Urban expansion, mainly occasioned by poorly controlled physical development, continues to pose severe threats to sustainable food production. While studies have concentrated more on food production in the hinterlands of Nigeria, there is a dearth of information on empirical investigations into urban food supply. This study, therefore, examined the effect of poorly controlled physical development on urban food production in Ibadan. An ecological footprint model was used to provide its theoretical anchor, while a longitudinal survey was the research design of choice. Both primary and secondary data were sourced. Geographical and remote sensing methods of analysis were used, with the primary focus being on Ibadan City and the dairy farm that has been converted to non-agricultural uses. This research revealed that Ibadan’s total urban area increased from 70.3584 ha in 1986 to 411.8877 ha in 2019. This expansion was accompanied by the loss of agricultural land, the depletion of water bodies, and agricultural land conversion. Validation of the research findings revealed a relatively high accuracy in terms of the Kappa value of 0.72 and an overall classification accuracy of 79.17% for 1986, of 0.84 and 88.33% for 2000, and of 0.91 and 92.5% for 2019. This studyrecommends that farmers should be trained on soilless farming practices such as aeroponics and hydroponics which both require relatively small portions of land to produce food.
{"title":"The effect of poorly controlled physical development on urban food production in Ibadan, Nigeria","authors":"U. Jimoh, K. Otokiti","doi":"10.4314/sajg.v11i2.6","DOIUrl":"https://doi.org/10.4314/sajg.v11i2.6","url":null,"abstract":"Urban expansion, mainly occasioned by poorly controlled physical development, continues to pose severe threats to sustainable food production. While studies have concentrated more on food production in the hinterlands of Nigeria, there is a dearth of information on empirical investigations into urban food supply. This study, therefore, examined the effect of poorly controlled physical development on urban food production in Ibadan. An ecological footprint model was used to provide its theoretical anchor, while a longitudinal survey was the research design of choice. Both primary and secondary data were sourced. Geographical and remote sensing methods of analysis were used, with the primary focus being on Ibadan City and the dairy farm that has been converted to non-agricultural uses. This research revealed that Ibadan’s total urban area increased from 70.3584 ha in 1986 to 411.8877 ha in 2019. This expansion was accompanied by the loss of agricultural land, the depletion of water bodies, and agricultural land conversion. Validation of the research findings revealed a relatively high accuracy in terms of the Kappa value of 0.72 and an overall classification accuracy of 79.17% for 1986, of 0.84 and 88.33% for 2000, and of 0.91 and 92.5% for 2019. This studyrecommends that farmers should be trained on soilless farming practices such as aeroponics and hydroponics which both require relatively small portions of land to produce food.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44977002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Osman Mohammed Abukari, Akwasi Acheampong, I. Dadzie, S. Osah
In this study, we determined three-dimensional (3D) position coordinates for eight new Continuous Operating Reference Stations (CORS) in Ghana through three different GNSS positioning techniques. The three GNSS positioning techniques whereby the network of CORS was tied to ITRF14 and War Office 1926 datums included:1) Precise Point Positioning (PPP); 2) Precise Differential GNSS (PDGNSS), using reference stations based on ITRF14; and 3) PDGNSS, using reference stations based on War Office. The PPP solutions were computed using the Canadian Spatial Reference System Precise Point Positioning software (CSRS-PPP), available online and as an open source GNSS laboratory tool software (gLAB). The PDGNSS solutions were obtained from OPUS and AUSPOS online services, as well as from self-post-processing using Topcon Tools software v8.2.3. All solutions were computed using 24-hour data for twelve consecutive days in the month of October 2018 (GPS DoY 284 to GPS DoY 295). The quality, reliability, and acceptability of position solutions were measured by computing the average positioning error, the rate of ambiguity resolution and the repeatability ratios of the solutions. The variability of coordinate differences for each pair of different positioning techniques was computed to determine their solution congruences. Ultimately, , the average positioning errors in northing, easting, and height were 0.003m, 0.005m and 0.009m, respectively. The rate of ambiguity resolution was between 75.3% and 90.3%. Repeatability ratios ranged between 1: 68,500,000 and 1: 411,100,000. Finally, the minimum and maximum range of variability in coordinate differences for each pair of positioning techniques was 1mm to 16mm for horizontal positions and 2mm to 137mm for vertical positions.
