This study focused on analyzing the trend of food insecurity in the Northern regions of Ghana. It applied the GIS-based Multi-Criteria Evaluation approach to the criteria of rainfall, land cover, population density, road networks, slope, market centres, potable water access, access to sanitation facilities, and disaster and conflict hotspots. The Weighted Linear Combination (WLC) technique, was used to standardize a set of criteria for each of the four dimensions of food security (availability, accessibility, utilization, and stability) into an ordinary numeric scale after which those factors were accumulated via weighted averaging to determine a composite index for all the districts within the study area. The research found that the food insecurity situation is relatively high, as 174,509 people (6.3 percent) are moderately food insecure while 25,246 people (0.9 percent) are severely food insecure. Overall, 199,755 people, representing 7.2 percent of the population were food insecure (both severely and moderately food insecure). The proportion of the food insecure population was highest in the Tamale metropolis (37.2 percent) and lowest in the Zabzugu and Tatale Sanguli districts (0 percent). A correlation analysis also revealed that the composite food security index was mainly influenced by food utilization (0.75) and stability (0.64). Also, there was no significant relationship between Food stability and the other three dimension of food security (food availability, accessibility, and utilization), implying that it did not influence domestic food production or market access due to the short-term nature of its effect.
{"title":"Spatial dimensions of food and nutrition security in the Northern region of Ghana","authors":"Moses Yao Korbli, Akwasi Acheampong","doi":"10.4314/sajg.v9i2.27","DOIUrl":"https://doi.org/10.4314/sajg.v9i2.27","url":null,"abstract":"This study focused on analyzing the trend of food insecurity in the Northern regions of Ghana. It applied the GIS-based Multi-Criteria Evaluation approach to the criteria of rainfall, land cover, population density, road networks, slope, market centres, potable water access, access to sanitation facilities, and disaster and conflict hotspots. The Weighted Linear Combination (WLC) technique, was used to standardize a set of criteria for each of the four dimensions of food security (availability, accessibility, utilization, and stability) into an ordinary numeric scale after which those factors were accumulated via weighted averaging to determine a composite index for all the districts within the study area. The research found that the food insecurity situation is relatively high, as 174,509 people (6.3 percent) are moderately food insecure while 25,246 people (0.9 percent) are severely food insecure. Overall, 199,755 people, representing 7.2 percent of the population were food insecure (both severely and moderately food insecure). The proportion of the food insecure population was highest in the Tamale metropolis (37.2 percent) and lowest in the Zabzugu and Tatale Sanguli districts (0 percent). A correlation analysis also revealed that the composite food security index was mainly influenced by food utilization (0.75) and stability (0.64). Also, there was no significant relationship between Food stability and the other three dimension of food security (food availability, accessibility, and utilization), implying that it did not influence domestic food production or market access due to the short-term nature of its effect.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43989772","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 exploitation and sustainable use of groundwater has received much attention with the sudden decline in quantity and quality of surface water. Knowledge on the current status of the physico-chemical parameters of groundwater becomes important in ensuring the sustainable use of the resource. This study used Geographic Information System (GIS) to assess groundwater quality in Ahafo-Kenyasi with particular focus on determining the spatial distribution of groundwater quality parameters and also produce groundwater quality map of the area. Physico-chemical analyses of groundwater quality parameters were made after collection of water samples from 24 community boreholes. The results of analysis carried out showed the following concentration ranges: pH (5.12-6.54), EC (71.6-952μS/cm), TDS (35.08-465.59mg/l), Turbidity (0-6.25NTU), Ammonia (0.01-0.61mg/l), Nitrate (0.1-4.12mg/l), Sulphate (1-65.5mg/l). All the samples analysed were above the guidelines set by World Health Organization (WHO, 2011) except for pH and Turbidity. Spatial distribution maps of the individual water quality parameters were developed using kriging interpolation technique and accepted based on the prediction performances of Stable, Exponential, K-Bessel semivariogram models. Overall water quality of the study area was assessed using Water Quality Index (WQI). The results showed that groundwater quality in the area decreases from north-western to south-eastern. However, groundwater from Ahafo-Kenyasi is good for domestic purposes.
