The Journal of Engineering and Exact Sciences, 2024
The dynamics of agricultural land change in peri-urban areas are critical due to their significan... more The dynamics of agricultural land change in peri-urban areas are critical due to their significant impacts on agricultural productivity, food security, sustainable development, and socio-economic dynamics. These intricate processes require a robust methodological approach that can effectively identify, quantify, and analyze the drivers behind land-use changes. In the peri-urban areas of Oran, Algeria, the rapid conversion of agricultural land, particularly along the main highways in the south and southwest regions, underscores the urgent need for focused research. This study aims to map and analyze agricultural land changes between 1998 and 2019, exploring the underlying factors contributing to these shifts. Employing a mixed methods approach, the study integrates both quantitative and qualitative data to provide a comprehensive understanding of the phenomenon. The methodology encompasses five main tasks:(1) data collection and identification of significant temporal markers,(2) implementation of a Random Forest classification using medium resolution Landsat imagery,(3) assessment of the extent and patterns of agricultural land changes,(4) Evaluation of relevant planning documents,(5) field work, including stakeholders interviews and focus groups. The results reveal a persistent increase in built-up areas over the study period, leading to a corresponding decline in agricultural land. This pattern highlights emerging land-use conflicts among stakeholders. The study offers valuable insights for policymakers, suggesting strategies for more effective land use management, and the promotion of sustainable agricultural practices.
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
Land cover mapping is essential for various applications, and the integration of satellite imager... more Land cover mapping is essential for various applications, and the integration of satellite imagery and deep learning techniques offers an accurate and efficient solution. This study focuses on mapping land cover and change detection in the new extensions of Greater Cairo, Egypt, using Sentinel-2 imagery and convolutional neural networks (CNNs). The CNN model was trained on the BigEarthNet dataset, and transfer learning was applied using a pre-trained U-Net model. The results reveal significant land cover changes in Greater Cairo, particularly in the eastern region due to the construction of the New Administrative Capital. The accuracy assessment metrics, including precision, recall, and F1-score, demonstrate high accuracy levels exceeding 90%. These findings contribute to the advancement of land cover mapping and its applications in urban development.
Journal of Social Transformation and Regional Development
This research seeks to identify the land use dynamic phenomenon in the unplanned settlements in G... more This research seeks to identify the land use dynamic phenomenon in the unplanned settlements in Greater Cairo Metropolitan region (GMCR) which embodied in the alternative use of space (AUS). This phenomenon represents the way for the poor communities to meet their needs of space for living, working, and entertainment purposes for free or for low costs. It is considered the first research which included clarification for this phenomenon although the main role of AUS to meet the poor communities needs of lands in GCMR. By field survey and direct interviews with users and surrounding residents we have identified AUS types, times of use and Frequency for each type in addition to impacts of it on the prices of essential needs. Based on the goals of urban sustainability we have identified positive and negative aspects of AUS on our case study district. AUS provide lands for various needs of essential activities in free or low-cost rent which reduced the price of essential needs to 13 time...
Natural disasters cause extensive economic losses every year. Rapid detection of earthquake-induc... more Natural disasters cause extensive economic losses every year. Rapid detection of earthquake-induced building damages is crucial for disaster response. Remote sensing (RS) has been widely used to assess the impacts of natural disasters i.e. earthquakes and its implications on building damages. Deep Learning (DL) techniques have become increasingly popular for detecting building damages from RS data and have achieved significant success in detecting disaster implications. This paper examines the ability of DL to detect building damages caused by Kumamoto earthquake in Mashiki town, Japan using RS data. The findings indicate that the newly trained model demonstrated effective performance in discriminating between different levels of building damages, including no damage, damage, and collapse. 1
IEEE International Geoscience and Remote Sensing Symposium, 2023
Land cover mapping is essential for various applications, and the integration of satellite imager... more Land cover mapping is essential for various applications, and the integration of satellite imagery and deep learning techniques offers an accurate and efficient solution. This study focuses on mapping land cover and change detection in the new extensions of Greater Cairo, Egypt, using Sentinel-2 imagery and convolutional neural networks (CNNs). The CNN model was trained on the BigEarthNet dataset, and transfer learning was applied using a pre-trained U-Net model. The results reveal significant land cover changes in Greater Cairo, particularly in the eastern region due to the construction of the New Administrative Capital. The accuracy assessment metrics, including precision, recall, and F1-score, demonstrate high accuracy levels exceeding 90%. These findings contribute to the advancement of land cover mapping and its applications in urban development.
ABSTRACT Land use/land cover (LULC) has changed dramatically in the peri-urban area (PUA) of grea... more ABSTRACT Land use/land cover (LULC) has changed dramatically in the peri-urban area (PUA) of greater Cairo (GC) since the Egyptian revolution of 2011. This study analyzes LULC change in the PUA of GC using two Landsat images from 2010 and 2018. The spatial trends of LULC change and visualizations of the gains and losses in LULC were analyzed using TerrSet software. The driving forces of LULC change from 2010–2018 were quantified using the logistic regression model (LRM). The results revealed that the processes of LULC change and urban sprawl have directly impacted the natural resources, particularly agricultural land. In addition, the study showed that the population growth and land value have the highest regression coefficients, 0.660 and 0.292, respectively, and were the most significant driving forces of LULC from 2010–2018. The outcomes of this study are important for decision-makers to adopt appropriate strategies for sustainable land use in this area.
