Broadacre Mapping of Wheat Biomass Using Ground-Based LiDAR Technology

Crop biomass is an important attribute to consider in relation to site-specific nitrogen (N) management as critical N levels in plants vary depending on crop biomass. Whilst LiDAR technology has been used extensively in small plot-based phenomics studies, large-scale crop scanning has not yet been r...

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Main Authors: André Freitas Colaço, Michael Schaefer, Robert G. V. Bramley
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/13/16/3218
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spelling doaj-e178e9702ef644f3850d53710fd657232021-08-26T14:17:41ZengMDPI AGRemote Sensing2072-42922021-08-01133218321810.3390/rs13163218Broadacre Mapping of Wheat Biomass Using Ground-Based LiDAR TechnologyAndré Freitas Colaço0Michael Schaefer1Robert G. V. Bramley2CSIRO, Waite Campus, Glen Osmond, SA 5064, AustraliaCSIRO, Black Mountain Science and Innovation Park, Acton, ACT 2601, AustraliaCSIRO, Waite Campus, Glen Osmond, SA 5064, AustraliaCrop biomass is an important attribute to consider in relation to site-specific nitrogen (N) management as critical N levels in plants vary depending on crop biomass. Whilst LiDAR technology has been used extensively in small plot-based phenomics studies, large-scale crop scanning has not yet been reported for cereal crops. A LiDAR sensing system was implemented to map a commercial 64-ha wheat paddock to assess the spatial variability of crop biomass. A proximal active reflectance sensor providing spectral indices and estimates of crop height was used as a comparison for the LiDAR system. Plant samples were collected at targeted locations across the field for the assessment of relationships between sensed and measured crop parameters. The correlation between crop biomass and LiDAR-derived crop height was 0.79, which is similar to results reported for plot scanning studies and greatly superior to results obtained for the spectral sensor tested. The LiDAR mapping showed significant crop biomass variability across the field, with estimated values ranging between 460 and 1900 kg ha<sup>−1</sup>. The results are encouraging for the use of LiDAR technology for large-scale operations to support site-specific management. To promote such an approach, we encourage the development of an automated, on-the-go data processing capability and dedicated commercial LiDAR systems for field operation.https://www.mdpi.com/2072-4292/13/16/3218laser scannersite-specific managementnitrogenprecision agriculturedigital agriculture
collection DOAJ
language English
format Article
sources DOAJ
author André Freitas Colaço
Michael Schaefer
Robert G. V. Bramley
spellingShingle André Freitas Colaço
Michael Schaefer
Robert G. V. Bramley
Broadacre Mapping of Wheat Biomass Using Ground-Based LiDAR Technology
Remote Sensing
laser scanner
site-specific management
nitrogen
precision agriculture
digital agriculture
author_facet André Freitas Colaço
Michael Schaefer
Robert G. V. Bramley
author_sort André Freitas Colaço
title Broadacre Mapping of Wheat Biomass Using Ground-Based LiDAR Technology
title_short Broadacre Mapping of Wheat Biomass Using Ground-Based LiDAR Technology
title_full Broadacre Mapping of Wheat Biomass Using Ground-Based LiDAR Technology
title_fullStr Broadacre Mapping of Wheat Biomass Using Ground-Based LiDAR Technology
title_full_unstemmed Broadacre Mapping of Wheat Biomass Using Ground-Based LiDAR Technology
title_sort broadacre mapping of wheat biomass using ground-based lidar technology
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2021-08-01
description Crop biomass is an important attribute to consider in relation to site-specific nitrogen (N) management as critical N levels in plants vary depending on crop biomass. Whilst LiDAR technology has been used extensively in small plot-based phenomics studies, large-scale crop scanning has not yet been reported for cereal crops. A LiDAR sensing system was implemented to map a commercial 64-ha wheat paddock to assess the spatial variability of crop biomass. A proximal active reflectance sensor providing spectral indices and estimates of crop height was used as a comparison for the LiDAR system. Plant samples were collected at targeted locations across the field for the assessment of relationships between sensed and measured crop parameters. The correlation between crop biomass and LiDAR-derived crop height was 0.79, which is similar to results reported for plot scanning studies and greatly superior to results obtained for the spectral sensor tested. The LiDAR mapping showed significant crop biomass variability across the field, with estimated values ranging between 460 and 1900 kg ha<sup>−1</sup>. The results are encouraging for the use of LiDAR technology for large-scale operations to support site-specific management. To promote such an approach, we encourage the development of an automated, on-the-go data processing capability and dedicated commercial LiDAR systems for field operation.
topic laser scanner
site-specific management
nitrogen
precision agriculture
digital agriculture
url https://www.mdpi.com/2072-4292/13/16/3218
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