{"title":"Congruence through repeatability of position solutions by different GNSS survey techniques","authors":"Osman Mohammed Abukari, Akwasi Acheampong, I. Dadzie, S. Osah","doi":"10.4314/sajg.v11i2.8","DOIUrl":"https://doi.org/10.4314/sajg.v11i2.8","url":null,"abstract":"In this study, we determined three-dimensional (3D) position coordinates for eight new Continuous Operating Reference Stations (CORS) in Ghana through three different GNSS positioning techniques. The three GNSS positioning techniques whereby the network of CORS was tied to ITRF14 and War Office 1926 datums included:1) Precise Point Positioning (PPP); 2) Precise Differential GNSS (PDGNSS), using reference stations based on ITRF14; and 3) PDGNSS, using reference stations based on War Office. The PPP solutions were computed using the Canadian Spatial Reference System Precise Point Positioning software (CSRS-PPP), available online and as an open source GNSS laboratory tool software (gLAB). The PDGNSS solutions were obtained from OPUS and AUSPOS online services, as well as from self-post-processing using Topcon Tools software v8.2.3. All solutions were computed using 24-hour data for twelve consecutive days in the month of October 2018 (GPS DoY 284 to GPS DoY 295). The quality, reliability, and acceptability of position solutions were measured by computing the average positioning error, the rate of ambiguity resolution and the repeatability ratios of the solutions. The variability of coordinate differences for each pair of different positioning techniques was computed to determine their solution congruences. Ultimately, , the average positioning errors in northing, easting, and height were 0.003m, 0.005m and 0.009m, respectively. The rate of ambiguity resolution was between 75.3% and 90.3%. Repeatability ratios ranged between 1: 68,500,000 and 1: 411,100,000. Finally, the minimum and maximum range of variability in coordinate differences for each pair of positioning techniques was 1mm to 16mm for horizontal positions and 2mm to 137mm for vertical positions.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46240647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Urbanisation has been identified as a major threat to the environment as it increases demand for urban spaces and transforms natural landscapes to impervious surfaces, leading to the Urban Heat Island (UHI) phenomenon. Natural landscapes such as vegetation and water bodies act as thermal sinks that absorb heat while impervious surfaces such as buildings and concrete pavements act as thermal sources that retain and emit heat. The thermal emission results in several negative effects such as temperature inversion, compromised human health, pollution, species loss, high energy consumption and climate change at a local, regional and global scales. Whereas studies on UHI are abound, there is paucity in literature on the influence of seasonal urban Land Use Land Cover (LULC) transformation on urban thermal characteristics. Specifically, the proportional seasonal variability and contribution of individual LULCs to urban heat is often poorly understood. Using the freely available Landsat 8 optical and thermal bands, this study examined the seasonal characteristics of the UHI phenomenon in relation to LULCs in the Pietermaritzburg city, South Africa. Results in this study revealed that UHIs exist in both winter and summer, but with more intensity in summer. The study also established that LULCs varied with seasons. Bare surfaces and dense vegetation had the most thermal influence during winter while dense vegetation and low density buildings had the most thermal influence during summer. These findings provide a better understanding of thermal distribution based on LULC seasonality changes, valuable for sustainable urban planning and climate change mitigation.
