The Effect of Surrounding Vegetation on Basal Stem Measurements Acquired Using Low-Cost Depth Sensors in Urban and Native Forest Environments
Three colour and depth (RGB-D) devices were compared, to assess the effect of depth image misalignment, resulting from simultaneous localisation and mapping (SLAM) error, due to forest structure complexity. Urban parkland (S1) was used to assess stem density, and understory vegetation (≤1.3 m) was a...
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| Format: | Article |
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MDPI AG
2023-04-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/8/3933 |
| _version_ | 1797603510930374656 |
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| author | James McGlade Luke Wallace Bryan Hally Karin Reinke Simon Jones |
| author_facet | James McGlade Luke Wallace Bryan Hally Karin Reinke Simon Jones |
| author_sort | James McGlade |
| collection | DOAJ |
| description | Three colour and depth (RGB-D) devices were compared, to assess the effect of depth image misalignment, resulting from simultaneous localisation and mapping (SLAM) error, due to forest structure complexity. Urban parkland (S1) was used to assess stem density, and understory vegetation (≤1.3 m) was assessed in native woodland (S2). Individual stem and continuous capture approaches were used, with stem diameter at breast height (DBH) estimated. Misalignment was present within point clouds; however, no significant differences in DBH were observed for stems captured at S1 with either approach (Kinect <i>p</i> = 0.16; iPad <i>p</i> = 0.27; Zed <i>p</i> = 0.79). Using continuous capture, the iPad was the only RGB-D device to maintain SLAM in all S2 plots. There was significant correlation between DBH error and surrounding understory vegetation with the Kinect device (<i>p</i> = 0.04). Conversely, there was no significant relationship between DBH error and understory vegetation for the iPad (<i>p</i> = 0.55) and Zed (<i>p</i> = 0.86). The iPad had the lowest DBH root-mean-square error (RMSE) across both individual stem (RMSE = <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>2.16</mn></mrow></semantics></math></inline-formula><inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi mathvariant="normal">c</mi></semantics></math></inline-formula><inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi mathvariant="normal">m</mi></semantics></math></inline-formula>) and continuous (RMSE = <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>3.23</mn></mrow></semantics></math></inline-formula><inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi mathvariant="normal">c</mi></semantics></math></inline-formula><inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi mathvariant="normal">m</mi></semantics></math></inline-formula>) capture approaches. The results suggest that the assessed RGB-D devices are more capable of operation within complex forest environments than previous generations. |
| first_indexed | 2024-03-11T04:33:09Z |
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| id | doaj.art-902dc3e0278d42e6bc86ab73641393d7 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T04:33:09Z |
| publishDate | 2023-04-01 |
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| spelling | doaj.art-902dc3e0278d42e6bc86ab73641393d72023-11-17T21:16:45ZengMDPI AGSensors1424-82202023-04-01238393310.3390/s23083933The Effect of Surrounding Vegetation on Basal Stem Measurements Acquired Using Low-Cost Depth Sensors in Urban and Native Forest EnvironmentsJames McGlade0Luke Wallace1Bryan Hally2Karin Reinke3Simon Jones4School of Science, Royal Melbourne Institute of Technology Univeristy, 124 La Trobe St, Melbourne, VIC 3000, AustraliaSchool of Geography, Planning and Spatial Sciences, University of Tasmania, Churchill Ave, Hobart, TAS 7001, AustraliaSchool of Science, Royal Melbourne Institute of Technology Univeristy, 124 La Trobe St, Melbourne, VIC 3000, AustraliaSchool of Science, Royal Melbourne Institute of Technology Univeristy, 124 La Trobe St, Melbourne, VIC 3000, AustraliaSchool of Science, Royal Melbourne Institute of Technology Univeristy, 124 La Trobe St, Melbourne, VIC 3000, AustraliaThree colour and depth (RGB-D) devices were compared, to assess the effect of depth image misalignment, resulting from simultaneous localisation and mapping (SLAM) error, due to forest structure complexity. Urban parkland (S1) was used to assess stem density, and understory vegetation (≤1.3 m) was assessed in native woodland (S2). Individual stem and continuous capture approaches were used, with stem diameter at breast height (DBH) estimated. Misalignment was present within point clouds; however, no significant differences in DBH were observed for stems captured at S1 with either approach (Kinect <i>p</i> = 0.16; iPad <i>p</i> = 0.27; Zed <i>p</i> = 0.79). Using continuous capture, the iPad was the only RGB-D device to maintain SLAM in all S2 plots. There was significant correlation between DBH error and surrounding understory vegetation with the Kinect device (<i>p</i> = 0.04). Conversely, there was no significant relationship between DBH error and understory vegetation for the iPad (<i>p</i> = 0.55) and Zed (<i>p</i> = 0.86). The iPad had the lowest DBH root-mean-square error (RMSE) across both individual stem (RMSE = <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>2.16</mn></mrow></semantics></math></inline-formula><inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi mathvariant="normal">c</mi></semantics></math></inline-formula><inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi mathvariant="normal">m</mi></semantics></math></inline-formula>) and continuous (RMSE = <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>3.23</mn></mrow></semantics></math></inline-formula><inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi mathvariant="normal">c</mi></semantics></math></inline-formula><inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi mathvariant="normal">m</mi></semantics></math></inline-formula>) capture approaches. The results suggest that the assessed RGB-D devices are more capable of operation within complex forest environments than previous generations.https://www.mdpi.com/1424-8220/23/8/3933RGB-Dforestryinventorylow-costremote sensing |
| spellingShingle | James McGlade Luke Wallace Bryan Hally Karin Reinke Simon Jones The Effect of Surrounding Vegetation on Basal Stem Measurements Acquired Using Low-Cost Depth Sensors in Urban and Native Forest Environments Sensors RGB-D forestry inventory low-cost remote sensing |
| title | The Effect of Surrounding Vegetation on Basal Stem Measurements Acquired Using Low-Cost Depth Sensors in Urban and Native Forest Environments |
| title_full | The Effect of Surrounding Vegetation on Basal Stem Measurements Acquired Using Low-Cost Depth Sensors in Urban and Native Forest Environments |
| title_fullStr | The Effect of Surrounding Vegetation on Basal Stem Measurements Acquired Using Low-Cost Depth Sensors in Urban and Native Forest Environments |
| title_full_unstemmed | The Effect of Surrounding Vegetation on Basal Stem Measurements Acquired Using Low-Cost Depth Sensors in Urban and Native Forest Environments |
| title_short | The Effect of Surrounding Vegetation on Basal Stem Measurements Acquired Using Low-Cost Depth Sensors in Urban and Native Forest Environments |
| title_sort | effect of surrounding vegetation on basal stem measurements acquired using low cost depth sensors in urban and native forest environments |
| topic | RGB-D forestry inventory low-cost remote sensing |
| url | https://www.mdpi.com/1424-8220/23/8/3933 |
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