3-D Modeling of Tomato Canopies Using a High-Resolution Portable Scanning Lidar for Extracting Structural Information

In the present study, an attempt was made to produce a precise 3D image of a tomato canopy using a portable high-resolution scanning lidar. The tomato canopy was scanned by the lidar from three positions surrounding it. Through the scanning, the point cloud data of the canopy were obtained and they were co-registered. Then, points corresponding to leaves were extracted and converted into polygon images. From the polygon images, leaf areas were accurately estimated with a mean absolute percent error of 4.6%. Vertical profile of leaf area density (LAD) and leaf area index (LAI) could be also estimated by summing up each leaf area derived from the polygon images. Leaf inclination angle could be also estimated from the 3-D polygon image. It was shown that leaf inclination angles had different values at each part of a leaf.

[1]  C. Osmond,et al.  Physiological Plant Ecology I , 1981, Encyclopedia of Plant Physiology.

[2]  G. Riechers.  Plants and Microclimate , 1984 .

[3]  Paul S. Heckbert,et al.  Survey of Texture Mapping , 1986, IEEE Computer Graphics and Applications.

[4]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Tadashi Takahashi,et al.  Seasonal Changes in Distribution of Intercepted Photosynthetically Active Radiation for Layer and Dry Matter Production in Spring Wheat Canopy , 1993 .

[6]  R. Belford,et al.  Effect of canopy structure on efficiency of radiation interception and use in spring wheat cultivars during the pre-anthesis period in a mediterranean-type environment , 1993 .

[7]  G. F. Sassenrath-Cole.  Dependence of canopy light distribution on leaf and canopy structure for two cotton (Gossypium) species , 1995 .

[8]  B. Moulia,et al.  Do changes in the azimuthal distribution of maize leaves over time affect canopy light absorption , 1999 .

[9]  V. Sadras,et al.  Profiles of Leaf Nitrogen and Light in Reproductive Canopies of Cotton (Gossypium hirsutum) , 2001 .

[10]  K. Omasa,et al.  Mapping of tree position of Larix leptolepis woods and estimation of diameter at breast height (DBH) and biomass of the trees using range data measured by a portable scanning lidar , 2002 .

[11]  M. Weissa,et al.  Review of methods for in situ leaf area index ( LAI ) determination Part II . Estimation of LAI , errors and sampling , 2003 .

[12]  N. Coops,et al.  Using airborne and ground-based ranging lidar to measure canopy structure in Australian forests , 2003 .

[13]  M. Wu,et al.  Principles of environmental physics , 2004, Plant Growth Regulation.

[14]  K. Omasa,et al.  3-D measurement of trees using a portable scanning lidar , 2005 .

[15]  Kenji Omasa,et al.  Voxel-Based 3-D Modeling of Individual Trees for Estimating Leaf Area Density Using High-Resolution Portable Scanning Lidar , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[16]  J. Morison,et al.  Boundary layer conductance for contrasting leaf shapes in a deciduous broadleaved forest canopy , 2006 .

[17]  H. Sinoquet,et al.  Simple equations to estimate light interception by isolated trees from canopy structure features: assessment with three-dimensional digitized apple trees. , 2007, The New phytologist.

[18]  K. Omasa,et al.  Factors contributing to accuracy in the estimation of the woody canopy leaf area density profile using 3D portable lidar imaging. , 2007, Journal of experimental botany.

[19]  K. Omasa,et al.  3D lidar imaging for detecting and understanding plant responses and canopy structure. , 2006, Journal of experimental botany.

[20]  K. Omasa,et al.  Three-Dimensional Modeling of an Urban Park and Trees by Combined Airborne and Portable On-Ground Scanning LIDAR Remote Sensing , 2008 .

[21]  K. Omasa,et al.  Estimating leaf inclination angle distribution of wheat canopy using portable scanning lider , 2009 .

[22]  K. Omasa,et al.  Estimating vertical plant area density profile and growth parameters of a wheat canopy at different growth stages using three-dimensional portable lidar imaging , 2009 .

[23]  K. Omasa,et al.  3D monitoring spatio-temporal effects of herbicide on a whole plant using combined range and chlorophyll a fluorescence imaging. , 2009, Functional plant biology : FPB.

[24]  K. Omasa,et al.  Estimating the leaf inclination angle distribution of the wheat canopy using a portable scanning lidar , 2009 .

[25]  Kenji Omasa,et al.  Estimation and Error Analysis of Woody Canopy Leaf Area Density Profiles Using 3-D Airborne and Ground-Based Scanning Lidar Remote-Sensing Techniques , 2010, IEEE Transactions on Geoscience and Remote Sensing.