With South Africa having a history of youth activism and a predominantly youthful population, this paper investigates why the youth (18-34 years) do not participate in local development planning in Gauteng Province. The main source of data used in this study was the 2015/2016 QoL data of the Gauteng City-Region Observatory (GCRO). Results across Gauteng show that the majority of the youth do not participate in ward committee (WC), community development forum (CDF), and integrated development planning (IDP) meetings. The geographically weighted regression (GWR) approach proved important in allowing us to investigate the spatial variation in non-attendance at WC meetings and the heterogeneity role of the predictor variables over the study area. The GWR results show that the percentage of employed youth, average household income, the percentage of youth who have never interacted with government, the percentage of youth dissatisfied with the local councillor, and the average educational level of the youth emerged as barriers to participation in WC meetings. While results for non-participation in CDF meetings had no significant localised GWR results, compared to those for WC meetings, common barriers (as in the ordinary least squares (OLS) model) to participation in CDF meetings were, for instance, the youth’s educational level and the lack of interaction with local government. Even according to the OLS model, the results of IDP meetings were not robust, and could not therefore be interpreted. Overall, however, these results are useful in spurring spatially-targeted – either region-wide or localised – policies.
{"title":"A Geographically Weighted Regression Analysis of Barriers to Youth’s Participation in Local Development Planning in Gauteng Province, South Africa","authors":"Koech Cheruiyot","doi":"10.4314/sajg.v12i.2.1","DOIUrl":"https://doi.org/10.4314/sajg.v12i.2.1","url":null,"abstract":"With South Africa having a history of youth activism and a predominantly youthful population, this paper investigates why the youth (18-34 years) do not participate in local development planning in Gauteng Province. The main source of data used in this study was the 2015/2016 QoL data of the Gauteng City-Region Observatory (GCRO). Results across Gauteng show that the majority of the youth do not participate in ward committee (WC), community development forum (CDF), and integrated development planning (IDP) meetings. The geographically weighted regression (GWR) approach proved important in allowing us to investigate the spatial variation in non-attendance at WC meetings and the heterogeneity role of the predictor variables over the study area. The GWR results show that the percentage of employed youth, average household income, the percentage of youth who have never interacted with government, the percentage of youth dissatisfied with the local councillor, and the average educational level of the youth emerged as barriers to participation in WC meetings. While results for non-participation in CDF meetings had no significant localised GWR results, compared to those for WC meetings, common barriers (as in the ordinary least squares (OLS) model) to participation in CDF meetings were, for instance, the youth’s educational level and the lack of interaction with local government. Even according to the OLS model, the results of IDP meetings were not robust, and could not therefore be interpreted. Overall, however, these results are useful in spurring spatially-targeted – either region-wide or localised – policies.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136000224","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 Afrifa Acheampong, Samuel Osah, John Ayer
In this study, the course towards determining the homogeneous three-dimensional (3D) coordinates of the newly established active Continuously Operating Reference Station (CORS), based on ITRF2014 in Ghana, is revealed. The aim is to address coordinate inconsistencies and inhomogeneity in the published positions of the new active CORS in Ghana. In order to attain homogeneity, the coordinates of two primary control points, GCS 305 and GCS 306, were obtained using AUSPOS online services via email. These were subsequently used as reference stations to compute the position of the LISAG_KUMASI CORS. Adjustments to the position coordinates were performed using Topcon Tools v8.2.3 software at a 1mm standard deviation. The adjusted coordinates of LISAG_KUMASI were used as the reference points to compute the positions of the LiSAGNet CORS in differential mode by using 24 hour data for 11 consecutive days. The GPS data covered DoY 284 to DoY 295 in 2021. The final positions of the CORS, computed by this approach, indicate some differences from the officially published coordinates of the same CORS, confirming the suspicion of inhomogeneity in the source coordinates used in determining the coordinates of the local CORS. Furthermore, a test network, consisting of five COR stations, was designed and used to address the coordinate inconsistencies in the officially published coordinates. Using the officially published coordinates as reference inputs, the ROVER I station was fixed by three different CORSs, thus resulting in average coordinate variabilities of 2.78m and 0.80m in the northing (N) and easting (E) directions, respectively. Through substitution, the coordinates computed in this study as reference inputs, namely, the ROVER I station, were fixed by the same three CORSs, thus resulting in a coordinate variability of 0.002m and 0.006m in the northing (N) and easting (E) directions, respectively. The analysis revealed inconsistencies and inhomogeneity in terms of the officially published coordinates. It is, therefore, recommended that the officially published coordinates of the CORS be replaced by the adjusted homogeneous and consistent values determined through the approach adopted in this study.
