Obituary compiled by Frank Naude from input by the Kirby family and friends.
讣告由Frank Naude根据Kirby家人和朋友的意见汇编而成。
{"title":"Obituary David Warton (Dave) Kirby","authors":"Francis Ulman Naude","doi":"10.4314/sajg.v10i1.7","DOIUrl":"https://doi.org/10.4314/sajg.v10i1.7","url":null,"abstract":"Obituary compiled by Frank Naude from input by the Kirby family and friends.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41313660","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. Idrees, D. Omar, A. Babalola, Hussein. A. Ahmadu, Abdulganiyu Abdu Yusuf, Falilat O. Lawal
Generation of land use/land cover map at different spatial scales using satellite remote sensing data has been in practice as far back as early 1970s. Since then, research focus has been on the development of classification steps and improving the quality of the resulting maps. In recent times, the demand for detailed high accuracy land-use and land-cover (LULC) data has been on the increase due to the growing complexity of earth processes, while, at the same time, processing step is becoming more complex. This paper explores Landsat 8 derived normalized difference vegetation index (NDVI) threshold for the purpose of simplifying land cover classification process. NDVI images of January, May and December, 2018, representing dry, wet and harmattan seasons were generated. Thereafter, NDVI values corresponding to the location of a set of training data representing the target urban land covers (water, built-up area, soil, grassland and shrub) were extracted. Using the statistics of the extracted values, NDVI threshold for the respective land cover type were determined for the classification process. Finally, the classification accuracy was evaluated using the unbiased matrix coefficient technique which produced overall accuracy of 71.3%, 46.4% and 75.6% at 95% confidence limit for the months of January, May and December of the year review respectively. The result has shown that NDVI threshold is a simple and practical alternative to obtain LULC map at a reasonable time with a few data.
{"title":"Urban land use land cover mapping in tropical savannah using Landsat-8 derived normalized difference vegetation index (NDVI) threshold","authors":"M. Idrees, D. Omar, A. Babalola, Hussein. A. Ahmadu, Abdulganiyu Abdu Yusuf, Falilat O. Lawal","doi":"10.4314/sajg.v11i1.8","DOIUrl":"https://doi.org/10.4314/sajg.v11i1.8","url":null,"abstract":"Generation of land use/land cover map at different spatial scales using satellite remote sensing data has been in practice as far back as early 1970s. Since then, research focus has been on the development of classification steps and improving the quality of the resulting maps. In recent times, the demand for detailed high accuracy land-use and land-cover (LULC) data has been on the increase due to the growing complexity of earth processes, while, at the same time, processing step is becoming more complex. This paper explores Landsat 8 derived normalized difference vegetation index (NDVI) threshold for the purpose of simplifying land cover classification process. NDVI images of January, May and December, 2018, representing dry, wet and harmattan seasons were generated. Thereafter, NDVI values corresponding to the location of a set of training data representing the target urban land covers (water, built-up area, soil, grassland and shrub) were extracted. Using the statistics of the extracted values, NDVI threshold for the respective land cover type were determined for the classification process. Finally, the classification accuracy was evaluated using the unbiased matrix coefficient technique which produced overall accuracy of 71.3%, 46.4% and 75.6% at 95% confidence limit for the months of January, May and December of the year review respectively. The result has shown that NDVI threshold is a simple and practical alternative to obtain LULC map at a reasonable time with a few data.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42402780","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}
Water is a scarce resource in South Africa, and approximately 62% of the water used in South Africa is for irrigation. This water is stored in many small dams scattered across the country. If not managed correctly, they could have a negative effect on catchment areas and on the availability of water. As such, there is a need for a new monitoring and management system to be developed. This study determined the minimum surface area that would be required for a waterbody to be detected on Sentinel-1 Synthetic Aperture Radar imagery. A Random Forest classifier was used to detect waterbodies on a Sentinel-1 image calculated from a time series of imagery taken over a period of three months. Steep incidence angles outperformed shallow incidence angles, with the classification having an overall accuracy of 80%. Detection rates were almost 90% for waterbodies of one hectare and greater, with no false positives, and a 10% false negative rate. These findings provide the foundation for developing a detection and monitoring system, which would allow for the better management of water resources in South Africa.
