Above ground biomass (AGB) is a parameter commonly used for assessment of grassland systems. While destructive sampling of AGB is highly accurate, it is time consuming and often precludes repeat temporal sampling or sampling in sensitive ecosystems. Consequently, a number of nondestructive techniques that relate grass structural properties to AGB have been developed. This study investigated the application of two recent technologies, Terrestrial Laser Scanning (TLS) and Structurefrom- Motion (SfM), in the development of rapid nondestructive AGB estimation of grassland plots. TLS and SfM volume metrics generated using a rasterized surface differencing method were linearly related to destructively measured total AGB and grass AGB excluding all litter, and results were compared to the conventional disc pasture meter. The linear models were assessed using a leave-one-out cross validation scheme. The disc pasture meter was found to be the least reliable method in assessing total AGB (r2 = 0.32, RMSELOOCV = 269 g/m2). SfM (r2 = 0.74, RMSELOOCV = 169 g/m2) outperformed TLS (r2 = 0.56, RMSELOOCV = 219 g/m2), though a much larger slope in SfM regressions suggests an increased sensitivity to error. Litter removal decreased the effectiveness of AGB estimation for both TLS (r2 = 0.49) and SfM (r2 = 0.51) but increased the fit of disc pasture meter estimations (r2 = 0.42), highlighting the complex relationship between litter accumulation and AGB. TLS and SfM derived volumes were shown to be insensitive to cell dimensions when calculating volume provided cell dimensions were large enough to ensure no empty cells occurred. Using observed ground surfaces in volumetric calculations rather than an estimated ground plane increased r2 to 0.63 for TLS and 0.77 for SfM. Though the disc pasture meter was found to be the most rapid of the three methods, TLS and SfM both out performed it and have clearly demonstrated their potential utility for AGB estimation of grass systems. Their ability to systematically collect measurements over larger spatial extents than those investigated here could greatly outpace the disc pasture meter’s predictive capabilities and speed.
","abstract_html":"<p>Above ground biomass (AGB) is a parameter commonly used for assessment of grassland systems. While destructive sampling of AGB is highly accurate, it is time consuming and often precludes repeat temporal sampling or sampling in sensitive ecosystems. Consequently, a number of nondestructive techniques that relate grass structural properties to AGB have been developed. This study investigated the application of two recent technologies, Terrestrial Laser Scanning (TLS) and Structurefrom- Motion (SfM), in the development of rapid nondestructive AGB estimation of grassland plots. TLS and SfM volume metrics generated using a rasterized surface differencing method were linearly related to destructively measured total AGB and grass AGB excluding all litter, and results were compared to the conventional disc pasture meter. The linear models were assessed using a leave-one-out cross validation scheme. The disc pasture meter was found to be the least reliable method in assessing total AGB (r<sup>2</sup> = 0.32, RMSELOOCV = 269 g/m2). SfM (r<sup>2</sup> = 0.74, RMSE<sub>LOOCV</sub> = 169 g/m2) outperformed TLS (r<sup>2</sup> = 0.56, RMSE<sub>LOOCV</sub> = 219 g/m2), though a much larger slope in SfM regressions suggests an increased sensitivity to error. Litter removal decreased the effectiveness of AGB estimation for both TLS (r<sup>2</sup> = 0.49) and SfM (r<sup>2</sup> = 0.51) but increased the fit of disc pasture meter estimations (r<sup>2</sup> = 0.42), highlighting the complex relationship between litter accumulation and AGB. TLS and SfM derived volumes were shown to be insensitive to cell dimensions when calculating volume provided cell dimensions were large enough to ensure no empty cells occurred. Using observed ground surfaces in volumetric calculations rather than an estimated ground plane increased r<sup>2</sup> to 0.63 for TLS and 0.77 for SfM. Though the disc pasture meter was found to be the most rapid of the three methods, TLS and SfM both out performed it and have clearly demonstrated their potential utility for AGB estimation of grass systems. Their ability to systematically collect measurements over larger spatial extents than those investigated here could greatly outpace the disc pasture meter’s predictive capabilities and speed.</p>","abstract_has_math":false,"creators":["Cooper, Sam D."],"institution":null,"degree_name":"Master of Science (MS)","degree_level":"Thesis - Open Access","degree_discipline":"Geography","degree_department":null,"school":null,"contributors":["David Roy"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-01-01T08:00:00Z","date_published":"2017-01-01T08:00:00Z","updated_at":"2026-07-24T04:28:43Z","subjects":["aboveground biomass","disc pasture meter","grass","Structure-from-Motion","Terrestrial Laser Scanning","Geographic Information Sciences","Physical and Environmental Geography","Remote Sensing"],"languages":["en"],"rights":[],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://openprairie.sdstate.edu/etd/1209","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["David Roy"]},{"key":"dc:creator","label":"Author","values":["Cooper, Sam D."