{"title":"The influence of seasonal land-use-land-cover transformation on thermal characteristics within the city of Pietermaritzburg","authors":"J. Odindi","doi":"10.4314/sajg.v9i2.23","DOIUrl":"https://doi.org/10.4314/sajg.v9i2.23","url":null,"abstract":"Urbanisation has been identified as a major threat to the environment as it increases demand for urban spaces and transforms natural landscapes to impervious surfaces, leading to the Urban Heat Island (UHI) phenomenon. Natural landscapes such as vegetation and water bodies act as thermal sinks that absorb heat while impervious surfaces such as buildings and concrete pavements act as thermal sources that retain and emit heat. The thermal emission results in several negative effects such as temperature inversion, compromised human health, pollution, species loss, high energy consumption and climate change at a local, regional and global scales. Whereas studies on UHI are abound, there is paucity in literature on the influence of seasonal urban Land Use Land Cover (LULC) transformation on urban thermal characteristics. Specifically, the proportional seasonal variability and contribution of individual LULCs to urban heat is often poorly understood. Using the freely available Landsat 8 optical and thermal bands, this study examined the seasonal characteristics of the UHI phenomenon in relation to LULCs in the Pietermaritzburg city, South Africa. Results in this study revealed that UHIs exist in both winter and summer, but with more intensity in summer. The study also established that LULCs varied with seasons. Bare surfaces and dense vegetation had the most thermal influence during winter while dense vegetation and low density buildings had the most thermal influence during summer. These findings provide a better understanding of thermal distribution based on LULC seasonality changes, valuable for sustainable urban planning and climate change mitigation.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":"1 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2020-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42987575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Humankind often needs to accurately model, identify and spatially quantify aboveground phenomena on the Earth’s surface for informed decision-making. Height data derived from digital elevation models (DEMs) is often used to achieve this. This study conducted a deterministic assessment of three normalised digital surface models (nDSMs) of different spatial resolutions, namely 2m, 4m and 12m, derived from VHR digital stereo aerial photography, tri-stereo Pléiades imagery and Tandem-X InSAR data, respectively. Covering a predominantly built-up area within a city landscape, the nDSMs were vertically and volumetrically compared to assess their quality and fit-for-use. In each case a consistent systematic evaluation was accomplished against a lidar derived reference surface at matching spatial resolutions (co-registered) using a semi-automated GIS routine. The relative height and volumetric errors were statistically analysed and described, including those computed individually over nine urban land cover/land use (LCLU) classes and several selected large buildings. Higher vertical accuracies were reported across single storey structures and areas with no to little or short vegetation, as apposed to substantially lower accuracies obtained over multi-levelled buildings and tall (dense) woody vegetation. Here significant underestimations of volumes exacerbated by lower spatial resolutions were also observed across each nDSM. Conversely, notable volume overestimations were found over predominantly grass-covered areas in especially the finer-scaled nDSMs. VHR elevation data is recommended to model and quantify aboveground elements spatially in 3D (e.g. buildings, earthworks and woody vegetation) in urban landscapes, but a sensitivity test beforehand remains critical to ensure more reliable outcomes for users and stakeholders alike.
