"Geospatial Sciences Center of Excellence &amp; Department of Geography, South Dakota State University, Brookings, SD 57007, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1347-0250","authenticated-orcid":false,"given":"David","family":"Roy","sequence":"additional","affiliation":[{"name":"Geospatial Sciences Center of Excellence &amp; Department of Geography, South Dakota State University, Brookings, SD 57007, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Crystal","family":"Schaaf","sequence":"additional","affiliation":[{"name":"School for the Environment, University of Massachusetts Boston, Boston, MA 02125, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ian","family":"Paynter","sequence":"additional","affiliation":[{"name":"School for the Environment, University of Massachusetts Boston, Boston, MA 02125, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2017,5,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1071\/CP10019","article-title":"Evaluating an active optical sensor for quantifying and mapping green herbage mass and growth in a perennial grass pasture","volume":"61","author":"Trotter","year":"2010","journal-title":"Crop Pasture Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"259","DOI":"10.2307\/1942578","article-title":"Ecology of a grazing ecosystem: The serengeti","volume":"55","author":"McNaughton","year":"1985","journal-title":"Ecol. Monogr."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1366","DOI":"10.1016\/j.jenvman.2010.02.018","article-title":"The use of digital photos to assess visual cover for wildlife in rangelands","volume":"91","author":"Carlyle","year":"2010","journal-title":"J. Environ. Manag."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"23531","DOI":"10.1029\/96JD00691","article-title":"Safari-92 characterization of biomass and fire behavior in the small experimental burns in the Kruger National Park","volume":"101","author":"Trollope","year":"1996","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"519","DOI":"10.2307\/2261261","article-title":"Relationships of fire, biomass and nutrient dynamics along a vegetation gradient in the Brazilian Cerrado","volume":"82","author":"Kauffman","year":"1994","journal-title":"J. Ecol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1598","DOI":"10.1126\/science.1133306","article-title":"Carbon-negative biofuels from low-input high-diversity grassland biomass","volume":"314","author":"Tilman","year":"2006","journal-title":"Science"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1046\/j.1365-2486.1998.00151.x","article-title":"The global carbon sink: A grassland perspective","volume":"4","author":"Scurlock","year":"1998","journal-title":"Glob. Chang. Biol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1038\/35083573","article-title":"Partitioning selection and complementarity in biodiversity experiments","volume":"412","author":"Loreau","year":"2001","journal-title":"Nature"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"843","DOI":"10.1126\/science.1060391","article-title":"Diversity and productivity in a long-term grassland experiment","volume":"294","author":"Tilman","year":"2001","journal-title":"Science"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"504","DOI":"10.2134\/agronj1958.00021962005000090003x","article-title":"Plant height times ground cover versus clipped samples for estimating forage production","volume":"50","author":"Evans","year":"1958","journal-title":"Agron. J."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"254","DOI":"10.2307\/3899090","article-title":"Nondestructive estimation of shortgrass aerial biomass","volume":"40","author":"Williamson","year":"1987","journal-title":"J. Range Manag."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"71","DOI":"10.2134\/agronj1979.00021962007100010017x","article-title":"Estimating forage yield with a disk meter","volume":"71","author":"Santillan","year":"1979","journal-title":"Agron. J."},{"key":"ref_13","unstructured":"Holmes, C. (1974). The massey grass meter. Dairy Farming Annual, Massey University."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3906","DOI":"10.3390\/rs6053906","article-title":"Change detection of tree biomass with terrestrial laser scanning and quantitative structure modelling","volume":"6","author":"Kaasalainen","year":"2014","journal-title":"Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"491","DOI":"10.3390\/rs5020491","article-title":"Fast automatic precision tree models from terrestrial laser scanner data","volume":"5","author":"Raumonen","year":"2013","journal-title":"Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"761","DOI":"10.1016\/j.envsoft.2010.12.008","article-title":"An architectural model of trees to estimate forest structural attributes using terrestrial LiDAR","volume":"26","author":"Cote","year":"2011","journal-title":"Environ. Model. Softw."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1111\/2041-210X.12301","article-title":"Nondestructive estimates of above-ground biomass using terrestrial laser scanning","volume":"6","author":"Calders","year":"2015","journal-title":"Methods Ecol. Evol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"959","DOI":"10.1007\/s13595-011-0102-2","article-title":"The use of terrestrial LiDAR technology in forest science: Application fields, benefits and challenges","volume":"68","author":"Dassot","year":"2011","journal-title":"Ann. For. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1523","DOI":"10.1016\/j.agrformet.2010.07.010","article-title":"An evaluation of overhead laser scanning to estimate herbage removals in pasture quadrats","volume":"150","author":"Radtke","year":"2010","journal-title":"Agric. For. Meteorol."},{"key":"ref_20","unstructured":"Rowell, E., and Seielstad, C. (2012, January 16\u201319). Characterizing grass, litter, and shrub fuels in longleaf pine forest pre-and post-fire using terrestrial LiDAR. Proceedings of the SilviLaser, Vancouver, BC, Canada."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Wallace, L., Gupta, V., Reinke, K., and Jones, S. (2016). An assessment of pre-and post fire near surface fuel hazard in an Australian dry sclerophyll forest using point cloud data captured using a terrestrial laser scanner. Remote Sens., 8.","DOI":"10.3390\/rs8080679"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"083671","DOI":"10.1117\/1.JRS.8.083671","article-title":"Multitemporal crop surface models: Accurate plant height measurement and biomass estimation with terrestrial laser scanning in paddy rice","volume":"8","author":"Tilly","year":"2014","journal-title":"J. Appl. Remote Sens."},{"key":"ref_23","first-page":"101","article-title":"Fusion of high resolution remote sensing images and terrestrial laser scanning for improved biomass estimation of maize","volume":"40","author":"Schiedung","year":"2014","journal-title":"Int. Arch. Photogram. Remote. Sens. Spat. Inf. Sci."},{"key":"ref_24","unstructured":"Umphries, T.A. (2013). Characterizing Fuelbed Structure, Depth, and Mass in a Grassland Using Terrestrial Laser Scanning. [Master\u2019s Thesis, University of Montana]."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.fcr.2014.01.008","article-title":"LiDAR based biomass and crop nitrogen estimates for rapid, non-destructive assessment of wheat nitrogen status","volume":"159","author":"Eitel","year":"2014","journal-title":"Field Crop. Res."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Schaefer, M.T., and Lamb, D.W. (2016). A combination of plant NDVI and LiDAR measurements improve the estimation of pasture biomass in tall fescue (Festuca arundinacea var. Fletcher). Remote Sens., 8.","DOI":"10.3390\/rs8020109"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1098\/rspb.1979.0006","article-title":"The interpretation of structure from motion","volume":"203","author":"Ullman","year":"1979","journal-title":"Proc. R. Soc. Lond. B: Biol. Sci."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"James, M.R., and Robson, S. (2012). Straightforward reconstruction of 3D surfaces and topography with a camera: Accuracy and geoscience application. J. Geophys. Res. Earth, 117.","DOI":"10.1029\/2011JF002289"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Nouwakpo, S.K., Weltz, M.A., and McGwire, K. (2015). Assessing the performance of structure-from-motion photogrammetry and terrestrial LiDAR for reconstructing soil surface microtopography of naturally vegetated plots. Earth Surf. Process. Landf.","DOI":"10.1002\/esp.3787"},{"key":"ref_30","first-page":"262","article-title":"3D capture of archaeology and architecture with a hand-held camera","volume":"34","author":"Pollefeys","year":"2003","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1260\/2047-4970.1.0.1","article-title":"Computer vision tools for 3D modelling in archaeology","volume":"1","author":"Brutto","year":"2012","journal-title":"Int. J. Herit. Digit. Era"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/j.ufug.2013.10.005","article-title":"Assessment of tree structure using a 3D image analysis technique\u2014A proof of concept","volume":"13","author":"Morgenroth","year":"2014","journal-title":"Urban For. Urban Green."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"6587","DOI":"10.3390\/rs6076587","article-title":"The use of a hand-held camera for individual tree 3D mapping in forest sample plots","volume":"6","author":"Liang","year":"2014","journal-title":"Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Forsman, M., B\u00f6rlin, N., and Holmgren, J. (2016). Estimation of tree stem attributes using terrestrial photogrammetry with a camera rig. Forests, 7.","DOI":"10.3390\/f7030061"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Surov\u00fd, P., Yoshimoto, A., and Panagiotidis, D. (2016). Accuracy of reconstruction of the tree stem surface using terrestrial close-range photogrammetry. Remote Sens., 8.","DOI":"10.3390\/rs8020123"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"932","DOI":"10.1016\/j.ufug.2015.09.001","article-title":"3D modelling of individual trees using a handheld camera: Accuracy of height, diameter and volume estimates","volume":"14","author":"Miller","year":"2015","journal-title":"Urban For. Urban Green."