An investigation of geospatial technologies in precision agriculture: a case study on a citrus orchard in the Eastern Cape
- Authors: Nish, Declan Mark
- Date: 2024-10-11
- Subjects: Geospatial technology , Agricultural innovations , Precision farming South Africa Eastern Cape , Citrus orchard , Citrus fruit industry , Drone aircraft , Remote sensing
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/465080 , vital:76571
- Description: Citrus production is an input-intensive farming practice that carries a high cost of production. A multitude of both local and global factors continue to put pressure on farmers to produce enough food for local consumption as well as international exports. Despite these challenges production and exports continue to increase, fighting to meet the growing rise in global demand for citrus (Genis, 2018). Growers are continuously in search of anything that may provide them with the ‘edge’ or an advantage to overcoming some of these challenges (Jupp, 2018). One way in which these issues could be addressed is the use of precision agriculture (PA). Precision agriculture, particularly that of commercial, Unmanned Aerial Vehicle (UAV) based PA, provides growers with solutions to these issues in the form of high quality, near real-time data, and provides access and benefits from technology driven agriculture to growers at all levels (Sishodia et al. 2020). The aim of this research therefore was to investigate the potential of high resolution, multi-spectral UAV, and satellite imagery to help citrus farmers manage their inputs better, save costs and increase their yields in a sustainable manner. Supervised image classification using a support vector machine (SVM) was applied to map and classify a citrus farm in the Eastern Cape. The approach aided the identification of Phytophthora spp in the section of interest and implies that remotely sensed data can be used to detect changes in citrus health. Guidelines for applying geospatial technologies at farm level were developed to provide a framework for enabling growers to enhance data driven farm management strategies. , Thesis (MSc) -- Faculty of Science, Geography, 2024
- Full Text:
- Authors: Nish, Declan Mark
- Date: 2024-10-11
- Subjects: Geospatial technology , Agricultural innovations , Precision farming South Africa Eastern Cape , Citrus orchard , Citrus fruit industry , Drone aircraft , Remote sensing
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/465080 , vital:76571
- Description: Citrus production is an input-intensive farming practice that carries a high cost of production. A multitude of both local and global factors continue to put pressure on farmers to produce enough food for local consumption as well as international exports. Despite these challenges production and exports continue to increase, fighting to meet the growing rise in global demand for citrus (Genis, 2018). Growers are continuously in search of anything that may provide them with the ‘edge’ or an advantage to overcoming some of these challenges (Jupp, 2018). One way in which these issues could be addressed is the use of precision agriculture (PA). Precision agriculture, particularly that of commercial, Unmanned Aerial Vehicle (UAV) based PA, provides growers with solutions to these issues in the form of high quality, near real-time data, and provides access and benefits from technology driven agriculture to growers at all levels (Sishodia et al. 2020). The aim of this research therefore was to investigate the potential of high resolution, multi-spectral UAV, and satellite imagery to help citrus farmers manage their inputs better, save costs and increase their yields in a sustainable manner. Supervised image classification using a support vector machine (SVM) was applied to map and classify a citrus farm in the Eastern Cape. The approach aided the identification of Phytophthora spp in the section of interest and implies that remotely sensed data can be used to detect changes in citrus health. Guidelines for applying geospatial technologies at farm level were developed to provide a framework for enabling growers to enhance data driven farm management strategies. , Thesis (MSc) -- Faculty of Science, Geography, 2024
- Full Text:
Investigating changes in pineapple (Ananas comosus) cultivation in the Eastern Cape, South Africa, from 1984 to 2020
- Authors: Marriner, Paul Joseph
- Date: 2024-04-04
- Subjects: Pineapple South Africa Eastern Cape , Land use and land cover , Land cover , Remote sensing , Image classification
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/435354 , vital:73150