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2017-05-11T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Geography"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MS)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["aboveground biomass","disc pasture meter","grass","Structure-from-Motion","Terrestrial Laser Scanning","Geographic Information Sciences","Physical and Environmental Geography","Remote Sensing"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://openprairie.sdstate.edu/etd/1209"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Above ground biomass (AGB) is a parameter commonly used for assessment of grassland systems. While destructive sampling of AGB is highly accurate, it is time consuming and often precludes repeat temporal sampling or sampling in sensitive ecosystems. Consequently, a number of nondestructive techniques that relate grass structural properties to AGB have been developed. This study investigated the application of two recent technologies, Terrestrial Laser Scanning (TLS) and Structurefrom- Motion (SfM), in the development of rapid nondestructive AGB estimation of grassland plots. TLS and SfM volume metrics generated using a rasterized surface differencing method were linearly related to destructively measured total AGB and grass AGB excluding all litter, and results were compared to the conventional disc pasture meter. The linear models were assessed using a leave-one-out cross validation scheme. The disc pasture meter was found to be the least reliable method in assessing total AGB (r2 = 0.32, RMSELOOCV = 269 g/m2). SfM (r2 = 0.74, RMSELOOCV = 169 g/m2) outperformed TLS (r2 = 0.56, RMSELOOCV = 219 g/m2), though a much larger slope in SfM regressions suggests an increased sensitivity to error. Litter removal decreased the effectiveness of AGB estimation for both TLS (r2 = 0.49) and SfM (r2 = 0.51) but increased the fit of disc pasture meter estimations (r2 = 0.42), highlighting the complex relationship between litter accumulation and AGB. TLS and SfM derived volumes were shown to be insensitive to cell dimensions when calculating volume provided cell dimensions were large enough to ensure no empty cells occurred. Using observed ground surfaces in volumetric calculations rather than an estimated ground plane increased r2 to 0.63 for TLS and 0.77 for SfM. Though the disc pasture meter was found to be the most rapid of the three methods, TLS and SfM both out performed it and have clearly demonstrated their potential utility for AGB estimation of grass systems. Their ability to systematically collect measurements over larger spatial extents than those investigated here could greatly outpace the disc pasture meter’s predictive capabilities and speed.
"]},{"key":"dc:title","label":"Title","values":["Examination of the Potential of Structure-from-Motion Photogrammetry and Terrestrial Laser Scanning for Rapid Nondestructive Field Measurement of Grass Biomass"]}]}],"canonical_facts":{"dc:contributor":["David Roy"],"dc:creator":["Cooper, Sam D."],"dc:date.available":["2017-05-11T07:00:00Z"],"dc:description.abstract":["Above ground biomass (AGB) is a parameter commonly used for assessment of grassland systems. While destructive sampling of AGB is highly accurate, it is time consuming and often precludes repeat temporal sampling or sampling in sensitive ecosystems. Consequently, a number of nondestructive techniques that relate grass structural properties to AGB have been developed. This study investigated the application of two recent technologies, Terrestrial Laser Scanning (TLS) and Structurefrom- Motion (SfM), in the development of rapid nondestructive AGB estimation of grassland plots. TLS and SfM volume metrics generated using a rasterized surface differencing method were linearly related to destructively measured total AGB and grass AGB excluding all litter, and results were compared to the conventional disc pasture meter. The linear models were assessed using a leave-one-out cross validation scheme. The disc pasture meter was found to be the least reliable method in assessing total AGB (r2 = 0.32, RMSELOOCV = 269 g/m2). SfM (r2 = 0.74, RMSELOOCV = 169 g/m2) outperformed TLS (r2 = 0.56, RMSELOOCV = 219 g/m2), though a much larger slope in SfM regressions suggests an increased sensitivity to error. Litter removal decreased the effectiveness of AGB estimation for both TLS (r2 = 0.49) and SfM (r2 = 0.51) but increased the fit of disc pasture meter estimations (r2 = 0.42), highlighting the complex relationship between litter accumulation and AGB. TLS and SfM derived volumes were shown to be insensitive to cell dimensions when calculating volume provided cell dimensions were large enough to ensure no empty cells occurred. Using observed ground surfaces in volumetric calculations rather than an estimated ground plane increased r2 to 0.63 for TLS and 0.77 for SfM. Though the disc pasture meter was found to be the most rapid of the three methods, TLS and SfM both out performed it and have clearly demonstrated their potential utility for AGB estimation of grass systems. Their ability to systematically collect measurements over larger spatial extents than those investigated here could greatly outpace the disc pasture meter’s predictive capabilities and speed.
"],"dc:identifier":["https://openprairie.sdstate.edu/etd/1209"],"dc:language":["en"],"dc:rights":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["aboveground biomass","disc pasture meter","grass","Structure-from-Motion","Terrestrial Laser Scanning","Geographic Information Sciences","Physical and Environmental Geography","Remote Sensing"],"dc:title":["Examination of the Potential of Structure-from-Motion Photogrammetry and Terrestrial Laser Scanning for Rapid Nondestructive Field Measurement of Grass Biomass"],"thesis:degree_discipline":["Geography"],"thesis:degree_level":["Thesis - Open Access"],"thesis:degree_name":["Master of Science (MS)"]},"updated_at":"2026-07-24T04:28:43Z"}