{"title":"3D Evaluation of fine-scale normalised DSMs in urban settings","authors":"A. Breytenbach","doi":"10.4314/sajg.v9i2.26","DOIUrl":"https://doi.org/10.4314/sajg.v9i2.26","url":null,"abstract":"Humankind often needs to accurately model, identify and spatially quantify aboveground phenomena on the Earth’s surface for informed decision-making. Height data derived from digital elevation models (DEMs) is often used to achieve this. This study conducted a deterministic assessment of three normalised digital surface models (nDSMs) of different spatial resolutions, namely 2m, 4m and 12m, derived from VHR digital stereo aerial photography, tri-stereo Pléiades imagery and Tandem-X InSAR data, respectively. Covering a predominantly built-up area within a city landscape, the nDSMs were vertically and volumetrically compared to assess their quality and fit-for-use. In each case a consistent systematic evaluation was accomplished against a lidar derived reference surface at matching spatial resolutions (co-registered) using a semi-automated GIS routine. The relative height and volumetric errors were statistically analysed and described, including those computed individually over nine urban land cover/land use (LCLU) classes and several selected large buildings. Higher vertical accuracies were reported across single storey structures and areas with no to little or short vegetation, as apposed to substantially lower accuracies obtained over multi-levelled buildings and tall (dense) woody vegetation. Here significant underestimations of volumes exacerbated by lower spatial resolutions were also observed across each nDSM. Conversely, notable volume overestimations were found over predominantly grass-covered areas in especially the finer-scaled nDSMs. VHR elevation data is recommended to model and quantify aboveground elements spatially in 3D (e.g. buildings, earthworks and woody vegetation) in urban landscapes, but a sensitivity test beforehand remains critical to ensure more reliable outcomes for users and stakeholders alike.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2020-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46461494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A new height datum for Uganda is computed using the corrective surface principle. It is based on a combination of the Uganda Gravimetric Quasigeoid model (UGQ) 2014 and GNSS/levelling. UGQ2014 was derived from the Uganda Gravimetric Geoid model (UGG) 2014, which was computed from sparse terrestrial gravity data from the International Gravimetric Bureau, the 3 arc second Shuttle Radar Topography Mission digital elevation model and the GOCE – only global geopotential model GO_CONS_GCF_2_TIM_R5. The corrective surface was constructed based on 21 discrete GNSS/levelling points and then evaluated with 4 independent points. Three interpolation techniques were tested for the creation of the corrective surface with the Kriging method giving the lowest standard deviation and noise level suggesting that it is the best method for interpolation. In absolute terms, the Root Mean Square of the fit between the known and computed normal-orthometric heights based on the new height datum is 11cm, which is about 5cm (31%) better than using UGQ2014 alone. For relative heights an average precision of 29 ppm is computed for all baselines tested. Both the absolute and relative tests show that the new height datum satisfies the precision and accuracy requirements of third order precise levelling. Therefore, UGQ2014C represents a significant step towards the determination of a precise new height datum for Uganda.
{"title":"Towards a new height datum for Uganda","authors":"R. Ssengendo, A. Gidudu","doi":"10.4314/sajg.v9i2.8","DOIUrl":"https://doi.org/10.4314/sajg.v9i2.8","url":null,"abstract":"A new height datum for Uganda is computed using the corrective surface principle. It is based on a combination of the Uganda Gravimetric Quasigeoid model (UGQ) 2014 and GNSS/levelling. UGQ2014 was derived from the Uganda Gravimetric Geoid model (UGG) 2014, which was computed from sparse terrestrial gravity data from the International Gravimetric Bureau, the 3 arc second Shuttle Radar Topography Mission digital elevation model and the GOCE – only global geopotential model GO_CONS_GCF_2_TIM_R5. The corrective surface was constructed based on 21 discrete GNSS/levelling points and then evaluated with 4 independent points. Three interpolation techniques were tested for the creation of the corrective surface with the Kriging method giving the lowest standard deviation and noise level suggesting that it is the best method for interpolation. In absolute terms, the Root Mean Square of the fit between the known and computed normal-orthometric heights based on the new height datum is 11cm, which is about 5cm (31%) better than using UGQ2014 alone. For relative heights an average precision of 29 ppm is computed for all baselines tested. Both the absolute and relative tests show that the new height datum satisfies the precision and accuracy requirements of third order precise levelling. Therefore, UGQ2014C represents a significant step towards the determination of a precise new height datum for Uganda.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2020-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48960359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Coping with rapid urbanisation and the impacts of climate change requires effective land management. Quality land information is essential for this. A land information infrastructure is a collaborative and coordinated initiative aimed at providing land information from different organisations, such as municipalities, government departments and private companies, to diverse user communities. A land information infrastructure is complex, spanning information streams through many organisations and technical systems, and presenting challenges for managing and monitoring the production of land information. In the manufacturing field, a supply chain refers to the stream of activities from the initial source to the delivery of end products to customers, and supply chain management is directed at optimising the creation of the products of such a chain. The Supply Chain Operations Reference (SCOR) model is widely used for analysing supply chain processes in order to quantify and improve product and service delivery, and it has also been applied to geographical information supply chains. In this study, the SCOR model is applied to the supply chain processes in a South African case study of a land information infrastructure focusing on the production of cadastral information products. The supply chain comprises a land developer, a land surveying firm, the Surveyor General’s and Deeds Offices, a geospatial data vendor and the end customer. This supply chain is mapped and analysed using supply chain mapping and the SCOR model, and based on this, the complexity of the land information infrastructure is revealed. The study shows that supply chain management and the SCOR model can be used to analyse, monitor and manage the production processes of land information within a land information infrastructure.