- Description: Land use and land cover change (LULCC) resulting from agricultural activities have significantly impacted landscape transformation and fragmentation. The Albany Thicket Biome in the Eastern Cape Province stands out for its exceptional vegetation diversity and remarkable rates of species endemism. However, the relationship between agricultural activities and the Albany Thicket Biome has not received sufficient attention in the literature, creating a significant gap in understanding the extent of landscape transformation and the vegetation's recovery rate. This study aims to address this gap by utilising remote sensing technologies to investigate the LULCC specifically caused by pineapple cultivation in the Lower Albany area between 1984 and 2020. Analysis, using remotely sensed imagery and spatial analytical tools, provide accurate identification of pineapple fields and enable monitoring of their effects on LULCC dynamics across a wide spatial and temporal scale. Complementary field assessments examined the impacts of pineapple cultivation on land use and cover. Twelve image classifiers were tested to identify the most appropriate technique for mapping pineapple fields, and the Supervised Pixel-based Support Vector Machine (SVM) image classifier was found to be the most suitable. Utilising Landsat 4, 5, 7, and 8 satellite imagery, 27 land cover maps were created, spanning the period from 1984 to 2020. Additionally, field verification was conducted at 59 randomly generated sites to validate the findings. Spatial analysis of the data revealed that the pineapple industry in the study area has expanded by 733 hectares since 1984. Significant land use changes were observed, including converting land to wildlife ranches, grazing areas, and alternative agricultural practices. The land cover analysis identified the emergence of pioneer species in former pineapple fields, suggesting the potential for Albany Thicket regrowth if appropriately managed. This research contributes to a better understanding of the impacts of pineapple cultivation on the Albany Thicket Biome and provides valuable insights for land use planning and monitoring efforts. A comprehensive assessment of LULCC dynamics can be achieved by utilising remote sensing techniques, informing sustainable land management practices in the study area and beyond. , Thesis (MSc) -- Faculty of Science, Geography, 2024
- Full Text:
- Authors: Marriner, Paul Joseph
- Date: 2024-04-04
- Subjects: Pineapple South Africa Eastern Cape , Land use and land cover , Land cover , Remote sensing , Image classification
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/435354 , vital:73150
- Description: Land use and land cover change (LULCC) resulting from agricultural activities have significantly impacted landscape transformation and fragmentation. The Albany Thicket Biome in the Eastern Cape Province stands out for its exceptional vegetation diversity and remarkable rates of species endemism. However, the relationship between agricultural activities and the Albany Thicket Biome has not received sufficient attention in the literature, creating a significant gap in understanding the extent of landscape transformation and the vegetation's recovery rate. This study aims to address this gap by utilising remote sensing technologies to investigate the LULCC specifically caused by pineapple cultivation in the Lower Albany area between 1984 and 2020. Analysis, using remotely sensed imagery and spatial analytical tools, provide accurate identification of pineapple fields and enable monitoring of their effects on LULCC dynamics across a wide spatial and temporal scale. Complementary field assessments examined the impacts of pineapple cultivation on land use and cover. Twelve image classifiers were tested to identify the most appropriate technique for mapping pineapple fields, and the Supervised Pixel-based Support Vector Machine (SVM) image classifier was found to be the most suitable. Utilising Landsat 4, 5, 7, and 8 satellite imagery, 27 land cover maps were created, spanning the period from 1984 to 2020. Additionally, field verification was conducted at 59 randomly generated sites to validate the findings. Spatial analysis of the data revealed that the pineapple industry in the study area has expanded by 733 hectares since 1984. Significant land use changes were observed, including converting land to wildlife ranches, grazing areas, and alternative agricultural practices. The land cover analysis identified the emergence of pioneer species in former pineapple fields, suggesting the potential for Albany Thicket regrowth if appropriately managed. This research contributes to a better understanding of the impacts of pineapple cultivation on the Albany Thicket Biome and provides valuable insights for land use planning and monitoring efforts. A comprehensive assessment of LULCC dynamics can be achieved by utilising remote sensing techniques, informing sustainable land management practices in the study area and beyond. , Thesis (MSc) -- Faculty of Science, Geography, 2024
- Full Text:
Relating vegetation distribution to cycles of erosion and deposition in the Kromme River wetlands
- Authors: Jarvis, Samuel Cameron
- Date: 2023-10-13
- Subjects: Biogeomorphology South Africa Kromme Estuary (Eastern Cape) , Earth observation , Remote sensing , Niche construction , Wetland ecology , Geomorphology , Ecological succession , Optical radar , Prionium serratum
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/424582 , vital:72166