{"title":"Homogenizing coordinates through the use of the active CORS in Ghana","authors":"Osman Mohammed Abukari, Akwasi Afrifa Acheampong, Samuel Osah, John Ayer","doi":"10.4314/sajg.v12i.2.2","DOIUrl":"https://doi.org/10.4314/sajg.v12i.2.2","url":null,"abstract":"In this study, the course towards determining the homogeneous three-dimensional (3D) coordinates of the newly established active Continuously Operating Reference Station (CORS), based on ITRF2014 in Ghana, is revealed. The aim is to address coordinate inconsistencies and inhomogeneity in the published positions of the new active CORS in Ghana. In order to attain homogeneity, the coordinates of two primary control points, GCS 305 and GCS 306, were obtained using AUSPOS online services via email. These were subsequently used as reference stations to compute the position of the LISAG_KUMASI CORS. Adjustments to the position coordinates were performed using Topcon Tools v8.2.3 software at a 1mm standard deviation. The adjusted coordinates of LISAG_KUMASI were used as the reference points to compute the positions of the LiSAGNet CORS in differential mode by using 24 hour data for 11 consecutive days. The GPS data covered DoY 284 to DoY 295 in 2021. The final positions of the CORS, computed by this approach, indicate some differences from the officially published coordinates of the same CORS, confirming the suspicion of inhomogeneity in the source coordinates used in determining the coordinates of the local CORS. Furthermore, a test network, consisting of five COR stations, was designed and used to address the coordinate inconsistencies in the officially published coordinates. Using the officially published coordinates as reference inputs, the ROVER I station was fixed by three different CORSs, thus resulting in average coordinate variabilities of 2.78m and 0.80m in the northing (N) and easting (E) directions, respectively. Through substitution, the coordinates computed in this study as reference inputs, namely, the ROVER I station, were fixed by the same three CORSs, thus resulting in a coordinate variability of 0.002m and 0.006m in the northing (N) and easting (E) directions, respectively. The analysis revealed inconsistencies and inhomogeneity in terms of the officially published coordinates. It is, therefore, recommended that the officially published coordinates of the CORS be replaced by the adjusted homogeneous and consistent values determined through the approach adopted in this study.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136000225","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}
The Government of Kenya, under its Vision 2030 Agenda, highlighted the need for decent and high-quality livelihoods for its citizens, by ensuring that sustainable provision be made for the necessary infrastructure required to meet their socio-economic needs. Thus, the government invested in an Electronic Development Application Management System (e-DAMS). It allows the Built Environment professionals to register and apply for planning certificates, construction permits, building inspection permits, and occupation permits. However, this system can only regulate and monitor the existing infrastructure projects in the database and has to exclude unauthorised developments. This GIS approach, which was built upon the recording and tracking of several types of electricity applications made by customers, could also be used to monitor new and existing infrastructure developments. Data were sourced from multiple government agencies in Mombasa County. A comparative analysis approach was subsequently employed to investigate the relationship between the trends in electricity supply applications, the respective types of urban land-use development, and the permits issued in approving the respective types of construction in Mombasa County. A direct relationship was found between the permits used to approve the respective types of construction and the Urban Development Master Plan. Also, a direct relationship was found between the applications for the respective types of electricity that were being made and the issuing of construction approval permits. The conclusion was reached that the applications for the prevailing types of electricity supply could be used as a proxy for identifying and assessing infrastructural development in Mombasa County. This GIS approach could provide the authorities with insights into unauthorised construction initiatives.