{"title":"Towards monitoring and managing the production of cadastral information in land information infrastructures using supply chain mapping and the Supply Chain Operations Reference (SCOR) model","authors":"Edward Kurwakumire, S. Coetzee, P. Schmitz","doi":"10.4314/SAJG.V9I2.12","DOIUrl":"https://doi.org/10.4314/SAJG.V9I2.12","url":null,"abstract":"Coping with rapid urbanisation and the impacts of climate change requires effective land management. Quality land information is essential for this. A land information infrastructure is a collaborative and coordinated initiative aimed at providing land information from different organisations, such as municipalities, government departments and private companies, to diverse user communities. A land information infrastructure is complex, spanning information streams through many organisations and technical systems, and presenting challenges for managing and monitoring the production of land information. In the manufacturing field, a supply chain refers to the stream of activities from the initial source to the delivery of end products to customers, and supply chain management is directed at optimising the creation of the products of such a chain. The Supply Chain Operations Reference (SCOR) model is widely used for analysing supply chain processes in order to quantify and improve product and service delivery, and it has also been applied to geographical information supply chains. In this study, the SCOR model is applied to the supply chain processes in a South African case study of a land information infrastructure focusing on the production of cadastral information products. The supply chain comprises a land developer, a land surveying firm, the Surveyor General’s and Deeds Offices, a geospatial data vendor and the end customer. This supply chain is mapped and analysed using supply chain mapping and the SCOR model, and based on this, the complexity of the land information infrastructure is revealed. The study shows that supply chain management and the SCOR model can be used to analyse, monitor and manage the production processes of land information within a land information infrastructure.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2020-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46301505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Africa is experiencing rapid urbanisation, which calls for well-considered urban and regional planning efforts to cater for the current and future populations. However, as it is typically the case in the global South, African countries are characterised by a lack of quality spatial economic data required for planning and evaluation processes. Using the study area of Harare, Zimbabwe, the paper demonstrates ways that, amidst the paucity of data, geographic information system can be used to measure urban development’s congruence with spatial plans. To prepare for the analysis, the base map preparation process entailed a laborious digitisation of hardcopy material obtained from the authorities. This was followed by land-use surveys and land-use change investigations whose data were analysed in ESRI’s ArcGIS 9.3. The analysis compared urban development patterns in 2014 with the proposals of two applicable spatial plans, which were approved in 1990 and 2000 respectively. The investigations uncovered that urban development patterns and trends did not correspond with the aspirations of the plans. The paper proposes that follow-up research be conducted on factors that influence the misalignment between plans and development, particularly in African countries that are characterised by rapid urbanisation.