- Description: The role of geomorphic disturbance has been increasingly recognized as fundamental in the creation and functioning of wetlands. This is true of the Kromme River wetland which has been formed through repeated cycles of erosion and deposition. However, the response – and influence – of wetland plants to these sorts of disturbance has not been investigated. This study sought to fill this knowledge gap by classifying vegetation communities over a range of hydrological and geomorphic disturbance regimes that have happened over the last few decades, and relating those vegetation communities to environmental factors. The study identified seven vegetation communities based on their species composition and abundance, which were related to geomorphic disturbance events. A conceptual model that accounts for vegetation distribution in the Kromme wetland was developed. Soil saturation was the most important factor explaining vegetation community distribution, which, in turn, is influenced by cycles of erosion and deposition. Following an erosional event on the valley floor, Prionium serratum dominated wetland is converted to a number of other vegetation communities. On the floodplain surface adjacent to the eroded gully, the Prionium serratum dominated wetland is transformed over time to Cynodon dactylon and Sporobolus fimbriatus communities. Prionium serratum clumps immediately adjacent to the recently incised gullies are able to persist, having sufficient access to water. Within the newly formed gullies, Juncus lomatophyllus colonizes the gully beds flooded to a shallow depth, Miscanthus capensis colonizes the gully bars and Setaria incrassata colonizes the exposed gully banks. Localised depositional features close to the thalweg in the gully are colonized by Prionium serratum seedlings and vegetative propagules. These plants represent the regenerating phase of Prionium serratum wetland, which also colonizes depositional floodouts downstream of the newly-formed gully. The Stenotaphrum secundatum community dominates drier, more elevated areas of the floodout. Over time, as the gully fills, Prionium serratum expands beyond the gully onto the valley floor, to replace the floodplain communities Cynodon dactylon and Sporobolus fimbriatus. Over time, Prionium serratum is thought to colonize the valley floor as the gully fills, stabilising it and promoting diffuse flow. Many restoration efforts in damaged palmiet wetlands have been focused on the preservation of intact palmiet communities upstream of erosional headcuts, with limited understanding of vegetation dynamics associated with the cut-and-fill cycles that naturally occur in these wetlands. Understanding the regeneration of Prionium serratum following erosional events is thus important for wetland restoration, as it should focus more attention on promoting palmiet restoration on depositional floodouts downstream of eroded gullies. A secondary aim of this study was to explore the possibility of mapping palmiet communities in Kromme River wetland using remote sensing techniques. Using a combination of ground-truthed data from this and previous studies in the Kromme River wetland, together with raster layers derived from a LiDAR survey, an overlay analysis was developed to effectively map the distribution of the Prionium serratum dominated community. The overlay was created using a machine learning library in RStudios known as Rpart. The results found that the model were 91% effective in classifying the distribution of the Prionium serratum community. A secondary finding was that the inclusion of a Relative Elevation Model in the overlay analysis allowed for the identification of Prionium serratum communities vulnerable to degradation following previous geomorphic disturbance events and those Prionium serratum communities that are likely to persist following a geomorphic disturbance event. , Thesis (MSc) -- Faculty of Science, Geography, 2023
- Full Text:
- Authors: Jarvis, Samuel Cameron
- Date: 2023-10-13
- Subjects: Biogeomorphology South Africa Kromme Estuary (Eastern Cape) , Earth observation , Remote sensing , Niche construction , Wetland ecology , Geomorphology , Ecological succession , Optical radar , Prionium serratum
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/424582 , vital:72166
- Description: The role of geomorphic disturbance has been increasingly recognized as fundamental in the creation and functioning of wetlands. This is true of the Kromme River wetland which has been formed through repeated cycles of erosion and deposition. However, the response – and influence – of wetland plants to these sorts of disturbance has not been investigated. This study sought to fill this knowledge gap by classifying vegetation communities over a range of hydrological and geomorphic disturbance regimes that have happened over the last few decades, and relating those vegetation communities to environmental factors. The study identified seven vegetation communities based on their species composition and abundance, which were related to geomorphic disturbance events. A conceptual model that accounts for vegetation distribution in the Kromme wetland was developed. Soil saturation was the most important factor explaining vegetation community distribution, which, in turn, is influenced by cycles of erosion and deposition. Following an erosional event on the valley floor, Prionium serratum dominated wetland is converted to a number of other vegetation communities. On the floodplain surface adjacent to the eroded gully, the Prionium serratum dominated wetland is transformed over time to Cynodon dactylon and Sporobolus fimbriatus