{"title":"Application of GIS to monitor infrastructural development in Mombasa County, Kenya","authors":"Margaret N. Munywoki, Kaveer Singh","doi":"10.4314/sajg.v12i.2.3","DOIUrl":"https://doi.org/10.4314/sajg.v12i.2.3","url":null,"abstract":"The Government of Kenya, under its Vision 2030 Agenda, highlighted the need for decent and high-quality livelihoods for its citizens, by ensuring that sustainable provision be made for the necessary infrastructure required to meet their socio-economic needs. Thus, the government invested in an Electronic Development Application Management System (e-DAMS). It allows the Built Environment professionals to register and apply for planning certificates, construction permits, building inspection permits, and occupation permits. However, this system can only regulate and monitor the existing infrastructure projects in the database and has to exclude unauthorised developments. This GIS approach, which was built upon the recording and tracking of several types of electricity applications made by customers, could also be used to monitor new and existing infrastructure developments. Data were sourced from multiple government agencies in Mombasa County. A comparative analysis approach was subsequently employed to investigate the relationship between the trends in electricity supply applications, the respective types of urban land-use development, and the permits issued in approving the respective types of construction in Mombasa County. A direct relationship was found between the permits used to approve the respective types of construction and the Urban Development Master Plan. Also, a direct relationship was found between the applications for the respective types of electricity that were being made and the issuing of construction approval permits. The conclusion was reached that the applications for the prevailing types of electricity supply could be used as a proxy for identifying and assessing infrastructural development in Mombasa County. This GIS approach could provide the authorities with insights into unauthorised construction initiatives.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135998924","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}
Informal settlements are a major influence in the urban growth of developing countries such as South Africa. There are also associated with negative socio-economic factors such as unemployment and are lacking in terms of secure land tenure arrangements. This research focuses on developing a geospatial understanding of the internal dynamics of informal settlement development within the City of Cape Town. To investigate how informal settlements are established and developed in a local context, the informal settlements of Imizamo Yethu, Langa, and Siqalo were monitored for the period 2011-2019 using image classification to determine the development, complexity, and compactness of the dwellings. The overall accuracy of the classified maps thus developed ranged between 88 and 96%. Change detection analysis was subsequently used to identify the geospatial trends for each informal settlement across all three. The combination of linear regression and ordinary least squares analysis determined that the major spatial trend driving growth was densification, which was correlated with the availability of open space, unemployment, poverty, and GDP. Furthermore, densification was identified along the major formal external transport routes and informal internal transport networks. It was found that individual settlements present unique internal geospatial development dynamics in the macroeconomic context of Cape Town, but that these tend to differ in the microeconomic context of the city. Among the explanatory variables for this situation were sloped lands, employment opportunities, and neighbouring areas where the incomes of the residents were higher. Across all the informal settlements, open space proved to be the most significant factor, while GDP played the most influential role in explaining shack compactness over time. This study could be used to contribute to policy and decision-making in the formalisation process in these informal settlements.
