Multi-temporal analysis of urban land-use and land-cover patterns in Alice, Eastern Cape Province, South Africa
- Authors: Manyanye, Owen
- Date: 2017
- Subjects: Geographic information systems Land use -- Remote sensing Land cover
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10353/8066 , vital:31506
- Description: South Africa is undergoing rapid urbanization coupled with fast demographic change in the major cities and towns. This economic shift leaves behind underdevelopment, particularly in the rural areas such as the Eastern Cape Province. Underdevelopment of rural Eastern Cape can be understood by revisiting the “native reserve policy” of the Union of South Africa (1910 –1948) and the separate development policies of the apartheid government (1948 –1994). These policies have induced landlessness in the rural Eastern Cape and the destruction of rural livelihoods, poverty and under-development of roads, housing, health, education and sanitation facilities, and constrained development of a sustainable local economy. This study was aimed at determining the temporal and spatial land-use / land-cover changes in and around Alice town in the Eastern Cape Province of South Africa by using multi-date remotely Landsat TM images covering 5 time slices for the years 1984, 1989, 1994, 1999 and 2009. This was done by using supervised classification to objectively reconstruct changes in land-use and land-cover by compiling time-series maps with four information classes and using the Kappa Coefficient to assess the accuracy of all map outputs. Results of this investigation point to significant changes in land-use and land-cover over the 25-year study period between 1984 and 2009 with built-up areas expanding by 3720 hectares from 3227 hectares in 1984 to 6947 hectares in 2009. This observation is important because it enhances our understanding of the dynamics of urban growth and provides useful insights that aid urban development planning and policy formulation. The research concludes by recommending the use time series remotely sensed imagery as a decision-support tool for urban and environment management.
- Full Text:
- Authors: Manyanye, Owen
- Date: 2017
- Subjects: Geographic information systems Land use -- Remote sensing Land cover
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10353/8066 , vital:31506
- Description: South Africa is undergoing rapid urbanization coupled with fast demographic change in the major cities and towns. This economic shift leaves behind underdevelopment, particularly in the rural areas such as the Eastern Cape Province. Underdevelopment of rural Eastern Cape can be understood by revisiting the “native reserve policy” of the Union of South Africa (1910 –1948) and the separate development policies of the apartheid government (1948 –1994). These policies have induced landlessness in the rural Eastern Cape and the destruction of rural livelihoods, poverty and under-development of roads, housing, health, education and sanitation facilities, and constrained development of a sustainable local economy. This study was aimed at determining the temporal and spatial land-use / land-cover changes in and around Alice town in the Eastern Cape Province of South Africa by using multi-date remotely Landsat TM images covering 5 time slices for the years 1984, 1989, 1994, 1999 and 2009. This was done by using supervised classification to objectively reconstruct changes in land-use and land-cover by compiling time-series maps with four information classes and using the Kappa Coefficient to assess the accuracy of all map outputs. Results of this investigation point to significant changes in land-use and land-cover over the 25-year study period between 1984 and 2009 with built-up areas expanding by 3720 hectares from 3227 hectares in 1984 to 6947 hectares in 2009. This observation is important because it enhances our understanding of the dynamics of urban growth and provides useful insights that aid urban development planning and policy formulation. The research concludes by recommending the use time series remotely sensed imagery as a decision-support tool for urban and environment management.