{"title":"Small dams: determining the minimum waterbody surface area that can be successfully detected using Sentinel-1 SAR imagery","authors":"M. von Fintel, J. Kemp","doi":"10.4314/sajg.v11i2.9","DOIUrl":"https://doi.org/10.4314/sajg.v11i2.9","url":null,"abstract":"Water is a scarce resource in South Africa, and approximately 62% of the water used in South Africa is for irrigation. This water is stored in many small dams scattered across the country. If not managed correctly, they could have a negative effect on catchment areas and on the availability of water. As such, there is a need for a new monitoring and management system to be developed. This study determined the minimum surface area that would be required for a waterbody to be detected on Sentinel-1 Synthetic Aperture Radar imagery. A Random Forest classifier was used to detect waterbodies on a Sentinel-1 image calculated from a time series of imagery taken over a period of three months. Steep incidence angles outperformed shallow incidence angles, with the classification having an overall accuracy of 80%. Detection rates were almost 90% for waterbodies of one hectare and greater, with no false positives, and a 10% false negative rate. These findings provide the foundation for developing a detection and monitoring system, which would allow for the better management of water resources in South Africa.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49519740","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}
L. Du Toit, Ivan Henrico, J. Bezuidenhout, B. Mtshawu
The construction of the Saldanha Port has been the reason for the major changes in the bathymetry and sediment dynamics observed in Saldanha Bay in the last decades. In this paper, newly acquired soundings from the National Hydrographer were used to analyse the changes between 1977 and 2021 - over a 44-year period - in the bathymetry of Saldanha Bay. The Ordinary Kriging (OK) interpolation method, available through the Geostatistical Wizard in ArcGIS Pro, was used for creating surface models to conduct comparisons with the bathymetry of Saldanha Bay. The results indicate a general increase in depth since 1977 of between 0.395 and 3.203 m, and an average increase in depth within the Big Bay of 1.799 m. Between 1977 and 2021, a total volume loss of 49 364 560.0 m3 in sediment was calculated - an indication of how the sedimentation process in Saldanha Bay has changed subsequent to the construction of the harbour.
{"title":"Analysing the changes in the bathymetry of Saldanha Bay between the years 1977 and 2021","authors":"L. Du Toit, Ivan Henrico, J. Bezuidenhout, B. Mtshawu","doi":"10.4314/sajg.v11i2.11","DOIUrl":"https://doi.org/10.4314/sajg.v11i2.11","url":null,"abstract":"The construction of the Saldanha Port has been the reason for the major changes in the bathymetry and sediment dynamics observed in Saldanha Bay in the last decades. In this paper, newly acquired soundings from the National Hydrographer were used to analyse the changes between 1977 and 2021 - over a 44-year period - in the bathymetry of Saldanha Bay. The Ordinary Kriging (OK) interpolation method, available through the Geostatistical Wizard in ArcGIS Pro, was used for creating surface models to conduct comparisons with the bathymetry of Saldanha Bay. The results indicate a general increase in depth since 1977 of between 0.395 and 3.203 m, and an average increase in depth within the Big Bay of 1.799 m. Between 1977 and 2021, a total volume loss of 49 364 560.0 m3 in sediment was calculated - an indication of how the sedimentation process in Saldanha Bay has changed subsequent to the construction of the harbour.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47191673","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}
Under the second phase of the National Oil Palm Project, the Government of Uganda plans to extend the oil palm project to Northern Uganda. According to the Final Project Design Report (2017) of the National Oil Palm Project, and based on the rainfall, soil and temperature of the region, areas in Northern Uganda have already been mapped for the project. However, no detailed information on the degree of suitability of the areas has been provided. In this research, other parameters such as land cover, elevation and slope were identified through the literature review. Furthermore, on the basis of the reclassify tool in ArcMap 10.8, the data were then reclassified into four classes, namely, highly suitable (S1), moderately suitable (S2), marginally suitable (S3) and unsuitable (N.) With the aid of the Analytical Hierarchical Process (AHP), pairwise comparison matrices were constructed and the weight of each parameter was computed. The suitability map obtained from a weighted linear combination identified 38.18%, 35.54%, 21.41% and 4.87% of the land area as highly suitable, moderately suitable, marginally suitable and unsuitable, respectively. A geospatial assessment of the suitability of the land for oil palm growing was carried out. It was based on only the soil types, but excluded the chemical properties of the soil. Therefore, further research on the chemical properties of the soils at suitable sites should be carried out. In-depth research should be carried out While considering social and economic factors among the criteria to determine the willingness and financial capability of the people to venture into oil palm growing as a source of income, Oil Palm Uganda Limited should conduct in-depth research into this issue.