{"title":"Geospatial analysis of groundwater quality using GIS: A case study of Ahafo Kenyasi, Ghana","authors":"Ankomah Ernest, Dadzie Isaac","doi":"10.4314/sajg.v10i1.3","DOIUrl":"https://doi.org/10.4314/sajg.v10i1.3","url":null,"abstract":"The exploitation and sustainable use of groundwater has received much attention with the sudden decline in quantity and quality of surface water. Knowledge on the current status of the physico-chemical parameters of groundwater becomes important in ensuring the sustainable use of the resource. This study used Geographic Information System (GIS) to assess groundwater quality in Ahafo-Kenyasi with particular focus on determining the spatial distribution of groundwater quality parameters and also produce groundwater quality map of the area. Physico-chemical analyses of groundwater quality parameters were made after collection of water samples from 24 community boreholes. The results of analysis carried out showed the following concentration ranges: pH (5.12-6.54), EC (71.6-952μS/cm), TDS (35.08-465.59mg/l), Turbidity (0-6.25NTU), Ammonia (0.01-0.61mg/l), Nitrate (0.1-4.12mg/l), Sulphate (1-65.5mg/l). All the samples analysed were above the guidelines set by World Health Organization (WHO, 2011) except for pH and Turbidity. Spatial distribution maps of the individual water quality parameters were developed using kriging interpolation technique and accepted based on the prediction performances of Stable, Exponential, K-Bessel semivariogram models. Overall water quality of the study area was assessed using Water Quality Index (WQI). The results showed that groundwater quality in the area decreases from north-western to south-eastern. However, groundwater from Ahafo-Kenyasi is good for domestic purposes.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49446893","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}
Positional accuracy is one of the important factors which determines acceptability of survey work. Apart from the equipment and method used which affect the accuracy of surveys, time of the day in which the equipment operates can equally affect the accuracy of a survey. In this study, the performance of Unmanned Aerial Vehicle (UAV) surveys as well as the appropriate time in the day to apply the technology in Tarkwa, Ghana, has been investigated. The paper assessed the positional accuracies of ground features on UAV-based orthophotos (with emphasis on horizontal coordinates), captured at different times of the day, keeping all other parameters unchanged for capturing, production and processing of all orthophotos each time. The positional accuracies of selected features on the orthophotos were determined by calculating the Root Mean Square Error (RMSE) between the feature coordinates on the ground measured with GNSS Receivers and those derived from the UAV-based orthophotos. The results show that coordinates derived from orthophotos captured in the morning, with average temperatures between 21 ℃ and 23 ℃, and average wind speed of not more than 10 m/s, produced images with the highest positional accuracies, with RMSE values between 0.0047 m and 0.0283 m. These RMSE are within the range of values recommended for standard mapping surveys as well as GIS.
{"title":"Assessment of positional accuracies of UAV-based coordinates derived from orthophotos at varying times of the day- A case study","authors":"S. Mantey, M. S. Aduah","doi":"10.4314/sajg.v10i1.4","DOIUrl":"https://doi.org/10.4314/sajg.v10i1.4","url":null,"abstract":"Positional accuracy is one of the important factors which determines acceptability of survey work. Apart from the equipment and method used which affect the accuracy of surveys, time of the day in which the equipment operates can equally affect the accuracy of a survey. In this study, the performance of Unmanned Aerial Vehicle (UAV) surveys as well as the appropriate time in the day to apply the technology in Tarkwa, Ghana, has been investigated. The paper assessed the positional accuracies of ground features on UAV-based orthophotos (with emphasis on horizontal coordinates), captured at different times of the day, keeping all other parameters unchanged for capturing, production and processing of all orthophotos each time. The positional accuracies of selected features on the orthophotos were determined by calculating the Root Mean Square Error (RMSE) between the feature coordinates on the ground measured with GNSS Receivers and those derived from the UAV-based orthophotos. The results show that coordinates derived from orthophotos captured in the morning, with average temperatures between 21 ℃ and 23 ℃, and average wind speed of not more than 10 m/s, produced images with the highest positional accuracies, with RMSE values between 0.0047 m and 0.0283 m. These RMSE are within the range of values recommended for standard mapping surveys as well as GIS.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47478687","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}
Forest fire is a devastating phenomenon in real life, causing huge losses of lives, properties and ecologies. A risk assessment model to identify, classify and map forest fire risk areas is presented in this paper. This model considers four risk models, i.e. ignition model, detection model, response model and fuel model analysis. The first model concentrates on human influence factors in forest fires, including the land use, distance from roads, and distance from settlements and the second model is made up of the possibility of fire visibility from road and settlement viewpoint. The forest fire response included distance from fire stations and motion resistance is the third model. The type of fuel (dry or wet), fuel moisture content, health of the forest vegetation and topography of the area were analysed as the fourth model. The study results indicate that very high-risk zones covered 38.8km2 representing 25.6% of the total forest area. Findings of the research are helpful in developing forest fire management systems. Fast and appropriate direction could be used by management to stop the spread of fire effectively. It also helps to provide effective means for protecting forests from fires as well as to formulate appropriate methods to control and manage forest fire damages and its spread. Recommendations were made at the end of the work to implement fire towers, break lines and employ the use of modern detection techniques such drones, etc to improve fire detection and response.
