Literature DB >> 17030540

3D lidar imaging for detecting and understanding plant responses and canopy structure.

Kenji Omasa1, Fumiki Hosoi, Atsumi Konishi.   

Abstract

Understanding and diagnosing plant responses to stress will benefit greatly from three-dimensional (3D) measurement and analysis of plant properties because plant responses are strongly related to their 3D structures. Light detection and ranging (lidar) has recently emerged as a powerful tool for direct 3D measurement of plant structure. Here the use of 3D lidar imaging to estimate plant properties such as canopy height, canopy structure, carbon stock, and species is demonstrated, and plant growth and shape responses are assessed by reviewing the development of lidar systems and their applications from the leaf level to canopy remote sensing. In addition, the recent creation of accurate 3D lidar images combined with natural colour, chlorophyll fluorescence, photochemical reflectance index, and leaf temperature images is demonstrated, thereby providing information on responses of pigments, photosynthesis, transpiration, stomatal opening, and shape to environmental stresses; these data can be integrated with 3D images of the plants using computer graphics techniques. Future lidar applications that provide more accurate dynamic estimation of various plant properties should improve our understanding of plant responses to stress and of interactions between plants and their environment. Moreover, combining 3D lidar with other passive and active imaging techniques will potentially improve the accuracy of airborne and satellite remote sensing, and make it possible to analyse 3D information on ecophysiological responses and levels of various substances in agricultural and ecological applications and in observations of the global biosphere.

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Mesh:

Year:  2006        PMID: 17030540     DOI: 10.1093/jxb/erl142

Source DB:  PubMed          Journal:  J Exp Bot        ISSN: 0022-0957            Impact factor:   6.992


  43 in total

1.  Relationships between the photochemical reflectance index (PRI) and chlorophyll fluorescence parameters and plant pigment indices at different leaf growth stages.

Authors:  Parinaz Rahimzadeh-Bajgiran; Masashi Munehiro; Kenji Omasa
Journal:  Photosynth Res       Date:  2012-05-30       Impact factor: 3.573

2.  Imaging of multi-color fluorescence emission from leaf tissues.

Authors:  Zuzana Benediktyová; Ladislav Nedbal
Journal:  Photosynth Res       Date:  2009-09-26       Impact factor: 3.573

3.  Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress.

Authors:  Gina H Mohammed; Roberto Colombo; Elizabeth M Middleton; Uwe Rascher; Christiaan van der Tol; Ladislav Nedbal; Yves Goulas; Oscar Pérez-Priego; Alexander Damm; Michele Meroni; Joanna Joiner; Sergio Cogliati; Wouter Verhoef; Zbyněk Malenovský; Jean-Philippe Gastellu-Etchegorry; John R Miller; Luis Guanter; Jose Moreno; Ismael Moya; Joseph A Berry; Christian Frankenberg; Pablo J Zarco-Tejada
Journal:  Remote Sens Environ       Date:  2019-07-13       Impact factor: 10.164

4.  Image-based dynamic quantification and high-accuracy 3D evaluation of canopy structure of plant populations.

Authors:  Fang Hui; Jinyu Zhu; Pengcheng Hu; Lei Meng; Binglin Zhu; Yan Guo; Baoguo Li; Yuntao Ma
Journal:  Ann Bot       Date:  2018-04-18       Impact factor: 4.357

5.  A Three-Dimensional Scanning System for Digital Archiving and Quantitative Evaluation of Arabidopsis Plant Architectures.

Authors:  Itsuki Kunita; Miyo Terao Morita; Masashi Toda; Takumi Higaki
Journal:  Plant Cell Physiol       Date:  2021-12-27       Impact factor: 4.927

6.  Automated recovery of three-dimensional models of plant shoots from multiple color images.

Authors:  Michael P Pound; Andrew P French; Erik H Murchie; Tony P Pridmore
Journal:  Plant Physiol       Date:  2014-10-20       Impact factor: 8.340

Review 7.  Integrating remote sensing with ecology and evolution to advance biodiversity conservation.

Authors:  Jeannine Cavender-Bares; Fabian D Schneider; Maria João Santos; Amanda Armstrong; Ana Carnaval; Kyla M Dahlin; Lola Fatoyinbo; George C Hurtt; David Schimel; Philip A Townsend; Susan L Ustin; Zhihui Wang; Adam M Wilson
Journal:  Nat Ecol Evol       Date:  2022-03-24       Impact factor: 15.460

Review 8.  Signature Optical Cues: Emerging Technologies for Monitoring Plant Health.

Authors:  Oi Wah Liew; Pek Ching Jenny Chong; Bingqing Li; Anand K Asundi
Journal:  Sensors (Basel)       Date:  2008-05-16       Impact factor: 3.576

9.  3-D modeling of tomato canopies using a high-resolution portable scanning lidar for extracting structural information.

Authors:  Fumiki Hosoi; Kazushige Nakabayashi; Kenji Omasa
Journal:  Sensors (Basel)       Date:  2011-02-15       Impact factor: 3.847

10.  Computer reconstruction of plant growth and chlorophyll fluorescence emission in three spatial dimensions.

Authors:  Chandra Bellasio; Julie Olejníčková; Radek Tesař; David Sebela; Ladislav Nedbal
Journal:  Sensors (Basel)       Date:  2012-01-18       Impact factor: 3.576

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