{"title":"Geospatial assessment of land suitability for oil palm (Elaeis guineensis Jacq.) growing in Northern Uganda.","authors":"Anjo Abraham, Ivan Bamweyana","doi":"10.4314/sajg.v11i2.10","DOIUrl":"https://doi.org/10.4314/sajg.v11i2.10","url":null,"abstract":"Under the second phase of the National Oil Palm Project, the Government of Uganda plans to extend the oil palm project to Northern Uganda. According to the Final Project Design Report (2017) of the National Oil Palm Project, and based on the rainfall, soil and temperature of the region, areas in Northern Uganda have already been mapped for the project. However, no detailed information on the degree of suitability of the areas has been provided. In this research, other parameters such as land cover, elevation and slope were identified through the literature review. Furthermore, on the basis of the reclassify tool in ArcMap 10.8, the data were then reclassified into four classes, namely, highly suitable (S1), moderately suitable (S2), marginally suitable (S3) and unsuitable (N.) With the aid of the Analytical Hierarchical Process (AHP), pairwise comparison matrices were constructed and the weight of each parameter was computed. The suitability map obtained from a weighted linear combination identified 38.18%, 35.54%, 21.41% and 4.87% of the land area as highly suitable, moderately suitable, marginally suitable and unsuitable, respectively. A geospatial assessment of the suitability of the land for oil palm growing was carried out. It was based on only the soil types, but excluded the chemical properties of the soil. Therefore, further research on the chemical properties of the soils at suitable sites should be carried out. In-depth research should be carried out While considering social and economic factors among the criteria to determine the willingness and financial capability of the people to venture into oil palm growing as a source of income, Oil Palm Uganda Limited should conduct in-depth research into this issue.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43628824","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}
Flooding in Lagos State has been on the rise in the past two decades, especially in the Eti-Osa area of the state. This is largely due to the increased volume of rainfall associated with climate variability and sea level rise. Flooding incidents have led to loss of lives and properties. The objective of this study is to examine the dynamics of flood occurrences in the Eti-Osa area of Lagos metropolis. Rainfall data for the area covering a period of 30 years (1990 to 2019) were obtained from the Nigerian Meteorological Agency (NiMET) in Lagos, and analyzed using the basic descriptive statistical technique. The purpose was to evaluate rainfall characteristics that were influencing flooding events in the area. Furthermore, remotely sensed multi-date Landsat imageries of 1990, 1997, 2001, 2012, and 2017 were obtained, and analyzed to determine how land use and land cover characteristics have changed and have been affected by flooding over the study period. The data were subjected to digital image processing and supervised classification was carried out on the images of the various dates. Results showed that flooding became prevalent as more areas became built up and as vegetated areas declined. Also, flooding events appeared to be responsive to the climatic extremes. Moreover, poor drainage, increased population number s, and non-compliance to building and current environmental regulations were key factors that exacerbated the increased prevalence of flooding in the area. The study recommended that flood control policies, including land-use planning for the area, need to be pursued urgently.