{"title":"Geospatial Analysis of Informal Settlement Development in Cape Town","authors":"T Fisher, K Singh","doi":"10.4314/sajg.v12i.2.7","DOIUrl":"https://doi.org/10.4314/sajg.v12i.2.7","url":null,"abstract":"Informal settlements are a major influence in the urban growth of developing countries such as South Africa. There are also associated with negative socio-economic factors such as unemployment and are lacking in terms of secure land tenure arrangements. This research focuses on developing a geospatial understanding of the internal dynamics of informal settlement development within the City of Cape Town. To investigate how informal settlements are established and developed in a local context, the informal settlements of Imizamo Yethu, Langa, and Siqalo were monitored for the period 2011-2019 using image classification to determine the development, complexity, and compactness of the dwellings. The overall accuracy of the classified maps thus developed ranged between 88 and 96%. Change detection analysis was subsequently used to identify the geospatial trends for each informal settlement across all three. The combination of linear regression and ordinary least squares analysis determined that the major spatial trend driving growth was densification, which was correlated with the availability of open space, unemployment, poverty, and GDP. Furthermore, densification was identified along the major formal external transport routes and informal internal transport networks. It was found that individual settlements present unique internal geospatial development dynamics in the macroeconomic context of Cape Town, but that these tend to differ in the microeconomic context of the city. Among the explanatory variables for this situation were sloped lands, employment opportunities, and neighbouring areas where the incomes of the residents were higher. Across all the informal settlements, open space proved to be the most significant factor, while GDP played the most influential role in explaining shack compactness over time. This study could be used to contribute to policy and decision-making in the formalisation process in these informal settlements.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136000226","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}
M. Nickola, H. Krásná, L. Combrinck, Jan Boehm, A. de Witt
In the Very Long Baseline Interferometry (VLBI) space geodetic technique, various station-specific error sources corrupt the observable VLBI delay. An antenna axis offset (AO) model is applied in the VLBI data analysis for antennas with non-intersecting rotational axes, such as the 26-m and 15-m antennas for the Hartebeesthoek Radio Astronomy Observatory (HartRAO). The a priori AO values recommended by the International VLBI Service for Geodesy and Astrometry (IVS) for use in geodetic VLBI data analysis are taken, where possible, from values measured in ground surveys. The a priori AO values used for the HartRAO antennas in geodetic VLBI analysis have been identified as possible sources of error. The a priori AO value of 6695.3 mm for the 26-m antenna originates from a 2003 co-locational ground survey, conducted before a major bearing repair in 2008, which could have changed the AO. The a priori AO value of 1495.0 mm for the 15-m antenna was determined in 2007 in only a preliminary GPS survey. In this study, the respective AO values of the HartRAO 26-m and 15-m antennas were estimated from a VLBI analysis using the Vienna VLBI and Satellite Software (VieVS) and compared with measurements from co-locational ground surveys. It was found that the VLBI estimated values do not agree within the formal margins of error with the ground survey values, in that they differ by up to eight millimetres (8 mm) for the 26-m antenna and up to five millimetres (5 mm) for the 15-m antenna. As the ground survey values are considered to be more accurate than the VLBI estimated values, a further investigation of the site-specific error sources that may be contaminating the accuracy of VLBI results is required.
{"title":"Hartebeesthoek Radio Astronomy Observatory (HartRAO) antenna axis offset determined by geodetic VLBI analysis and ground survey","authors":"M. Nickola, H. Krásná, L. Combrinck, Jan Boehm, A. de Witt","doi":"10.4314/sajg.v12i1.7","DOIUrl":"https://doi.org/10.4314/sajg.v12i1.7","url":null,"abstract":"In the Very Long Baseline Interferometry (VLBI) space geodetic technique, various station-specific error sources corrupt the observable VLBI delay. An antenna axis offset (AO) model is applied in the VLBI data analysis for antennas with non-intersecting rotational axes, such as the 26-m and 15-m antennas for the Hartebeesthoek Radio Astronomy Observatory (HartRAO). The a priori AO values recommended by the International VLBI Service for Geodesy and Astrometry (IVS) for use in geodetic VLBI data