communities. Prionium serratum clumps immediately adjacent to the recently incised gullies are able to persist, having sufficient access to water. Within the newly formed gullies, Juncus lomatophyllus colonizes the gully beds flooded to a shallow depth, Miscanthus capensis colonizes the gully bars and Setaria incrassata colonizes the exposed gully banks. Localised depositional features close to the thalweg in the gully are colonized by Prionium serratum seedlings and vegetative propagules. These plants represent the regenerating phase of Prionium serratum wetland, which also colonizes depositional floodouts downstream of the newly-formed gully. The Stenotaphrum secundatum community dominates drier, more elevated areas of the floodout. Over time, as the gully fills, Prionium serratum expands beyond the gully onto the valley floor, to replace the floodplain communities Cynodon dactylon and Sporobolus fimbriatus. Over time, Prionium serratum is thought to colonize the valley floor as the gully fills, stabilising it and promoting diffuse flow. Many restoration efforts in damaged palmiet wetlands have been focused on the preservation of intact palmiet communities upstream of erosional headcuts, with limited understanding of vegetation dynamics associated with the cut-and-fill cycles that naturally occur in these wetlands. Understanding the regeneration of Prionium serratum following erosional events is thus important for wetland restoration, as it should focus more attention on promoting palmiet restoration on depositional floodouts downstream of eroded gullies. A secondary aim of this study was to explore the possibility of mapping palmiet communities in Kromme River wetland using remote sensing techniques. Using a combination of ground-truthed data from this and previous studies in the Kromme River wetland, together with raster layers derived from a LiDAR survey, an overlay analysis was developed to effectively map the distribution of the Prionium serratum dominated community. The overlay was created using a machine learning library in RStudios known as Rpart. The results found that the model were 91% effective in classifying the distribution of the Prionium serratum community. A secondary finding was that the inclusion of a Relative Elevation Model in the overlay analysis allowed for the identification of Prionium serratum communities vulnerable to degradation following previous geomorphic disturbance events and those Prionium serratum communities that are likely to persist following a geomorphic disturbance event. , Thesis (MSc) -- Faculty of Science, Geography, 2023
- Full Text:
Remote sensing as a monitoring solution for water hyacinth (Pontederia crassipes) in the context of the biological control programme at Hartbeespoort Dam
- Authors: Kinsler, David Louis
- Date: 2023-10-13
- Subjects: Remote sensing , Water hyacinth South Africa Hartbeespoort , Aquatic weeds Biological control South Africa Hartbeespoort , Megamelus scutellaris , Eutrophication
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/424599 , vital:72167
- Description: Water hyacinth (Pontederia crassipes (C.Mart.) Solms (Pontederiaceae)) is a significant aquatic weed both globally and in South Africa. Despite notable success with biological control of other invasive macrophytes, the plant remains as a problematic weed in many aquatic systems in South Africa, particularly due to the eutrophic status of many of its water systems, as well as the plant’s tolerance to cooler climatic conditions than most of its existing biological control agents. Hartbeespoort Dam, located about 30 kilometres west of Pretoria, South Africa, has been infamously infested with water hyacinth for decades, which impacts the important socioeconomic utility of the dam and functioning of natural ecological processes in the system. The dam has a long history of efforts to control water hyacinth, which include widespread herbicidal spray, mechanical removal and classical biological control programmes since the early 1990s - mostly with limited or short-lived success. However, after the introduction of a new, cold-tolerant biological control agent, Megamelus scutellaris Berg (Hemiptera: Delphacidae) in 2018 with an inundative release strategy, the water hyacinth dropped significantly from a maximum cover of about 45 percent (819 hectares) down to less than two percent (40 hectares) over a three-month period (November 2019 – January 2020). This was significant, as it marked the first successful biological control of water hyacinth in a eutrophic, temperate system in South Africa. However, due to the scale of Hartbeespoort Dam (1820 hectares) and the high spatiotemporal variation of the floating mats across time and space, quantifying and monitoring these rapid changes has proved difficult. In response to this problem, this thesis proposed a remote sensing solution to address the need for accurate, timely and readily accessible monitoring data of the water hyacinth population on the dam. Leveraging the temporally frequent (< 5 days revisit time) Sentinel-2 multispectral satellite data, as well as the powerful cloud-computing resources of Google Earth Engine, this thesis developed and deployed a relatively simple and robust index-based decision tree classification