{"title":"Geospatial assessment of land use/cover, rainfall, and flood incidents in Eti–Osa, Lagos, Nigeria","authors":"Toka Sunday Onajomo","doi":"10.4314/sajg.v11i2.3","DOIUrl":"https://doi.org/10.4314/sajg.v11i2.3","url":null,"abstract":"Flooding in Lagos State has been on the rise in the past two decades, especially in the Eti-Osa area of the state. This is largely due to the increased volume of rainfall associated with climate variability and sea level rise. Flooding incidents have led to loss of lives and properties. The objective of this study is to examine the dynamics of flood occurrences in the Eti-Osa area of Lagos metropolis. Rainfall data for the area covering a period of 30 years (1990 to 2019) were obtained from the Nigerian Meteorological Agency (NiMET) in Lagos, and analyzed using the basic descriptive statistical technique. The purpose was to evaluate rainfall characteristics that were influencing flooding events in the area. Furthermore, remotely sensed multi-date Landsat imageries of 1990, 1997, 2001, 2012, and 2017 were obtained, and analyzed to determine how land use and land cover characteristics have changed and have been affected by flooding over the study period. The data were subjected to digital image processing and supervised classification was carried out on the images of the various dates. Results showed that flooding became prevalent as more areas became built up and as vegetated areas declined. Also, flooding events appeared to be responsive to the climatic extremes. Moreover, poor drainage, increased population number s, and non-compliance to building and current environmental regulations were key factors that exacerbated the increased prevalence of flooding in the area. The study recommended that flood control policies, including land-use planning for the area, need to be pursued urgently.","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":"43843790","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}
Fire regimes have the potential to disturb ecological aspects of a landscape and/or contribute to the maintenance of the biological diversity. Thus, a gauge of the impact of planned and unplanned fire regimes is vital to South Africa’s national reserves. The Jonkershoek Nature Reserve in the Western Cape is characterized by the occurrence of indigenous Fynbos and Afromontane Forest vegetation. Geographical Information Systems (GIS) and Remote Sensing (RS) can aid the management and preservation of indigenous vegetational species. This study used knowledge of the ecological conditions of the Reserve, historical fire data, Landsat TM and Landsat OLI imagery, and geospatial analysis to investigate the impact of the fire regimes in the Reserve. Image classification was carried out from 2005 to 2015 to determine the burn patterns, with the process being aided by the fire regime history from 1970 to 2015. Ordinary Least Squares (OLS) analysis was carried out to determine how abiotic factors, such as elevation, slope and aspect, impact fires in the Reserve. The assessment of fires included the ascertainment of their location, coverage, and frequency, the Normalised Burn Ratio (NBR), the differenced Normalised Burn Ratio (dNBR) and the Normalised Difference Vegetation Index (NDVI). There were 39 fires recorded in the Jonkershoek Nature Reserve from 1970 to 2015. The largest fire events were recorded in 1999 (26503.6 ha.) and 2015 (8363.0 ha.). The lowest area of fire impact recorded occurred in the years 2010 (0.15ha.), 1973 (1.1 ha.) and 1987 (3.1 ha.). With an overall classification accuracy of 94.17%, the Landsat OLI imagery performed better with an overall classification accuracy of 94.17% than the Landsat TM at 75.83%. The OLS regression showed that fire severity was positively correlated to NDVI and elevation. This may suggest that regions of healthy vegetation at any altitude may be susceptible to burnings if there is sufficient vegetation to fuel a fire. The OLS was negatively correlated to slope and aspect. This may impact fire risk as steeper slopes may have vegetation growing in their fire shadow.
{"title":"GIS investigation of the fire history of Jonkershoek Nature Reserve","authors":"S. Mashele, K. Singh","doi":"10.4314/sajg.v11i2.2","DOIUrl":"https://doi.org/10.4314/sajg.v11i2.2","url":null,"abstract":"Fire regimes have the potential to disturb ecological aspects of a landscape and/or contribute to the maintenance of the biological diversity. Thus, a gauge of the impact of planned and unplanned fire regimes is vital to South Africa’s national reserves. The Jonkershoek Nature Reserve in the Western Cape is characterized by the occurrence of indigenous Fynbos and Afromontane Forest vegetation. Geographical Information Systems (GIS) and Remote Sensing (RS) can aid the management and preservation of indigenous vegetational species. This study used knowledge of the ecological conditions of the Reserve, historical fire data, Landsat TM and Landsat OLI imagery, and geospatial analysis to investigate the impact of the fire regimes in the Reserve. Image classification was carried out from 2005 to 2015 to determine the burn patterns, with the process being aided by the fire regime history from 1970 to 2015. Ordinary Least Squares (OLS) analysis was carried out to determine how abiotic factors, such as elevation, slope and aspect, impact fires in the Reserve. The assessment of fires included the ascertainment of their location, coverage, and frequency, the Normalised Burn Ratio (NBR), the differenced Normalised Burn Ratio (dNBR) and the Normalised Difference Vegetation Index (NDVI). There were 39 fires recorded in the Jonkershoek Nature Reserve from 1970 to 2015. The largest