analysis are taken, where possible, from values measured in ground surveys. The a priori AO values used for the HartRAO antennas in geodetic VLBI analysis have been identified as possible sources of error. The a priori AO value of 6695.3 mm for the 26-m antenna originates from a 2003 co-locational ground survey, conducted before a major bearing repair in 2008, which could have changed the AO. The a priori AO value of 1495.0 mm for the 15-m antenna was determined in 2007 in only a preliminary GPS survey. In this study, the respective AO values of the HartRAO 26-m and 15-m antennas were estimated from a VLBI analysis using the Vienna VLBI and Satellite Software (VieVS) and compared with measurements from co-locational ground surveys. It was found that the VLBI estimated values do not agree within the formal margins of error with the ground survey values, in that they differ by up to eight millimetres (8 mm) for the 26-m antenna and up to five millimetres (5 mm) for the 15-m antenna. As the ground survey values are considered to be more accurate than the VLBI estimated values, a further investigation of the site-specific error sources that may be contaminating the accuracy of VLBI results is required.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48884779","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}
Mooketsi Segobye, Loago K. Motlogelwa, B. Nkwae, Y. Ouma, Lopang Maphale, Bagadzi M. Manisa
Explorations of the differences between Gravity Recovery and Climate Experiment (GRACE) solutions in local regions and basins are fundamental in determining their suitability and applicability in these environments. Because of the different mathematical inversions used by the respective processing centers, individual solutions exhibit discrepancies in terms of mass increase or loss, which makes it difficult for users to select the best model for studying terrestrial water storage anomalies (TWSAs). This study compares TWSA trends, as derived from different GRACE solutions over the arid and semi-arid Botswana (2002-2019), where both storage and flux from CSR, JPL, GFZ, TUGRAZ, AIUB, and COST-G[1] were compared. The results show that the six solutions are fairly correlated with the least correlation of R=0.829 between JPL and AIUB, and a maximum of R=0.921 between CSR and TUGRAZ at a 95% confidence level. The TWSA analyses for 2002-2019 indicate that TWS is increasing in Botswana, with the least linear trend of +0.11cm/yr detected from the TUGRAZ inversion model, and the highest linear trend at +0.43cm/year from the COST-G model. On comparing TWS with rainfall, all the solutions presented the same spatio-temporal trends as the rainfall patterns, indicating that the GRACE solutions exhibit the same responses with respect to the received rainfall. Over the 18 years investigated, the long-term rainfall trend was found to decrease, which was only detected by the TUGRAZ model in terms of the recorded equivalent water height (EWH) of -0.008cm/yr from the monthly trend observations. Overall, the AIUB inversion solution gave a better result as its signal was found to be the same as the rainfall signal. [1] CSR = Center for Space Research; JPL = Jet Propulsion Laboratory; GFZ = the German Research Center for Geosciences; TUGRAZ = Graz University of Techology; AIUB = the Astronomical Institute of the University of Bern; COST-G = the International Combination Service for Time-Variable Gravity Fields
{"title":"Comparison of GRACE Gravity Anomaly Solutions for Terrestrial Water Storage Variability in Arid and Semi-arid Botswana","authors":"Mooketsi Segobye, Loago K. Motlogelwa, B. Nkwae, Y. Ouma, Lopang Maphale, Bagadzi M. Manisa","doi":"10.4314/sajg.v12i1.4","DOIUrl":"https://doi.org/10.4314/sajg.v12i1.4","url":null,"abstract":"Explorations of the differences between Gravity Recovery and Climate Experiment (GRACE) solutions in local regions and basins are fundamental in determining their suitability and applicability in these environments. Because of the different mathematical inversions used by the respective processing centers, individual solutions exhibit discrepancies in terms of mass increase or loss, which makes it difficult for users to select the best model for studying terrestrial water storage anomalies (TWSAs). This study compares TWSA trends, as derived from different GRACE solutions over the arid and semi-arid Botswana (2002-2019), where both storage and flux from CSR, JPL, GFZ, TUGRAZ, AIUB, and COST-G[1] were compared. The results show that the six solutions are fairly correlated with the least correlation of R=0.829 between JPL and AIUB, and a maximum of R=0.921 between CSR and TUGRAZ at a 95% confidence level. The TWSA analyses for 2002-2019 indicate that TWS is increasing in Botswana, with the least linear trend of +0.11cm/yr detected from the TUGRAZ inversion model, and the highest linear trend at +0.43cm/year from the COST-G model. On comparing TWS with rainfall, all the solutions presented the same spatio-temporal trends as the rainfall patterns, indicating that the GRACE solutions exhibit the same responses with respect to the received rainfall. Over the 18 years investigated, the long-term rainfall trend was found to decrease, which was only detected by the TUGRAZ model in terms of the recorded equivalent water height (EWH) of -0.008cm/yr from the monthly trend observations. Overall, the AIUB inversion solution gave a better result as its signal was found to be the same as the rainfall signal. \u0000 \u0000[1] CSR = Center for Space Research; JPL = Jet Propulsion Laboratory; GFZ = the German Research Center for Geosciences; TUGRAZ = Graz University of Techology; AIUB = the Astronomical Institute of the University of Bern; COST-G = the International Combination Service for Time-Variable Gravity Fields","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48301827","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}
Urban land use efficiency is a key indicator of the resilience of a city and its sustainability. However, in Africa and Ghana, information on land use efficiency in cities is lacking. There is little to no understanding as to how urban development is affecting the lives of people, the economy and the environment. In this study, geospatial techniques were used to estimate urban land use efficiency (LUE), the changes in the built-up area per capita and urban sprawl speed (SS) for the Sekondi-Takoradi Metropolitan area. Multi-temporal land use maps and population data were used for this purpose. The results indicate that generally land use efficiency in the city has improved since 2002, from a value of 0.67 between 2002 and 2008 to 0.88 between 2008 and 2016, and that it deteriorated slightly above one (1) between 2016 and 2021. The city has also become more built up over the period, with the rate of sprawling also declining. However, the study shows that land in the city that was either agricultural land or grassland has been converted to built-up land use/land cover, which is indeed a challenge for urban agriculture. The results of this study can be used by city authorities as a guide to urban development.
{"title":"Assessment of Land Use Efficiencies of Ghanaian Cities: Case Study of Sekondi-Takoradi Metropolis","authors":"M. S. Aduah, S. Mantey","doi":"10.4314/sajg.v12i1.6","DOIUrl":"https://doi.org/10.4314/sajg.v12i1.6","url":null,"abstract":"Urban land use efficiency is a key indicator of the resilience of a city and its sustainability. However, in Africa and Ghana, information on land use efficiency in cities is lacking. There is little to no understanding as to how urban development is affecting the lives of people, the economy and the environment. In this study, geospatial techniques were used to estimate urban land use efficiency (LUE), the changes in the built-up area per capita and urban sprawl speed (SS) for the Sekondi-Takoradi Metropolitan area. Multi-temporal land use maps and population data were used for this purpose. The results indicate that generally land use efficiency in the city has improved since 2002, from a value of 0.67 between 2002 and 2008 to 0.88 between 2008 and 2016, and that it deteriorated slightly above one (1) between 2016 and 2021. The city has also become more built up over the period, with the rate of sprawling also declining. However, the study shows that land in the city that was either agricultural land or grassland has been converted to built-up land use/land cover, which is indeed a challenge for urban agriculture. The results of this study can be used by city authorities as a guide to urban development.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47171330","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}
Khaled Mahmoud Abdel Aziz, Karim Samir Rashwan, Nasr Saba
The heights determined by Global Positioning System (GPS) refer to the ellipsoid called the World Geodetic System 1984 (WGS84). Global Geopotential Models (GGMs) that are available on GNSS commercial software are generally used to transform ellipsoidal heights to orthometric heights. In this study, the geoid heights of GPS/Levelling were computed to evaluate the accuracy of the geoid heights obtained from two GGMs, namely, the Earth Gravitational Model 96 (EGM96) and the Earth Gravitational Model 08 (EGM08). Seventeen (17) GPS/Levelling stations of the High Accuracy Reference Network (HARN) over Egypt were used for this purpose. The standard deviations for the differences between the geoid heights obtained through GPS/Levelling and those obtained from EGM96 and EGM08 were determined as ± 1.212 m and ± 0.543 m, respectively. This research confirms that the geoid heights obtained from EGM08 are closer to the geoid heights determined using GPS/Levelling over Egypt.
