Assessing the Capability and Potential of LiDAR for Weed Detection
Conventional methods of uniformly spraying fields to combat weeds, requires large herbicide inputs at significant cost with impacts on the environment. More focused weed control methods such as site-specific weed management (SSWM) have become popular but require methods to identify weed locations. A...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-03-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/21/7/2328 |
| _version_ | 1797539817425207296 |
|---|---|
| author | Nooshin Shahbazi Michael B. Ashworth J. Nikolaus Callow Ajmal Mian Hugh J. Beckie Stuart Speidel Elliot Nicholls Ken C. Flower |
| author_facet | Nooshin Shahbazi Michael B. Ashworth J. Nikolaus Callow Ajmal Mian Hugh J. Beckie Stuart Speidel Elliot Nicholls Ken C. Flower |
| author_sort | Nooshin Shahbazi |
| collection | DOAJ |
| description | Conventional methods of uniformly spraying fields to combat weeds, requires large herbicide inputs at significant cost with impacts on the environment. More focused weed control methods such as site-specific weed management (SSWM) have become popular but require methods to identify weed locations. Advances in technology allows the potential for automated methods such as drone, but also ground-based sensors for detecting and mapping weeds. In this study, the capability of Light Detection and Ranging (LiDAR) sensors were assessed to detect and locate weeds. For this purpose, two trials were performed using artificial targets (representing weeds) at different heights and diameter to understand the detection limits of a LiDAR. The results showed the detectability of the target at different scanning distances from the LiDAR was directly influenced by the size of the target and its orientation toward the LiDAR. A third trial was performed in a wheat plot where the LiDAR was used to scan different weed species at various heights above the crop canopy, to verify the capacity of the stationary LiDAR to detect weeds in a field situation. The results showed that 100% of weeds in the wheat plot were detected by the LiDAR, based on their height differences with the crop canopy. |
| first_indexed | 2024-03-10T12:51:15Z |
| format | Article |
| id | doaj.art-665a71a571204bc590ac3a56c7cb8365 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T12:51:15Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-665a71a571204bc590ac3a56c7cb83652023-11-21T13:01:33ZengMDPI AGSensors1424-82202021-03-01217232810.3390/s21072328Assessing the Capability and Potential of LiDAR for Weed DetectionNooshin Shahbazi0Michael B. Ashworth1J. Nikolaus Callow2Ajmal Mian3Hugh J. Beckie4Stuart Speidel5Elliot Nicholls6Ken C. Flower7UWA School of Agriculture and Environment, The University of Western Australia, Crawley, Stirling Highway, WA 6009, AustraliaUWA School of Agriculture and Environment, The University of Western Australia, Crawley, Stirling Highway, WA 6009, AustraliaUWA School of Agriculture and Environment, The University of Western Australia, Crawley, Stirling Highway, WA 6009, AustraliaUWA School of Computer Science and Software Engineering, The University of Western Australia, Crawley, Stirling Highway, WA 6009, AustraliaUWA School of Agriculture and Environment, The University of Western Australia, Crawley, Stirling Highway, WA 6009, AustraliaStealth Technologies, 138 Churchill Avenue, Subiaco, WA 6008, AustraliaStealth Technologies, 138 Churchill Avenue, Subiaco, WA 6008, AustraliaUWA School of Agriculture and Environment, The University of Western Australia, Crawley, Stirling Highway, WA 6009, AustraliaConventional methods of uniformly spraying fields to combat weeds, requires large herbicide inputs at significant cost with impacts on the environment. More focused weed control methods such as site-specific weed management (SSWM) have become popular but require methods to identify weed locations. Advances in technology allows the potential for automated methods such as drone, but also ground-based sensors for detecting and mapping weeds. In this study, the capability of Light Detection and Ranging (LiDAR) sensors were assessed to detect and locate weeds. For this purpose, two trials were performed using artificial targets (representing weeds) at different heights and diameter to understand the detection limits of a LiDAR. The results showed the detectability of the target at different scanning distances from the LiDAR was directly influenced by the size of the target and its orientation toward the LiDAR. A third trial was performed in a wheat plot where the LiDAR was used to scan different weed species at various heights above the crop canopy, to verify the capacity of the stationary LiDAR to detect weeds in a field situation. The results showed that 100% of weeds in the wheat plot were detected by the LiDAR, based on their height differences with the crop canopy.https://www.mdpi.com/1424-8220/21/7/2328light detection and ranging (LiDAR) sensorsweed detectiontarget sizescanning distancetarget orientation |
| spellingShingle | Nooshin Shahbazi Michael B. Ashworth J. Nikolaus Callow Ajmal Mian Hugh J. Beckie Stuart Speidel Elliot Nicholls Ken C. Flower Assessing the Capability and Potential of LiDAR for Weed Detection Sensors light detection and ranging (LiDAR) sensors weed detection target size scanning distance target orientation |
| title | Assessing the Capability and Potential of LiDAR for Weed Detection |
| title_full | Assessing the Capability and Potential of LiDAR for Weed Detection |
| title_fullStr | Assessing the Capability and Potential of LiDAR for Weed Detection |
| title_full_unstemmed | Assessing the Capability and Potential of LiDAR for Weed Detection |
| title_short | Assessing the Capability and Potential of LiDAR for Weed Detection |
| title_sort | assessing the capability and potential of lidar for weed detection |
| topic | light detection and ranging (LiDAR) sensors weed detection target size scanning distance target orientation |
| url | https://www.mdpi.com/1424-8220/21/7/2328 |
| work_keys_str_mv | AT nooshinshahbazi assessingthecapabilityandpotentialoflidarforweeddetection AT michaelbashworth assessingthecapabilityandpotentialoflidarforweeddetection AT jnikolauscallow assessingthecapabilityandpotentialoflidarforweeddetection AT ajmalmian assessingthecapabilityandpotentialoflidarforweeddetection AT hughjbeckie assessingthecapabilityandpotentialoflidarforweeddetection AT stuartspeidel assessingthecapabilityandpotentialoflidarforweeddetection AT elliotnicholls assessingthecapabilityandpotentialoflidarforweeddetection AT kencflower assessingthecapabilityandpotentialoflidarforweeddetection |