fire events were recorded in 1999 (26503.6 ha.) and 2015 (8363.0 ha.). The lowest area of fire impact recorded occurred in the years 2010 (0.15ha.), 1973 (1.1 ha.) and 1987 (3.1 ha.). With an overall classification accuracy of 94.17%, the Landsat OLI imagery performed better with an overall classification accuracy of 94.17% than the Landsat TM at 75.83%. The OLS regression showed that fire severity was positively correlated to NDVI and elevation. This may suggest that regions of healthy vegetation at any altitude may be susceptible to burnings if there is sufficient vegetation to fuel a fire. The OLS was negatively correlated to slope and aspect. This may impact fire risk as steeper slopes may have vegetation growing in their fire shadow.","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":"49387584","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 evapotranspiration models are critical in order to understand the cycling of water in the environment. Initially, an outline of the concepts related to evapotranspiration, as well as the shortcomings of land-based methods, is presented. The aim of the study was based on reviewing remote sensing evapotranspiration models which provide an alternative data source. These models have proved to be a cheaper alternative to mapping and estimating spatiotemporal evapotranspiration measurements across local and regional scales. This paper reviews the single-source energy balance model, which differs from the two-source model, for estimating spatiotemporal measurements of evapotranspiration. The single-source energy balance model is underpinned by mathematical equations which differentiate the various single-source evapotranspiration models (Surface Energy Balance Systems, Simplified Surface Energy Systems, Surface Energy Balance Algorithm, and Mapping Evapotranspiration at high Resolution and with Internalised Calibration). The soil surface and forest canopy components were observed to be the major difference between the single and dual-source models. Further advice was discussed on the implementation of the OpenET tool, which provides an open and accessible satellite-based estimation of evapotranspiration for improved water management.
{"title":"Remote sensing-based evapotranspiration determination: A review of single-source energy balance models","authors":"Lehlohonolo Sello, Akhona Maqhubela, Gaathier Mahed","doi":"10.4314/sajg.v11i2.7","DOIUrl":"https://doi.org/10.4314/sajg.v11i2.7","url":null,"abstract":"Remote Sensing evapotranspiration models are critical in order to understand the cycling of water in the environment. Initially, an outline of the concepts related to evapotranspiration, as well as the shortcomings of land-based methods, is presented. The aim of the study was based on reviewing remote sensing evapotranspiration models which provide an alternative data source. These models have proved to be a cheaper alternative to mapping and estimating spatiotemporal evapotranspiration measurements across local and regional scales. This paper reviews the single-source energy balance model, which differs from the two-source model, for estimating spatiotemporal measurements of evapotranspiration. The single-source energy balance model is underpinned by mathematical equations which differentiate the various single-source evapotranspiration models (Surface Energy Balance Systems, Simplified Surface Energy Systems, Surface Energy Balance Algorithm, and Mapping Evapotranspiration at high Resolution and with Internalised Calibration). The soil surface and forest canopy components were observed to be the major difference between the single and dual-source models. Further advice was discussed on the implementation of the OpenET tool, which provides an open and accessible satellite-based estimation of evapotranspiration for improved water management.","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":"48609408","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 unprecedented influx of people into urban areas has led to the horizontal and vertical growth of urban environments. One of the notable impacts of urbanisation is the encroachment of urban-like environments into non-urban areas. This is common in both developed and developing countries, and South Africa’s City of Tshwane, the administrative capital of the country, has been affected by urbanisation because of migration. One of the parameters or proxies used to quantify urban growth is vegetation cover. There is a consensus that with the increase in the population of urban dwellers, vegetation cover will decrease. To assess and monitor vegetation cover, the Normalised Difference Vegetation Index (NDVI) is commonly used. In this study, MODIS NDVI data with a 250m spatial resolution was used to assess the impact of urban growth on vegetation. A time series analysis of the MODIS NDVI with a spatial resolution of 250m was used to establish the patterns of vegetation cover. Trends in vegetation change were determined in newly developed residential areas, informal settlements, and various vegetated areas. Sen's slope estimator and Mann-Kendall’s statisticwere used to analyse the spatial trends and variations in trends among different land cover classes. The slope of the trends differs significantly but there is a general decline in vegetation cover. The temporal profiles revealed the high and low NDVI values, respectively showing greening (high vegetation) and browning (low vegetation) trends from 2000 to 2016. It is concluded that urban growth has an impact on vegetation cover. However, this does not disturb the seasonal changes in vegetation where high NDVI values prevail in summer and low values in winter.