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Mikita, T., Janata, P., and Surov\u00fd, P. (2016). Forest stand inventory based on combined aerial and terrestrial close-range photogrammetry. Forests, 7.","DOI":"10.3390\/f7080165"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.jaridenv.2014.05.001","article-title":"Three-dimensional vegetation structure of Tillandsia latifolia on a coppice dune","volume":"109","author":"Hesse","year":"2014","journal-title":"J. Arid Environ."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Wu, M., Yang, C., Song, X., Hoffmann, W.C., Huang, W., Niu, Z., Wang, C., and Li, W. (2017). Evaluation of orthomosics and digital surface models derived from aerial imagery for crop type mapping. Remote Sens., 9.","DOI":"10.3390\/rs9030239"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"45","DOI":"10.5194\/isprsarchives-XL-1-W2-45-2013","article-title":"Very high resolution crop surface models (CSMs) from UAV-based stereo images for rice growth monitoring in Northeast China","volume":"40","author":"Bendig","year":"2013","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Holman, F.H., Riche, A.B., Michalski, A., Castle, M., Wooster, M.J., and Hawkesford, M.J. (2016). High throughput field phenotyping of wheat plant height and growth rate in field plot trials using UAV based remote sensing. Remote Sens., 8.","DOI":"10.3390\/rs8121031"},{"key":"ref_42","unstructured":"SDSU Mesonet (2017, February 16). South Dakota Climate and Weather, South Dakota State University. Available online: https:\/\/climate.sdstate.edu\/."},{"key":"ref_43","unstructured":"Staff, S.S. (2017, February 16). Web Soil Survey, Available online: https:\/\/websoilsurvey.sc.egov.usda.gov\/."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1002\/rse2.26","article-title":"Observing ecosystems with lightweight, rapid-scanning terrestrial LiDAR scanners","volume":"2","author":"Paynter","year":"2016","journal-title":"Remote Sens. Ecol. Conserv."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.agrformet.2006.09.007","article-title":"Influence of measurement set-up of ground-based LiDAR for derivation of tree structure","volume":"141","author":"Hoet","year":"2006","journal-title":"Agric. For. Meteorol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.isprsjprs.2016.01.006","article-title":"Terrestrial laser scanning in forest inventories","volume":"115","author":"Liang","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"238","DOI":"10.2134\/agronj1998.00021962009000020022x","article-title":"A standardized plate meter for estimating pasture mass in on-farm research trials","volume":"90","author":"Rayburn","year":"1998","journal-title":"Agron. J."},{"key":"ref_48","unstructured":"Girardeau-Montaut, D. (2017, July 20). Cloudcompare, 2.7.0. Available online: http:\/\/www.cloudcompare.org."},{"key":"ref_49","unstructured":"Agisoft, L. (2014). Agisoft Photoscan User Manual: Professional Edition, Agisoft LLC."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.isprsjprs.2013.12.006","article-title":"Aboveground total and green biomass of dryland shrub derived from terrestrial laser scanning","volume":"88","author":"Olsoy","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"3610","DOI":"10.1109\/TGRS.2006.881743","article-title":"Voxel-based 3-D modeling of individual trees for estimating leaf area density using high-resolution portable scanning LiDAR","volume":"44","author":"Hosoi","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_52","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_53","doi-asserted-by":"crossref","first-page":"676","DOI":"10.1071\/WF07138","article-title":"Ground-based LiDAR: A novel approach to quantify fine-scale fuelbed characteristics","volume":"18","author":"Loudermilk","year":"2009","journal-title":"Int. J. Wildland Fire"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.agrformet.2014.03.022","article-title":"Implications of sensor configuration and topography on vertical plant profiles derived from terrestrial LiDAR","volume":"194","author":"Calders","year":"2014","journal-title":"Agric. For. Meteorol."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1024","DOI":"10.1002\/j.1537-2197.1995.tb11567.x","article-title":"Interannual variability in primary production in tallgrass prairie: Climate, soil-moisture, topographic position, and fire as determinants of aboveground biomass","volume":"82","author":"Briggs","year":"1995","journal-title":"Am. J. Bot."},{"key":"ref_56","unstructured":"Lamond, R.E., Ohlenbusch, P.D., and Posler, G.L. (1986). Smooth Brome Production and Utilization, C-Kansas State University, Cooperative Extension Service (USA)."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"467","DOI":"10.2307\/3899613","article-title":"Evaluation of the forage-disk method in mixed-grass rangelands of Kansas","volume":"40","author":"Karl","year":"1987","journal-title":"J. Range Manag."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/6\/531\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:37:02Z","timestamp":1760207822000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/6\/531"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,5,26]]},"references-count":57,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2017,6]]}},"alternative-id":["rs9060531"],"URL":"https:\/\/doi.org\/10.3390\/rs9060531","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,5,26]]}}}