{"title":"Modelling the risk of forest to fire for the Bosomkese Forest Reserve, Ahafo Region, Ghana","authors":"Adams Elias Dadzie, A. Mary","doi":"10.4314/sajg.v10i1.5","DOIUrl":"https://doi.org/10.4314/sajg.v10i1.5","url":null,"abstract":"Forest fire is a devastating phenomenon in real life, causing huge losses of lives, properties and ecologies. A risk assessment model to identify, classify and map forest fire risk areas is presented in this paper. This model considers four risk models, i.e. ignition model, detection model, response model and fuel model analysis. The first model concentrates on human influence factors in forest fires, including the land use, distance from roads, and distance from settlements and the second model is made up of the possibility of fire visibility from road and settlement viewpoint. The forest fire response included distance from fire stations and motion resistance is the third model. The type of fuel (dry or wet), fuel moisture content, health of the forest vegetation and topography of the area were analysed as the fourth model. The study results indicate that very high-risk zones covered 38.8km2 representing 25.6% of the total forest area. Findings of the research are helpful in developing forest fire management systems. Fast and appropriate direction could be used by management to stop the spread of fire effectively. It also helps to provide effective means for protecting forests from fires as well as to formulate appropriate methods to control and manage forest fire damages and its spread. Recommendations were made at the end of the work to implement fire towers, break lines and employ the use of modern detection techniques such drones, etc to improve fire detection and response.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43811142","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 main aim of this paper is to demonstrate the mapping outputs of the historic core of Gonabad city based on both physical and nonphysical elements. Despite the fact that the architectural elements have been the main sources of data for the conservation of the historic part of cities, seemingly, the cognitive map based on the perceptions of the inhabitants could enhance the level of the reliability of the outputs. The methods of the research were designed based on the survey and interview to collect both physical and nonphysical data. The physical was included the current historical elements such as mosque, school, and water storage, and the nonphysical was included the destroyed elements such as the wall, gates, towers that have been part of the memories of the inhabitants. ArcGIS was applied for overlaying the data. The findings of the research identified that despite the architectural elements located in a specific location, perception of the people referred to the broader areas in terms of the historic area. As a conclusion, both historical areas of the city include a different pattern of the development. The physical and nonphysical elements played a significant role to highlight the historic core of the city. However, the cognitive map based on the perception of users is not fitted exactly with the geo-reference data, and it is more flexible in terms of conceptual forms. The result of the study represented the map of the historic cores of the city for conservation activity.