{"title":"Evaluation of EGM96 and EGM08 based on GPS/Levelling Heights in Egypt","authors":"Khaled Mahmoud Abdel Aziz, Karim Samir Rashwan, Nasr Saba","doi":"10.4314/sajg.v12i1.3","DOIUrl":"https://doi.org/10.4314/sajg.v12i1.3","url":null,"abstract":"The heights determined by Global Positioning System (GPS) refer to the ellipsoid called the World Geodetic System 1984 (WGS84). Global Geopotential Models (GGMs) that are available on GNSS commercial software are generally used to transform ellipsoidal heights to orthometric heights. In this study, the geoid heights of GPS/Levelling were computed to evaluate the accuracy of the geoid heights obtained from two GGMs, namely, the Earth Gravitational Model 96 (EGM96) and the Earth Gravitational Model 08 (EGM08). Seventeen (17) GPS/Levelling stations of the High Accuracy Reference Network (HARN) over Egypt were used for this purpose. The standard deviations for the differences between the geoid heights obtained through GPS/Levelling and those obtained from EGM96 and EGM08 were determined as ± 1.212 m and ± 0.543 m, respectively. This research confirms that the geoid heights obtained from EGM08 are closer to the geoid heights determined using GPS/Levelling over Egypt.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45584066","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}
Olusola Gabriel Omogunloye, Nnamdi Samson Iyasele, Olufemi Ayoade Olunlade, O. Abiodun, Tosin J. Salami, Abiodun O. Alabi
Insurgencies by Boko Haram, a terrorist group operating in the north-west African states, have negatively impacted the sense of national security in Nigeria. The activities of the sect have assumed political dimensions in that they have evaded all the possible technical and military solutions that have been implemented. The humanitarian crisis caused by incessant attacks by Boko Haram sects has led to a growth in the population of internally displaced persons and the associated camps accommodating them. This research examined the activities of the Boko Haram sect and how they relate to internally displaced persons, as well as to the challenges faced by the latter from 2009 to 2021. The data used comprise data from the Armed Conflict and Location Event Data Database (ACLED), from the National Emergency Management Agency (NEMA), and geospatial data from Diva-GIS. The method that was applied for this purpose incorporated the use of GIS techniques for mapping the activities of the sect from 2009 to 2021: Microsoft Excel was used for the purposes of data refinement and analysis; while ArcGIS was used for the mapping of the camps of internally displaced persons, as well as for the hotspot and directional analyses in this particular context.. The findings of this research study show that Borno state experiences a 77% frequency of insurgency attacks, followed by Yobe state with 11%. Over the years under study, 2015 is the year recording the highest number of fatalities in Nigeria, with Adamawa recording the highest number of fatalities in a state in spite of it being the least of all the states susceptible to terrorism. Borno, the most terrorized of the states, hosts the largest number of IDP camps but the challenges that these state experiences are relatively limited.