- Full Text:
Multi-temporal assessment of spatial changes in vegetation distribution in the Swartkops estuary, Port Elizabeth, Eastern Cape, South Africa
- Authors: Atyosi, Yonwaba
- Date: 2017
- Subjects: Climatic changes -- South Africa -- Eastern Cape Environmental impact analysis Estuaries -- South Africa -- Eastern Cape
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10353/13762 , vital:39710
- Description: Over the last decade, image classification has been widely used as a change detection method and provides detailed information for detecting and monitoring changes in land use and land cover (LULC). The main objective of this study was to reconstruct long-term changes in the spatial distribution of different vegetation types in the Swartkops Estuary from 1983 to 2013. The Swartkops Estuary is ecologically important for its wide range of vegetation types that are habitat to estuarine and riverine organisms. Four Landsat images for the years 1984 (Thematic Mapper), 1993 (Thematic Mapper), 2003(Enhanced Thematic Mapper +) and 2013 (Operational Land Imager) were used with the aid of aerial photographs that were used as an ancillary data source. The research methodology comprised of supervised classification, classification accuracy assessment and image differencing. Supervised classification was performed and results of the image classification process for the four time periods were compared to derive information on changes that occurred over the 29-year study period. Images were classified into the following classes: Estuarine water, Salt works, Zostera capensis, Spartina maritima, Terrestrial vegetation, Salt marsh, Swartkops thicket, Built-up areas, Bare areas, and Beach sand, using the Maximum likelihood classifier on Erdas IMAGINE 2014 Software. The significance of the image classification was tested using linear trend regression analysis. Image differencing was performed using 1984 and 2013 Landsat images to reconstruct overall changes in vegetation distribution of the Swartkops Estuary. Results of this investigation revealed significant changes in all land cover types, 24 ha increase from 1984 to 2013 in Zostera capensis as well as Spartina maritima, salt marshes increased by 14 ha between 1984 and 2013, terrestrial vegetation declined by 18 ha between 1984 and 2013. There was a stable increase in estuarine water from 1984 to 2013 by a total area of 29 ha. Water increased by 14 ha between 1984 and 1993, 11 ha increase between 1993 and 2003. However, there was a decline in estuarine water in the period between 2003 and 2013.This decline is associated with the increase in submerged macrophytes like Zostera capensis which utilise open water habitat. The dominant salt marsh species Limonium peregrinum, Sarcoconia pillansii and Spartina maritima occurred in the intertidal, supratidal and floodplain areas where the water table was the shallowest, with the soil moisture being the highest. These results indicate that Remote Sensing and GIS can be effectively used to detect and monitor changes in estuarine biodiversity and habitat in South Africa.
- Full Text:
- Authors: Atyosi, Yonwaba
- Date: 2017
- Subjects: Climatic changes -- South Africa -- Eastern Cape Environmental impact analysis Estuaries -- South Africa -- Eastern Cape
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10353/13762 , vital:39710
- Description: Over the last decade, image classification has been widely used as a change detection method and provides detailed information for detecting and monitoring changes in land use and land cover (LULC). The main objective of this study was to reconstruct long-term changes in the spatial distribution of different vegetation types in the Swartkops Estuary from 1983 to 2013. The Swartkops Estuary is ecologically important for its wide range of vegetation types that are habitat to estuarine and riverine organisms. Four Landsat images for the years 1984 (Thematic Mapper), 1993 (Thematic Mapper), 2003(Enhanced Thematic Mapper +) and 2013 (Operational Land Imager) were used with the aid of aerial photographs that were used as an ancillary data source. The research methodology comprised of supervised classification, classification accuracy assessment and image differencing. Supervised classification was performed and results of the image classification process for the four time periods were compared to derive information on changes that occurred over the 29-year study period. Images were classified into the following classes: Estuarine water, Salt works, Zostera capensis, Spartina maritima, Terrestrial vegetation, Salt marsh, Swartkops thicket, Built-up areas, Bare areas, and Beach sand, using the Maximum likelihood classifier on Erdas IMAGINE 2014 Software. The significance of the image classification was tested using linear trend regression analysis. Image differencing was performed using 1984 and 2013 Landsat images to reconstruct overall changes in vegetation distribution of the Swartkops Estuary. Results of this investigation revealed significant changes in all land cover types, 24 ha increase from 1984 to 2013 in Zostera capensis as well as Spartina maritima, salt marshes increased by 14 ha between 1984 and 2013, terrestrial vegetation declined by 18 ha between 1984 and 2013. There was a stable increase in estuarine water from 1984 to 2013 by a total area of 29 ha. Water increased by 14 ha between 1984 and 1993, 11 ha increase between 1993 and 2003. However, there was a decline in estuarine water in the period between 2003 and 2013.This decline is associated with the increase in submerged macrophytes like Zostera capensis which utilise open water habitat. The dominant salt marsh species Limonium peregrinum, Sarcoconia pillansii and Spartina maritima occurred in the intertidal, supratidal and floodplain areas where the water table was the shallowest, with the soil moisture being the highest. These results indicate that Remote Sensing and GIS can be effectively used to detect and monitor changes in estuarine biodiversity and habitat in South Africa.
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Using GIS and remote sensing to map suitable sites for wind farms: a case study of Nkonkobe Municipality, Eastern Cape.