{"title":"Application of physical and nonphysical elements in the conservation of historic core of city","authors":"R. Tafahomi","doi":"10.4314/sajg.v10i1.6","DOIUrl":"https://doi.org/10.4314/sajg.v10i1.6","url":null,"abstract":"The main aim of this paper is to demonstrate the mapping outputs of the historic core of Gonabad city based on both physical and nonphysical elements. Despite the fact that the architectural elements have been the main sources of data for the conservation of the historic part of cities, seemingly, the cognitive map based on the perceptions of the inhabitants could enhance the level of the reliability of the outputs. The methods of the research were designed based on the survey and interview to collect both physical and nonphysical data. The physical was included the current historical elements such as mosque, school, and water storage, and the nonphysical was included the destroyed elements such as the wall, gates, towers that have been part of the memories of the inhabitants. ArcGIS was applied for overlaying the data. The findings of the research identified that despite the architectural elements located in a specific location, perception of the people referred to the broader areas in terms of the historic area. As a conclusion, both historical areas of the city include a different pattern of the development. The physical and nonphysical elements played a significant role to highlight the historic core of the city. However, the cognitive map based on the perception of users is not fitted exactly with the geo-reference data, and it is more flexible in terms of conceptual forms. The result of the study represented the map of the historic cores of the city for conservation activity.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47987649","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}
Flood prediction is very important in land and water resources management. Many flood disasters could be mitigated with adequate preparedness especially in urban watershed. This study assessed the runoff potential of Opa watershed in Southwest Nigeria using remote sensing and the Soil Conservation Service or SCS curve number (CN) techniques. The 2007 NigSat image of the year 2007 was classified into different land cover classes and combined with its hydrological soil groups to determine the curve number of each sub-watershed. The sub-watershed with low curve number is considered to have lower runoff potential while the one with higher curve number is considered to have higher runoff potential. The CN was also used to estimate the potential maximum retention, (S) and potential runoff, (Q) for each sub-watershed using a rainfall event of 2-year return period in the watershed. The weighted runoff was used to determine sub-watersheds with highest and lowest runoff potential. The study showed that urban sub-watershed 9 with average CN value of 85.93 has highest weighted runoff potential (5.53 mm) while the vegetated sub-watershed 10 with average CN value of 69.46 has the lowest weighted runoff potential (0.34 mm). The study concluded that using available geospatial technology and appropriate hydrologic assessment techniques constitute an effective flood prediction method for disaster risk reduction and sustainable urban watershed management.
{"title":"Assessment of runoff potential for disaster risk reduction using geospatial technology in Opa watershed, Southwestern Nigeria","authors":"Orewole Maruf Oladotun","doi":"10.4314/sajg.v10i2.8","DOIUrl":"https://doi.org/10.4314/sajg.v10i2.8","url":null,"abstract":"Flood prediction is very important in land and water resources management. Many flood disasters could be mitigated with adequate preparedness especially in urban watershed. This study assessed the runoff potential of Opa watershed in Southwest Nigeria using remote sensing and the Soil Conservation Service or SCS curve number (CN) techniques. The 2007 NigSat image of the year 2007 was classified into different land cover classes and combined with its hydrological soil groups to determine the curve number of each sub-watershed. The sub-watershed with low curve number is considered to have lower runoff potential while the one with higher curve number is considered to have higher runoff potential. The CN was also used to estimate the potential maximum retention, (S) and potential runoff, (Q) for each sub-watershed using a rainfall event of 2-year return period in the watershed. The weighted runoff was used to determine sub-watersheds with highest and lowest runoff potential. The study showed that urban sub-watershed 9 with average CN value of 85.93 has highest weighted runoff potential (5.53 mm) while the vegetated sub-watershed 10 with average CN value of 69.46 has the lowest weighted runoff potential (0.34 mm). The study concluded that using available geospatial technology and appropriate hydrologic assessment techniques constitute an effective flood prediction method for disaster risk reduction and sustainable urban watershed management.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46058529","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}
This paper estimates bare area gain detected using cloud free Landsat 7 (ETM+) and Landsat 8 (OLI) in Botswana. From 2002 to 2020, agricultural fields shrunk by 76.4%, while built-up increased by 49.2%, and bare areas increased from 3.32% to 7.03% (or 111.7%). There is a significant seasonal change in bare area detected reaching maximum during the dry season when there is little or no ground cover. In this study, the seasonality of bare area gain was overcome by only considering a bare area pixel to contribute to bare area gain if it exists during both the winter and summer months. The probability of bare area detection was 75.0% and probability of false detection 13.3% respectively. The 13% false detection tended to be built-up areas which had similar spectral characteristics as bare areas since most built-up areas have no ground cover. The bare area gain is driven by the high population growth rate of 3.4%. From 2001 to 2017, the population of the study area has increased by 34% and now accounts for 47% of the population of Botswana.
