Investigating the role of UAVs and convolutional neural networks in the identification of invasive plant species in the Albany Thicket
- Authors: Wesson, Frank Cameron
- Date: 2023-04
- Subjects: Drone aircraft -- Control systems , Drone -- South Africa , Albany Thicket -- South Africa
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10948/61097 , vital:69755
- Description: The study aimed to determine whether plant species could be classified by using high resolution aerial imagery and a convolutional neural network (CNN). The full capabilities of a CNN were examined including testing whether the platform could be used for land cover and the evaluation of land change over time. A drone or unmanned aerial vehicle (UAV) was used to collect the aerial data of the study area, and 45 subplots were used for the image analysis. The CNN was coded and operated in RStudio, and digitised data from the input imagery were used as training and validation data by the programme to learn features. Four classifications were performed using various quantities of input data to access the performance of the neural network. In addition, tests were performed to understand whether the CNN could be used as a land cover and land change detection tool. Accuracy assessments were done on the results to test reliability and accuracy. The best-performing classification achieved an average user and producer accuracy of above 90%, while the overall accuracy was 93%, and the kappa coefficient score was 0.86. The CNN was also able to predict the land coverage area of Opuntia to be within 4% of the ground truthing data area. A change in land cover over time was detected by the programme after the manual clearing of the invasive plant had been undertaken. This research has determined that the use of a CNN in remote sensing is a very powerful tool for supervised image classifications and that it can be used for monitoring land cover by accurately estimating the spatial distribution of plant species and by monitoring the species' growth or decline over time. A CNN could also be used as a tool for landowners to prove that they are making efforts to clear invasive species from their land. , Thesis (MSc) -- Faculty of Science, School of Environmental Sciences, 2023
- Full Text:
- Date Issued: 2023-04
- Authors: Wesson, Frank Cameron
- Date: 2023-04
- Subjects: Drone aircraft -- Control systems , Drone -- South Africa , Albany Thicket -- South Africa
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10948/61097 , vital:69755
- Description: The study aimed to determine whether plant species could be classified by using high resolution aerial imagery and a convolutional neural network (CNN). The full capabilities of a CNN were examined including testing whether the platform could be used for land cover and the evaluation of land change over time. A drone or unmanned aerial vehicle (UAV) was used to collect the aerial data of the study area, and 45 subplots were used for the image analysis. The CNN was coded and operated in RStudio, and digitised data from the input imagery were used as training and validation data by the programme to learn features. Four classifications were performed using various quantities of input data to access the performance of the neural network. In addition, tests were performed to understand whether the CNN could be used as a land cover and land change detection tool. Accuracy assessments were done on the results to test reliability and accuracy. The best-performing classification achieved an average user and producer accuracy of above 90%, while the overall accuracy was 93%, and the kappa coefficient score was 0.86. The CNN was also able to predict the land coverage area of Opuntia to be within 4% of the ground truthing data area. A change in land cover over time was detected by the programme after the manual clearing of the invasive plant had been undertaken. This research has determined that the use of a CNN in remote sensing is a very powerful tool for supervised image classifications and that it can be used for monitoring land cover by accurately estimating the spatial distribution of plant species and by monitoring the species' growth or decline over time. A CNN could also be used as a tool for landowners to prove that they are making efforts to clear invasive species from their land. , Thesis (MSc) -- Faculty of Science, School of Environmental Sciences, 2023
- Full Text:
- Date Issued: 2023-04
Future technological factors affecting unmanned aircraft systems (UAS):a South African perspective towards 2025
- Authors: Marope, Tumisang
- Date: 2015
- Subjects: Drone aircraft -- Control systems , Drone aircraft pilots -- South Africa
- Language: English
- Type: Thesis , Masters , MBA
- Identifier: http://hdl.handle.net/10948/2939 , vital:20371
- Description: The fact that pilots are not physically situated in the aircraft for UAS operations makes the current standards applicable to manned aircraft not suitable for UAS operations (FAA, 2013). FAA (2013:18) states that ―removing the pilot from the aircraft creates a series of performance considerations between manned and unmanned aircraft that need to be fully researched and understood to determine acceptability and potential impact on safe operations in the NAS. According to ERSG (2013), not all technologies necessary to ensure the safe integration of civil UASs into civilian airspace are available today. The extrapolation that can be made based on the above arguments is that advancement of UAS technologies will more likely have a significant bearing on the safe integration of UASs into civilian airspace. Therefore, as an identified research gap, the research/main objective of this research is to identify future technological factors affecting Unmanned Aircraft Systems in the Republic of South Africa leading towards the year 2025.
- Full Text:
- Date Issued: 2015
- Authors: Marope, Tumisang
- Date: 2015
- Subjects: Drone aircraft -- Control systems , Drone aircraft pilots -- South Africa
- Language: English
- Type: Thesis , Masters , MBA
- Identifier: http://hdl.handle.net/10948/2939 , vital:20371
- Description: The fact that pilots are not physically situated in the aircraft for UAS operations makes the current standards applicable to manned aircraft not suitable for UAS operations (FAA, 2013). FAA (2013:18) states that ―removing the pilot from the aircraft creates a series of performance considerations between manned and unmanned aircraft that need to be fully researched and understood to determine acceptability and potential impact on safe operations in the NAS. According to ERSG (2013), not all technologies necessary to ensure the safe integration of civil UASs into civilian airspace are available today. The extrapolation that can be made based on the above arguments is that advancement of UAS technologies will more likely have a significant bearing on the safe integration of UASs into civilian airspace. Therefore, as an identified research gap, the research/main objective of this research is to identify future technological factors affecting Unmanned Aircraft Systems in the Republic of South Africa leading towards the year 2025.
- Full Text:
- Date Issued: 2015
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