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12篇 您的检索式：作者名="BUCKSCH"

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		题名	作者	年代	出处	被引量
	1	Structural Monitoring of Tunnels Using TerrestrialLaser Scanning 显示文摘	Lindenbergh R Uchanski L Bucksch A	2009	Geodesy2009，87，2：	1
	2	CAMPINO a skeletonization method for point cloud processing 显示文摘	Bucksch A Lindenbergh R	2008	ISPRS Journal of Photo- grammetry & Remote Sensing2008，，：	1
	3	Error budget of terrestrial laser scanning: influence of the intensity remission on the scan quality 显示文摘	A Bucksch R Lindenbergh J Van Ree	2007	Proceedings in the GeoSiberia-2007，2007，：	1
	4	Dynamische Kriterien für die Auslegung von Fahrleitungen显示文摘	Bauer K H Bucksch R Lemer F	1979	ZEV Glasers Annalen1979，103，10：	1
	5	Localized registration of point clouds of botanic trees 显示文摘	A Bucksch K Khoshelham	2013	IEEE Geoscience and Remote Sensing Letters2013，10，3：	1
	6	International trends in adolescent screen-time behaviors from 2002 to 2010显示文摘	BUCKSCH J SIGMUNDOVA D HAMRIK Z	2016	J Adolesc Health2016，58，4：	1
	7	Three-dimensional laser imaging as a valuable tool for specifying changes in breast shape after augmentation mammaplasty显示文摘	Esme DL Bucksch A Beekman WH		0，，02：	1
	8	Localized registration of point clouds of botanic trees显示文摘	Bucksch A Khoshelham K	2013	IEEE Geoscience and Remote Sensing Letters2013，10，3：	1
	9	Structural monitoring of tunnels using terrestrial laser scanning显示文摘	LINDENBERGH R UCHANSKI L BUCKSCH A	2009	Reports on Geodesy2009，2，87：	1
	10	Dynamische krite2rien die auslegung yon fahrleitungen 显示文摘	BAUER K H BUCKSCH R LEMER F	1979	ZEV Glasers An- nalen1979，103，10：	1
	11	Three-dimensional laser imaging as a valuable tool for specifying changes in breast shape after augmentation mammaplasty 显示文摘	Esme DL Bucksch A Beckman WH	2009	Aesthetic Plast Surg2009，33，2：	1
	12	Canopy Roughness:A New Phenotypic Trait to Estimate Aboveground Biomass from Unmanned Aerial System显示文摘Cost-effective phenotyping methods are urgently needed to advance crop genetics in order to meet the food,fuel,and fiber demands of the coming decades.Concretely,characterizing plot level traits in fields is of particular interest.Recent developments in highresolution imaging sensors for UAS(unmanned aerial systems)focused on collecting detailed phenotypic measurements are a potential solution.We introduce canopy roughness as a new plant plot-level trait.We tested its usability with soybean by optical data collected from UAS to estimate biomass.We validate canopy roughness on a panel of 108 soybean[Glycine max(L.)Merr.]recombinant inbred lines in a multienvironment trial during the R^(2) growth stage.A senseFly eBee UAS platform obtained aerial images with a senseFly S.O.D.A.compact digital camera.Using a structure from motion(SfM)technique,we reconstructed 3D point clouds of the soybean experiment.A novel pipeline for feature extraction was developed to compute canopy roughness from point clouds.We used regression analysis to correlate canopy roughness with field-measured aboveground biomass(AGB)with a leave-one-out cross-validation.Overall,our models achieved a coefficient of determination(R^(2))greater than 0.5 in all trials.Moreover,we found that canopy roughness has the ability to discern AGB variations among different genotypes.Our test trials demonstrate the potential of canopy roughness as a reliable trait for high-throughput phenotyping to estimate AGB.As such,canopy roughness provides practical information to breeders in order to select phenotypes on the basis of UAS data.	Monica Herrero-Huerta Alexander Bucksch Eetu Puttonen Katy M.Rainey	2020	Plant Phenomics2020，2，1：	0

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