method to demonstrate the value of these technologies as an effective monitoring and analysis tool for monitoring large macrophyte infestations. To this end, several challenges had to be overcome in order to produce easily accessible data that was accurate and reliable. For example, due to the size of the Sentinel-2 Level-1C image dataset from August 2015 to March 2021 (n = 654), an automated process of filtering out clouded images was required. Additionally, the co-presence of algal and cyanobacterial blooms necessitated the development of a novel index, coined the Algae Resistant Macrophyte Index (ARMI), to deal with the challenges of accurate macrophyte detection. The high spatiotemporal variability of the floating mats meant that a typical, location-based confusion matrix as a means of assessing the accuracy of the decision tree classifier required a different approach which compared the total classified areas with higher resolution images. This thesis aims to demonstrate the utility of remote sensing tools to provide effective monitoring information to managers, researchers and other stakeholders. There is scope to expand to more areas in South Africa and beyond and may prove an invaluable tool to augment and support on-going and future macrophyte monitoring programmes. , Thesis (MSc) -- Faculty of Science, Geography, 2023
- Full Text:
- Authors: Kinsler, David Louis
- Date: 2023-10-13
- Subjects: Remote sensing , Water hyacinth South Africa Hartbeespoort , Aquatic weeds Biological control South Africa Hartbeespoort , Megamelus scutellaris , Eutrophication
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/424599 , vital:72167
- Description: Water hyacinth (Pontederia crassipes (C.Mart.) Solms (Pontederiaceae)) is a significant aquatic weed both globally and in South Africa. Despite notable success with biological control of other invasive macrophytes, the plant remains as a problematic weed in many aquatic systems in South Africa, particularly due to the eutrophic status of many of its water systems, as well as the plant’s tolerance to cooler climatic conditions than most of its existing biological control agents. Hartbeespoort Dam, located about 30 kilometres west of Pretoria, South Africa, has been infamously infested with water hyacinth for decades, which impacts the important socioeconomic utility of the dam and functioning of natural ecological processes in the system. The dam has a long history of efforts to control water hyacinth, which include widespread herbicidal spray, mechanical removal and classical biological control programmes since the early 1990s - mostly with limited or short-lived success. However, after the introduction of a new, cold-tolerant biological control agent, Megamelus scutellaris Berg (Hemiptera: Delphacidae) in 2018 with an inundative release strategy, the water hyacinth dropped significantly from a maximum cover of about 45 percent (819 hectares) down to less than two percent (40 hectares) over a three-month period (November 2019 – January 2020). This was significant, as it marked the first successful biological control of water hyacinth in a eutrophic, temperate system in South Africa. However, due to the scale of Hartbeespoort Dam (1820 hectares) and the high spatiotemporal variation of the floating mats across time and space, quantifying and monitoring these rapid changes has proved difficult. In response to this problem, this thesis proposed a remote sensing solution to address the need for accurate, timely and readily accessible monitoring data of the water hyacinth population on the dam. Leveraging the temporally frequent (< 5 days revisit time) Sentinel-2 multispectral satellite data, as well as the powerful cloud-computing resources of Google Earth Engine, this thesis developed and deployed a relatively simple and robust index-based decision tree classification method to demonstrate the value of these technologies as an effective monitoring and analysis tool for monitoring large macrophyte infestations. To this end, several challenges had to be overcome in order to produce easily accessible data that was accurate and reliable. For example, due to the size of the Sentinel-2 Level-1C image dataset from August 2015 to March 2021 (n = 654), an automated process of filtering out clouded images was required. Additionally, the co-presence of algal and cyanobacterial blooms necessitated the development of a novel index, coined the Algae Resistant Macrophyte Index (ARMI), to deal with the challenges of accurate macrophyte detection. The high spatiotemporal variability of the floating mats meant that a typical, location-based confusion matrix as a means of assessing the accuracy of the decision tree classifier required a different approach which compared the total classified areas with higher resolution images. This thesis aims to demonstrate the utility of remote sensing tools to provide effective monitoring information to managers, researchers and other stakeholders. There is scope to expand to more areas in South Africa and beyond and may prove an invaluable tool to augment and support on-going and future macrophyte monitoring programmes. , Thesis (MSc) -- Faculty of Science, Geography, 2023
- Full Text:
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