{"title":"Using geographic information system to analyse the divergence of urban development from spatial plans in Harare, Zimbabwe","authors":"D. Machakaire, N. Tapela, Masilonyane Mokhele","doi":"10.4314/sajg.v9i2.15","DOIUrl":"https://doi.org/10.4314/sajg.v9i2.15","url":null,"abstract":"Africa is experiencing rapid urbanisation, which calls for well-considered urban and regional planning efforts to cater for the current and future populations. However, as it is typically the case in the global South, African countries are characterised by a lack of quality spatial economic data required for planning and evaluation processes. Using the study area of Harare, Zimbabwe, the paper demonstrates ways that, amidst the paucity of data, geographic information system can be used to measure urban development’s congruence with spatial plans. To prepare for the analysis, the base map preparation process entailed a laborious digitisation of hardcopy material obtained from the authorities. This was followed by land-use surveys and land-use change investigations whose data were analysed in ESRI’s ArcGIS 9.3. The analysis compared urban development patterns in 2014 with the proposals of two applicable spatial plans, which were approved in 1990 and 2000 respectively. The investigations uncovered that urban development patterns and trends did not correspond with the aspirations of the plans. The paper proposes that follow-up research be conducted on factors that influence the misalignment between plans and development, particularly in African countries that are characterised by rapid urbanisation.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2020-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46789442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Peerbhay, Roxanne. Munsamy, M. Gebreslasie, R. Ismail
Accurate multi-source forest inventory attributes are necessary for estimating productivity and timber stock in commercial forest plantations. This study aims to uncover the effects of terrain variation on the growth of even aged Eucalyptus forest species using Light Detection and Ranging (LiDAR) topographical variables. Using 32 generated variables at 5 different spatial resolutions (1m, 3m, 5m, 7m, 9m), the random forest (RF) regression successfully revealed variations for structural attributes such as volume (Vol/ha), dominant tree height (HtD), mean tree height (Htm), and diameter breast heights (DBH). Results indicate that smaller spatial resolutions performed better for younger stands while larger resolutions produced the best results for mature stands. Using the multi-resolution approach results improved with variable selection. Incoming solar radiation and slope variables were among the most important terrain variables for modelling forest structural variability. The findings from this study demonstrates the value of stratifying forest productivity across the commercial forest landscapes of South Africa.
{"title":"Modelling the effect of terrain variability in even-aged Eucalyptus species using LiDAR-derived DTM variables","authors":"K. Peerbhay, Roxanne. Munsamy, M. Gebreslasie, R. Ismail","doi":"10.4314/sajg.v9i2.9","DOIUrl":"https://doi.org/10.4314/sajg.v9i2.9","url":null,"abstract":"Accurate multi-source forest inventory attributes are necessary for estimating productivity and timber stock in commercial forest plantations. This study aims to uncover the effects of terrain variation on the growth of even aged Eucalyptus forest species using Light Detection and Ranging (LiDAR) topographical variables. Using 32 generated variables at 5 different spatial resolutions (1m, 3m, 5m, 7m, 9m), the random forest (RF) regression successfully revealed variations for structural attributes such as volume (Vol/ha), dominant tree height (HtD), mean tree height (Htm), and diameter breast heights (DBH). Results indicate that smaller spatial resolutions performed better for younger stands while larger resolutions produced the best results for mature stands. Using the multi-resolution approach results improved with variable selection. Incoming solar radiation and slope variables were among the most important terrain variables for modelling forest structural variability. The findings from this study demonstrates the value of stratifying forest productivity across the commercial forest landscapes of South Africa.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2020-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43264011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
O. Popoola, Peters Durojaye, T. Bayode, A. Popoola, J. Olanibi, Olamide Aladetuyi
The threat of the increasing global temperature is now of global concern than ever before. This prompted the authors to gain insights on the Urban Heat Island (UHI) phenomenon in a medium-sized city of Akure, Nigeria. A random sampling of three hundred and twenty-five (325) structured questionnaires was administered and analyzed with the aid of the Statistical Package for Social Sciences (SPSS). Landsat satellite imagery for the years 2000; 2007; 2013 and 2018 were acquired and used for the computation of land use-land cover (LULC) and the Land Surface Temperature (LST) of the study area using ArcGIS 10.5. Between the years 2000 and 2018, built-up area increased by 8.78% at the expense of the non-built up land use. The residents were aware of UHI and climate change but characterized by superficiality. The study recommends a community awareness program on the menace of climate change and the integration of climate education into the curriculum of schools and other institutions of higher learning.