{"title":"Non-seasonal Landsat based bare area gain detection in Botswana during 2002 to 2020 Period using Maximum Likelihood Classifier (MLC).","authors":"R. Tsheko","doi":"10.4314/sajg.v11i1.7","DOIUrl":"https://doi.org/10.4314/sajg.v11i1.7","url":null,"abstract":"This paper estimates bare area gain detected using cloud free Landsat 7 (ETM+) and Landsat 8 (OLI) in Botswana. From 2002 to 2020, agricultural fields shrunk by 76.4%, while built-up increased by 49.2%, and bare areas increased from 3.32% to 7.03% (or 111.7%). There is a significant seasonal change in bare area detected reaching maximum during the dry season when there is little or no ground cover. In this study, the seasonality of bare area gain was overcome by only considering a bare area pixel to contribute to bare area gain if it exists during both the winter and summer months. The probability of bare area detection was 75.0% and probability of false detection 13.3% respectively. The 13% false detection tended to be built-up areas which had similar spectral characteristics as bare areas since most built-up areas have no ground cover. The bare area gain is driven by the high population growth rate of 3.4%. From 2001 to 2017, the population of the study area has increased by 34% and now accounts for 47% of the population of Botswana.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43873341","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}
Heindrich du Plessis, H. Grobler, Curtis Mashimbye
The purpose of this paper is to investigate the geographical information science (GISc) competencies, knowledge, and skills required by practitioners working in the mining and exploration industries. The paper promotes the appropriate design of education programs including short learning programs (SLP) as well as emerging delivery mechanisms such as distance learning opportunities. Programs are submitted for quality control through certification and accreditation at quality control councils such as the Council for Higher Education (CHE), South African Qualifications Authority (SAQA) and the South African Geomatics Council (SAGC). The paper concludes with a proposed module composition that is still subject to further consultation and input from the mining industry.
{"title":"A review of GISc education, its value and use in the mining and exploration industries","authors":"Heindrich du Plessis, H. Grobler, Curtis Mashimbye","doi":"10.4314/sajg.v11i1.9","DOIUrl":"https://doi.org/10.4314/sajg.v11i1.9","url":null,"abstract":"The purpose of this paper is to investigate the geographical information science (GISc) competencies, knowledge, and skills required by practitioners working in the mining and exploration industries. The paper promotes the appropriate design of education programs including short learning programs (SLP) as well as emerging delivery mechanisms such as distance learning opportunities. Programs are submitted for quality control through certification and accreditation at quality control councils such as the Council for Higher Education (CHE), South African Qualifications Authority (SAQA) and the South African Geomatics Council (SAGC). The paper concludes with a proposed module composition that is still subject to further consultation and input from the mining industry.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41825370","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}
Remote sensing and GIS are often used to assess spatiotemporal variations for land use/land cover (LULC) monitoring and classification. While LULC monitoring and classification has been undertaken in Eswatini, little attention has been given to ascertaining covered thematic areas, methods of image classification, and approaches and techniques for improving classification accuracy. This paper summarises and synthesizes the progress made in the Kingdom of Eswatini regarding the application of remote sensing and GIS in LULC monitoring and classification. Eight thematic areas (water resources mapping; land degradation; forestry; wildfire detection; urban expansion; crop production; disease surveillance; general mapping) dominate evaluated LULC studies, employing three LULC classification methods (classic; manual; advanced). While some studies include strengths and weaknesses of LULC classification techniques applied, others do not. This review shows that only two advanced classifiers (random forest; object-based) were identified from the reviewed articles. In addition, reviewed studies applied only two approaches (use of multi temporal data; fine spatial resolution data) and three techniques (use of ancillary data; post-classification procedure; the use of multisource data) for improving classification accuracy. Furthermore, the review finds that limited LULC investigations have been covered in Eswatini with a specific focus on the Sustainable Development Goals (SDGs). As such, this review recommends 1) the inclusion of higher resolution imagery for mapping purposes, 2) the adaptation of strengths and weaknesses for any image classification technique employed in future publications, 3) the use of more varied approaches and techniques for improving classification accuracy and area estimates, 4) inclusion of standard errors or confidence intervals for error-adjusted area estimates as part of accuracy assessment reporting, 5) the application of advanced image classifiers, and 6) the application of Earth Observation (EO) Analysis Ready Data (ARD) in the production of information for the support of the SDGs.
