Crop height monitoring using a consumer-grade camera and UAV Technology
Recent advances in the ability to capture high spatial resolution images by unmanned aerial vehicles (UAVs) have shown the potential of this technology for a wide range of application including exploring the effects of different external stimuli when monitoring environmental and structural variables...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Language: | English |
| Published: |
Springer Nature
2019
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/80202 |
| _version_ | 1848764180645019648 |
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| author | Belton, David Helmholz, Petra Long, John Zerihun, Ayalsew |
| author_facet | Belton, David Helmholz, Petra Long, John Zerihun, Ayalsew |
| author_sort | Belton, David |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Recent advances in the ability to capture high spatial resolution images by unmanned aerial vehicles (UAVs) have shown the potential of this technology for a wide range of application including exploring the effects of different external stimuli when monitoring environmental and structural variables. In this paper, we show the application of UAV technology for crop height monitoring and modelling to provide quantitative crop growth data and demonstrate the remote sensing and photogrammetric
capabilities of the technology to the farming industry. This study was carried out in a field trial involving a combination of six wheat varieties and three different fungicide treatments. The UAV imagery of the field trial site was captured on five occasions throughout crop development. These were used to create digital surface models from which crop surface models
(CSMs) were extracted for the cropped areas. Crop heights are estimated from the photogrammetric derived CSMs and are compared against the reference heights captured using Real-Time Kinematic Global Navigation Satellite System (GNSS) to validate the CSMs. Furthermore, crop growth differences among varieties are analysed; and crop height correlations
with grain yield as well as with independently estimated vegetation indices are evaluated. These evaluations show that the technology is suitable (with average bias range 2–10 cm depending on wind conditions relative to GNSS height) and has potential for quantitative and qualitative monitoring of canopy and/or crop height and growth. |
| first_indexed | 2025-11-14T11:15:16Z |
| format | Journal Article |
| id | curtin-20.500.11937-80202 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:15:16Z |
| publishDate | 2019 |
| publisher | Springer Nature |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-802022020-12-09T02:29:35Z Crop height monitoring using a consumer-grade camera and UAV Technology Belton, David Helmholz, Petra Long, John Zerihun, Ayalsew Science & Technology Technology Remote Sensing Imaging Science & Photographic Technology Crop monitoring Crop surface model Digital surface model Low-cost sensor system Unmanned aerial vehicles UAV in agriculture PHOTOGRAMMETRY SYSTEMS YIELD MODEL LIDAR Recent advances in the ability to capture high spatial resolution images by unmanned aerial vehicles (UAVs) have shown the potential of this technology for a wide range of application including exploring the effects of different external stimuli when monitoring environmental and structural variables. In this paper, we show the application of UAV technology for crop height monitoring and modelling to provide quantitative crop growth data and demonstrate the remote sensing and photogrammetric capabilities of the technology to the farming industry. This study was carried out in a field trial involving a combination of six wheat varieties and three different fungicide treatments. The UAV imagery of the field trial site was captured on five occasions throughout crop development. These were used to create digital surface models from which crop surface models (CSMs) were extracted for the cropped areas. Crop heights are estimated from the photogrammetric derived CSMs and are compared against the reference heights captured using Real-Time Kinematic Global Navigation Satellite System (GNSS) to validate the CSMs. Furthermore, crop growth differences among varieties are analysed; and crop height correlations with grain yield as well as with independently estimated vegetation indices are evaluated. These evaluations show that the technology is suitable (with average bias range 2–10 cm depending on wind conditions relative to GNSS height) and has potential for quantitative and qualitative monitoring of canopy and/or crop height and growth. 2019 Journal Article http://hdl.handle.net/20.500.11937/80202 10.1007/s41064-019-00087-8 English Springer Nature fulltext |
| spellingShingle | Science & Technology Technology Remote Sensing Imaging Science & Photographic Technology Crop monitoring Crop surface model Digital surface model Low-cost sensor system Unmanned aerial vehicles UAV in agriculture PHOTOGRAMMETRY SYSTEMS YIELD MODEL LIDAR Belton, David Helmholz, Petra Long, John Zerihun, Ayalsew Crop height monitoring using a consumer-grade camera and UAV Technology |
| title | Crop height monitoring using a consumer-grade camera and UAV Technology |
| title_full | Crop height monitoring using a consumer-grade camera and UAV Technology |
| title_fullStr | Crop height monitoring using a consumer-grade camera and UAV Technology |
| title_full_unstemmed | Crop height monitoring using a consumer-grade camera and UAV Technology |
| title_short | Crop height monitoring using a consumer-grade camera and UAV Technology |
| title_sort | crop height monitoring using a consumer-grade camera and uav technology |
| topic | Science & Technology Technology Remote Sensing Imaging Science & Photographic Technology Crop monitoring Crop surface model Digital surface model Low-cost sensor system Unmanned aerial vehicles UAV in agriculture PHOTOGRAMMETRY SYSTEMS YIELD MODEL LIDAR |
| url | http://hdl.handle.net/20.500.11937/80202 |