{"title":"Spatio-temporal variance and urban heat island in Akure, Nigeria: A time-spaced analysis Using GIS Techniqu","authors":"O. Popoola, Peters Durojaye, T. Bayode, A. Popoola, J. Olanibi, Olamide Aladetuyi","doi":"10.4314/sajg.v9i2.24","DOIUrl":"https://doi.org/10.4314/sajg.v9i2.24","url":null,"abstract":"The threat of the increasing global temperature is now of global concern than ever before. This prompted the authors to gain insights on the Urban Heat Island (UHI) phenomenon in a medium-sized city of Akure, Nigeria. A random sampling of three hundred and twenty-five (325) structured questionnaires was administered and analyzed with the aid of the Statistical Package for Social Sciences (SPSS). Landsat satellite imagery for the years 2000; 2007; 2013 and 2018 were acquired and used for the computation of land use-land cover (LULC) and the Land Surface Temperature (LST) of the study area using ArcGIS 10.5. Between the years 2000 and 2018, built-up area increased by 8.78% at the expense of the non-built up land use. The residents were aware of UHI and climate change but characterized by superficiality. The study recommends a community awareness program on the menace of climate change and the integration of climate education into the curriculum of schools and other institutions of higher learning.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2020-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43405224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Urbanisation is accelerating urban land use dynamics and this has a significant impact on land surface temperature (LST). Impervious surfaces and increase in air pollution has led to the increase in land surface temperature. This study reports on the use of geospatial technologies to monitor and quantify changes in LST using remotely sensed data in the City of Tshwane. Land surface temperature was retrieved using the winter and summer Landsat datasets for 1997 and 2015 and the MODIS data from 2000 to 2015. Land surface temperature was extracted using emissivity and satellite temperature as input parameters. The spatial and temporal variations in the LST were retrieved to show the effects of land cover change on LST. Change in LST was also analysed on different land cover types using transects across the study area. The study revealed an increase in land surface temperature between the years. It also showed that impervious surfaces had a higher LST compared to the non-impervious surfaces. The results revealed variations in LST between non-cropped and cropped agricultural areas, where the former had higher LST than the latter. Temporal trends revealed a notable increase in LST in the urban areas and there were some seasonal variations in LST with high LST values in summer and low values in winter. Cross-section analysis along transects revealed spatio-temporal thermal variations across different land cover types.
{"title":"Spatio-temporal variations of land surface temperature using Landsat and MODIS: case study of the City of Tshwane, South Africa","authors":"J. Magidi, F. Ahmed","doi":"10.4314/sajg.v9i2.25","DOIUrl":"https://doi.org/10.4314/sajg.v9i2.25","url":null,"abstract":"Urbanisation is accelerating urban land use dynamics and this has a significant impact on land surface temperature (LST). Impervious surfaces and increase in air pollution has led to the increase in land surface temperature. This study reports on the use of geospatial technologies to monitor and quantify changes in LST using remotely sensed data in the City of Tshwane. Land surface temperature was retrieved using the winter and summer Landsat datasets for 1997 and 2015 and the MODIS data from 2000 to 2015. Land surface temperature was extracted using emissivity and satellite temperature as input parameters. The spatial and temporal variations in the LST were retrieved to show the effects of land cover change on LST. Change in LST was also analysed on different land cover types using transects across the study area. The study revealed an increase in land surface temperature between the years. It also showed that impervious surfaces had a higher LST compared to the non-impervious surfaces. The results revealed variations in LST between non-cropped and cropped agricultural areas, where the former had higher LST than the latter. Temporal trends revealed a notable increase in LST in the urban areas and there were some seasonal variations in LST with high LST values in summer and low values in winter. Cross-section analysis along transects revealed spatio-temporal thermal variations across different land cover types.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2020-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43822635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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