{"title":"Monitoring vegetation phenology using MODIS NDVI 250m in the City of Tshwane, South Africa","authors":"J. Magidi, Fethi Ahmed","doi":"10.4314/sajg.v11i2.1","DOIUrl":"https://doi.org/10.4314/sajg.v11i2.1","url":null,"abstract":"The unprecedented influx of people into urban areas has led to the horizontal and vertical growth of urban environments. One of the notable impacts of urbanisation is the encroachment of urban-like environments into non-urban areas. This is common in both developed and developing countries, and South Africa’s City of Tshwane, the administrative capital of the country, has been affected by urbanisation because of migration. One of the parameters or proxies used to quantify urban growth is vegetation cover. There is a consensus that with the increase in the population of urban dwellers, vegetation cover will decrease. To assess and monitor vegetation cover, the Normalised Difference Vegetation Index (NDVI) is commonly used. In this study, MODIS NDVI data with a 250m spatial resolution was used to assess the impact of urban growth on vegetation. A time series analysis of the MODIS NDVI with a spatial resolution of 250m was used to establish the patterns of vegetation cover. Trends in vegetation change were determined in newly developed residential areas, informal settlements, and various vegetated areas. Sen's slope estimator and Mann-Kendall’s statisticwere used to analyse the spatial trends and variations in trends among different land cover classes. The slope of the trends differs significantly but there is a general decline in vegetation cover. The temporal profiles revealed the high and low NDVI values, respectively showing greening (high vegetation) and browning (low vegetation) trends from 2000 to 2016. It is concluded that urban growth has an impact on vegetation cover. However, this does not disturb the seasonal changes in vegetation where high NDVI values prevail in summer and low values in winter.","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":"46651490","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}
R. Suya, Charles Kapachika, M. Soko, Vincent Luhanga, J. Ogwang, Harvey Chilembwe, Francis Gitau
Global Navigation Satellite System (GNSS) signals in the L-band are affected by the non-dispersive neutral atmosphere. Regardless of their center frequency, the L-band code and phase observations are affected by the same measure of delay. GNSS receivers play a significant role in quantifying the zenith tropospheric delay (ZTD) from satellite signals. Malawi has a Continuously Operating Reference Stations (CORS) network which was established to support research in geophysical geodesy and geodynamics. However, the quality of the observations tracked by the CORS has never been tested in terms of its meteorological application. In this paper, the ZTD estimation approach and the evaluation of results from the Global Positioning System (GPS) measurements are presented. The optimal approach of precise point positioning (PPP) was used to estimate ZTD from one-week datasets which were collected from six CORS monuments distributed in the northern and southern regions of Malawi. In addition, the zenith wet delay (ZWD) and zenith hydrostatic delay (ZHD) were also estimated to determine their respective contributions to the total delay in all the stations. Alongside the meteorological parameters, the positioning repeatabilities were also established for all stations. Results indicate that the averaged ZTD, ZWD and ZHD can reach as high as 247mm, 47 mm, and 199 mm, respectively. The minimum ZTD, ZWD, and ZHD for the stations can drop to as low as 220 mm, 24 mm, and 181 mm, respectively. This indicates that the ZHD contributes to more than 90% of the total delay at the stations. For the positioning performance, there was no obvious disparity in the latitude (less than 0.5 cm), longitude (less than 1 cm), and ellipsoidal height repeatabilities (less than 1.5 cm). Thus, the results clearly demonstrate that the Malawi CORS network may be used for GNSS-based meteorological applications using the available geodetic receivers. However, for high precision meteorological applications, Malawi may consider densifying the available network with geodetic grade receivers.
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