{"title":"Mapping of human displacement by Boko Haram in Nigeria from 2009 to 2021","authors":"Olusola Gabriel Omogunloye, Nnamdi Samson Iyasele, Olufemi Ayoade Olunlade, O. Abiodun, Tosin J. Salami, Abiodun O. Alabi","doi":"10.4314/sajg.v12i1.5","DOIUrl":"https://doi.org/10.4314/sajg.v12i1.5","url":null,"abstract":"Insurgencies by Boko Haram, a terrorist group operating in the north-west African states, have negatively impacted the sense of national security in Nigeria. The activities of the sect have assumed political dimensions in that they have evaded all the possible technical and military solutions that have been implemented. The humanitarian crisis caused by incessant attacks by Boko Haram sects has led to a growth in the population of internally displaced persons and the associated camps accommodating them. This research examined the activities of the Boko Haram sect and how they relate to internally displaced persons, as well as to the challenges faced by the latter from 2009 to 2021. The data used comprise data from the Armed Conflict and Location Event Data Database (ACLED), from the National Emergency Management Agency (NEMA), and geospatial data from Diva-GIS. The method that was applied for this purpose incorporated the use of GIS techniques for mapping the activities of the sect from 2009 to 2021: Microsoft Excel was used for the purposes of data refinement and analysis; while ArcGIS was used for the mapping of the camps of internally displaced persons, as well as for the hotspot and directional analyses in this particular context.. The findings of this research study show that Borno state experiences a 77% frequency of insurgency attacks, followed by Yobe state with 11%. Over the years under study, 2015 is the year recording the highest number of fatalities in Nigeria, with Adamawa recording the highest number of fatalities in a state in spite of it being the least of all the states susceptible to terrorism. Borno, the most terrorized of the states, hosts the largest number of IDP camps but the challenges that these state experiences are relatively limited.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49304936","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}
As a boundary of the seashore, the high-water mark (HWM) is relevant to the public, the State, and other rights holders in the coastal zone. Unlike most fixed property boundaries that are surveyed and beaconed, the HWM is subject to dynamic natural coastal processes and moves over time. Its location is difficult to determine, and the precision of this determination is unknown. This paper reports on an experiment to measure the precision (variability/repeatability) of the location of the HWM at a variety of sites near Cape Town, by volunteer participants. Four sites were chosen along stable (non-mobile) shores along the open, high energy oceanic shores south of Cape Town on the Cape Peninsula. One of these sites exhibits large variation in coastal terrain and type – at this site three sets of measurements were undertaken, bringing the total number of experimental sites to six. Surveying was undertaken in the South African national control survey system using network real-time kinematic global navigation satellite systems (GNSS). This experiment shows that the professional land surveyors located the HWM to ±1,6m, coastal engineers to ±4,1m, and the group of ‘others’ to ±4,2m. The professional land surveyors determined the height of the HWM to ±0,4m over all sites, compared to ±0,7m for all participants. The HWM is likely to be about 4 - 5m above the lowest astronomic tide. However, the line is not a contour – it is affected by weather and local variations in the coastline such as slope and seashore composition. The averaged heights of the HWM at each of the sites for all participants showed a range of 1,3m. Since the boundaries of the seashore cannot be determined with precision, property, cadastral and environmental law needs to continue to respect the nature of this environment and the limitations of locating the HWM.
{"title":"An Experiment in Determining the High-water Mark","authors":"J. Whittal, K. Mackie","doi":"10.4314/sajg.v12i1.1","DOIUrl":"https://doi.org/10.4314/sajg.v12i1.1","url":null,"abstract":"As a boundary of the seashore, the high-water mark (HWM) is relevant to the public, the State, and other rights holders in the coastal zone. Unlike most fixed property boundaries that are surveyed and beaconed, the HWM is subject to dynamic natural coastal processes and moves over time. Its location is difficult to determine, and the precision of this determination is unknown. This paper reports on an experiment to measure the precision (variability/repeatability) of the location of the HWM at a variety of sites near Cape Town, by volunteer participants. Four sites were chosen along stable (non-mobile) shores along the open, high energy oceanic shores south of Cape Town on the Cape Peninsula. One of these sites exhibits large variation in coastal terrain and type – at this site three sets of measurements were undertaken, bringing the total number of experimental sites to six. Surveying was undertaken in the South African national control survey system using network real-time kinematic global navigation satellite systems (GNSS). \u0000This experiment shows that the professional land surveyors located the HWM to ±1,6m, coastal engineers to ±4,1m, and the group of ‘others’ to ±4,2m. The professional land surveyors determined the height of the HWM to ±0,4m over all sites, compared to ±0,7m for all participants. The HWM is likely to be about 4 - 5m above the lowest astronomic tide. However, the line is not a contour – it is affected by weather and local variations in the coastline such as slope and seashore composition. The averaged heights of the HWM at each of the sites for all participants showed a range of 1,3m. Since the boundaries of the seashore cannot be determined with precision, property, cadastral and environmental law needs to continue to respect the nature of this environment and the limitations of locating the HWM.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41438917","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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