{"title":"The use of remote sensing and GIS for land use and land cover mapping in Eswatini: A Review","authors":"Sabelo P. Simelane, C. Hansen, C. Munghemezulu","doi":"10.4314/sajg.v10i2.13","DOIUrl":"https://doi.org/10.4314/sajg.v10i2.13","url":null,"abstract":"Remote sensing and GIS are often used to assess spatiotemporal variations for land use/land cover (LULC) monitoring and classification. While LULC monitoring and classification has been undertaken in Eswatini, little attention has been given to ascertaining covered thematic areas, methods of image classification, and approaches and techniques for improving classification accuracy. This paper summarises and synthesizes the progress made in the Kingdom of Eswatini regarding the application of remote sensing and GIS in LULC monitoring and classification. Eight thematic areas (water resources mapping; land degradation; forestry; wildfire detection; urban expansion; crop production; disease surveillance; general mapping) dominate evaluated LULC studies, employing three LULC classification methods (classic; manual; advanced). While some studies include strengths and weaknesses of LULC classification techniques applied, others do not. This review shows that only two advanced classifiers (random forest; object-based) were identified from the reviewed articles. In addition, reviewed studies applied only two approaches (use of multi temporal data; fine spatial resolution data) and three techniques (use of ancillary data; post-classification procedure; the use of multisource data) for improving classification accuracy. Furthermore, the review finds that limited LULC investigations have been covered in Eswatini with a specific focus on the Sustainable Development Goals (SDGs). As such, this review recommends 1) the inclusion of higher resolution imagery for mapping purposes, 2) the adaptation of strengths and weaknesses for any image classification technique employed in future publications, 3) the use of more varied approaches and techniques for improving classification accuracy and area estimates, 4) inclusion of standard errors or confidence intervals for error-adjusted area estimates as part of accuracy assessment reporting, 5) the application of advanced image classifiers, and 6) the application of Earth Observation (EO) Analysis Ready Data (ARD) in the production of information for the support of the SDGs.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45735197","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}
Tropospheric delay prediction models have become increasingly important in Global Navigation Satellite System (GNSS) as they play a critical role in GNSS positioning applications. Due to the different atmospheric conditions over the earth regions, tropospheric effect on GNSS signals also differs, influencing the performance of these prediction models. Thus, the choice of a particular prediction model can significantly degrade the positioning accuracy especially when the model does not suit the user’s environs. Therefore, a performance assessment of existing prediction models in various regions for a suitable one is very imperative. This paper evaluates and analyses seven commonly used tropospheric delay models in Ghana in terms of performances in Zenith Tropospheric Delay (ZTD) estimation and baseline positional accuracies using data from six selected Continuously Operating Reference Stations (CORS). The 1˚x1˚ gridded Vienna Mapping Functions 3 (VMF3) ZTD product and coordinates solutions from the CSRS-PPP positioning service were respectively used as references. The results show that the Black model performed better in estimating the ZTD, followed by Askne and Nordius model. The Saastamoinen, Marini and Murray, Niell, Goads and Goodman and Hopfield models respectively performed poorly. However, the result of the baseline solutions did not show much variation in the coordinate difference provided by the use of the prediction models, nonetheless, the Black and Askne and Nordius models continue to dominate the other models. Of all the models evaluated, either Black or Askne and Nordius model is recommended for use to mitigate the ZTD in the study area, however, the choice of the Black model will be more desirable.
{"title":"Comparative evaluation and analysis of different tropospheric delay models in Ghana","authors":"S. Osah, Akwasi Acheampong, I. Dadzie, C. Fosu","doi":"10.4314/sajg.v10i2.10","DOIUrl":"https://doi.org/10.4314/sajg.v10i2.10","url":null,"abstract":"Tropospheric delay prediction models have become increasingly important in Global Navigation Satellite System (GNSS) as they play a critical role in GNSS positioning applications. Due to the different atmospheric conditions over the earth regions, tropospheric effect on GNSS signals also differs, influencing the performance of these prediction models. Thus, the choice of a particular prediction model can significantly degrade the positioning accuracy especially when the model does not suit the user’s environs. Therefore, a performance assessment of existing prediction models in various regions for a suitable one is very imperative. This paper evaluates and analyses seven commonly used tropospheric delay models in Ghana in terms of performances in Zenith Tropospheric Delay (ZTD) estimation and baseline positional accuracies using data from six selected Continuously Operating Reference Stations (CORS). The 1˚x1˚ gridded Vienna Mapping Functions 3 (VMF3) ZTD product and coordinates solutions from the CSRS-PPP positioning service were respectively used as references. The results show that the Black model performed better in estimating the ZTD, followed by Askne and Nordius model. The Saastamoinen, Marini and Murray, Niell, Goads and Goodman and Hopfield models respectively performed poorly. However, the result of the baseline solutions did not show much variation in the coordinate difference provided by the use of the prediction models, nonetheless, the Black and Askne and Nordius models continue to dominate the other models. Of all the models evaluated, either Black or Askne and Nordius model is recommended for use to mitigate the ZTD in the study area, however, the choice of the Black model will be more desirable.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49177782","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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