- Authors: Gwena, Jay
- Date: 2015
- Subjects: Geographic information systems http://id.loc.gov/authorities/subjects/sh90001880 , Remote sensing http://id.loc.gov/authorities/subjects/sh85112798 , Renewable energy sources http://id.loc.gov/authorities/subjects/sh85112837
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10353/19420 , vital:43082
- Description: Issues relating to energy use, renewable energy introduction and climate change have received a lot of attention from governments throughout the world in the past two decades. Many developing nations like South Africa heavily rely on coal and other non-renewable resources for their production of energy. The processing of the non-renewable resources into secondary energy forms is according to many energy experts a chief contributor to climate change. Climate change is affecting agricultural production in many developing countries that entirely rely on rainfall for their production. The loss in production in South Africa is increasing the level of poverty in low-income earners and unemployed people. Also a lot of households found in rural areas of South Africa have no access to electricity. Electricity in South Africa is generated and distributed by Eskom a state owned company. In April 2008 Eskom failed to meet power demand and started introducing load shedding to maintain and upgrade their power plants. The load shedding stopped for while and was introduced again in 2014 when the power utility faced the challenge of failing to produce power to meet demand again due to problems with their power stations. The ongoing energy provision problems in South Africa can be alleviated by introducing alternative sources like renewable energy. Introduction of renewable energy in poorly developed areas like Nkonkobe Municipality can help households‘ access electricity and reduce load on the national grid. The aim of this study was to locate suitable sites for setting up wind farms in Nkonkobe municipality in South Africa. Wind energy as a resource is abundant in many areas of South Africa and areas to set wind farms for optimum harness of wind power were identified using GIS, remote sensing and multi-criteria decision making techniques. Wind speed, distance from settlements, distance from main roads, distance from national, slope and land use/land cover were chosen as the factors to consider in selecting a suitable site. Data was collected from South Africa Weather Services, University of Fort Hare and online free data sources. Thematic maps for all the factors were developed in ArcGIS and fed into Nkonkobe Municipality database developed for the study. Thematic maps were assigned weights before being overlaid using weighted overlay tool. Weights for the factors were determined using Analytical hierarchy Process‘ pairwise comparison approach. Weighted overlay of the thematic maps produced a map showing suitable areas based on the weight influence of each factor. The output map was compared to results obtained from using Boolean approach and weighted sum method as a way of checking the accuracy of obtained suitable sites. Results showed there are three sites that can be used for setting up wind farms in the study area. , Thesis (MSc) (Applied Remote Sensing and GIS) -- University of Fort Hare, 2015
- Full Text:
- Authors: Gwena, Jay
- Date: 2015
- Subjects: Geographic information systems http://id.loc.gov/authorities/subjects/sh90001880 , Remote sensing http://id.loc.gov/authorities/subjects/sh85112798 , Renewable energy sources http://id.loc.gov/authorities/subjects/sh85112837
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10353/19420 , vital:43082
- Description: Issues relating to energy use, renewable energy introduction and climate change have received a lot of attention from governments throughout the world in the past two decades. Many developing nations like South Africa heavily rely on coal and other non-renewable resources for their production of energy. The processing of the non-renewable resources into secondary energy forms is according to many energy experts a chief contributor to climate change. Climate change is affecting agricultural production in many developing countries that entirely rely on rainfall for their production. The loss in production in South Africa is increasing the level of poverty in low-income earners and unemployed people. Also a lot of households found in rural areas of South Africa have no access to electricity. Electricity in South Africa is generated and distributed by Eskom a state owned company. In April 2008 Eskom failed to meet power demand and started introducing load shedding to maintain and upgrade their power plants. The load shedding stopped for while and was introduced again in 2014 when the power utility faced the challenge of failing to produce power to meet demand again due to problems with their power stations. The ongoing energy provision problems in South Africa can be alleviated by introducing alternative sources like renewable energy. Introduction of renewable energy in poorly developed areas like Nkonkobe Municipality can help households‘ access electricity and reduce load on the national grid. The aim of this study was to locate suitable sites for setting up wind farms in Nkonkobe municipality in South Africa. Wind energy as a resource is abundant in many areas of South Africa and areas to set wind farms for optimum harness of wind power were identified using GIS, remote sensing and multi-criteria decision making techniques. Wind speed, distance from settlements, distance from main roads, distance from national, slope and land use/land cover were chosen as the factors to consider in selecting a suitable site. Data was collected from South Africa Weather Services, University of Fort Hare and online free data sources. Thematic maps for all the factors were developed in ArcGIS and fed into Nkonkobe Municipality database developed for the study. Thematic maps were assigned weights before being overlaid using weighted overlay tool. Weights for the factors were determined using Analytical hierarchy Process‘ pairwise comparison approach. Weighted overlay of the thematic maps produced a map showing suitable areas based on the weight influence of each factor. The output map was compared to results obtained from using Boolean approach and weighted sum method as a way of checking the accuracy of obtained suitable sites. Results showed there are three sites that can be used for setting up wind farms in the study area. , Thesis (MSc) (Applied Remote Sensing and GIS) -- University of Fort Hare, 2015
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