International Journal of Sustainable Development and Planning
During the last few decades, sustainable development (SD) has increasingly received attention glo... more During the last few decades, sustainable development (SD) has increasingly received attention globally. Therefore, international organizations and researchers sought to assess progress towards SD at different territorial levels. However, most of the studies were conducted at the city level and a very small number of studies has conducted at the urban periphery territory. This study aims to fill the current research gap through assessing the progress towards SD in the urban periphery of Greater Cairo (GC) in Egypt between 1996-2017. Eight composite indicators have been employed to assess the progress towards SD in this territory. These composite indicators were constructed based on the 14 individual indicators associated with sustainable development goals. The results showed meaningful progress achieved in the peripheral municipalities of GC, particularly in infrastructure and education indicators, while the economic and environmental indicators have deteriorated, particularly after ...
The peri-urban area (PUA) of the Greater Cairo Region (GCR) in Egypt has witnessed a rapid urban ... more The peri-urban area (PUA) of the Greater Cairo Region (GCR) in Egypt has witnessed a rapid urban expansion during the last few years. This urban expansion has led to the loss of wide, areas of agriculture lands and the annexation of many peripheral villages into the boundary of the GCR. This study analyzed the driving factors causing the urban expansion in the GCR during the period 2007–2017 using the logistic regression model (LRM). Eight independent variables were applied in this model: distance to the nearest urban center, distance to the nearest center of regional services, distance to water streams, distance to the main agglomeration, distance to industrial areas, distance to nearest road, number of urban cells within a 3 × 3 cell window and population density. The analysis was conducted using LOGISTICREG module in Terrset software. This research showed that the population density and distance to the nearest road have the highest regression coefficients, 0.540 and 0.114, respec...
Sustainable development (SD) has become a crucial challenge globally, particularly in developing ... more Sustainable development (SD) has become a crucial challenge globally, particularly in developing countries and cities. SD of peri-urban areas (PUA) has been tackled by a limited number of studies, unlike that of urban areas or cities. The PUAs of Greater Cairo (GC) are no exception; no study had addressed the state of the PUAs in terms of SD. Thus, this study sought to measure and evaluate the progress towards the SD in the PUAs of Greater Cairo, Egypt. Thirteen indicators were extracted from selected documents of the competent international organizations to measure and evaluate the performance of SD in the study area. The study resulted in a variety of charts and maps to explain the progress of SD in each municipality of the PUAs and then classify these municipalities based on their performance in sustainability indicators. The results revealed a wide gap between PUAs’ municipalities and the urban core of Greater Cairo. These results can help urban planners and decision-makers to b...
World Academy of Science, Engineering and Technology, International Journal of Transport and Vehicle Engineering, 2017
One of the most risky areas in Aswan is Abouelreesh, which is suffering from flood disasters, as ... more One of the most risky areas in Aswan is Abouelreesh, which is suffering from flood disasters, as heavy deluge inundates urban areas causing considerable damage to buildings and infrastructure. Moreover, the main problem was the urban sprawl towards this risky area. This paper aims to identify the urban areas located in the risk areas prone to flash floods. Analyzing this phenomenon needs a lot of data to ensure satisfactory results; however, in this case the official data and field data were limited, and therefore, free sources of satellite data were used. This paper used ArcGIS tools to obtain the storm water drains network by analyzing DEM files. Additionally, historical imagery in Google Earth was studied to determine the age of each building. The last step was to overlay the urban area layer and the storm water drains layer to identify the vulnerable areas. The results of this study would be helpful to urban planners and government officials to make the disasters risk estimation...
The Journal of Engineering and Exact Sciences, 2024
The dynamics of agricultural land change in peri-urban areas are critical due to their significan... more The dynamics of agricultural land change in peri-urban areas are critical due to their significant impacts on agricultural productivity, food security, sustainable development, and socio-economic dynamics. These intricate processes require a robust methodological approach that can effectively identify, quantify, and analyze the drivers behind land-use changes. In the peri-urban areas of Oran, Algeria, the rapid conversion of agricultural land, particularly along the main highways in the south and southwest regions, underscores the urgent need for focused research. This study aims to map and analyze agricultural land changes between 1998 and 2019, exploring the underlying factors contributing to these shifts. Employing a mixed methods approach, the study integrates both quantitative and qualitative data to provide a comprehensive understanding of the phenomenon. The methodology encompasses five main tasks:(1) data collection and identification of significant temporal markers,(2) implementation of a Random Forest classification using medium resolution Landsat imagery,(3) assessment of the extent and patterns of agricultural land changes,(4) Evaluation of relevant planning documents,(5) field work, including stakeholders interviews and focus groups. The results reveal a persistent increase in built-up areas over the study period, leading to a corresponding decline in agricultural land. This pattern highlights emerging land-use conflicts among stakeholders. The study offers valuable insights for policymakers, suggesting strategies for more effective land use management, and the promotion of sustainable agricultural practices.
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
Land cover mapping is essential for various applications, and the integration of satellite imager... more Land cover mapping is essential for various applications, and the integration of satellite imagery and deep learning techniques offers an accurate and efficient solution. This study focuses on mapping land cover and change detection in the new extensions of Greater Cairo, Egypt, using Sentinel-2 imagery and convolutional neural networks (CNNs). The CNN model was trained on the BigEarthNet dataset, and transfer learning was applied using a pre-trained U-Net model. The results reveal significant land cover changes in Greater Cairo, particularly in the eastern region due to the construction of the New Administrative Capital. The accuracy assessment metrics, including precision, recall, and F1-score, demonstrate high accuracy levels exceeding 90%. These findings contribute to the advancement of land cover mapping and its applications in urban development.
Journal of Social Transformation and Regional Development
This research seeks to identify the land use dynamic phenomenon in the unplanned settlements in G... more This research seeks to identify the land use dynamic phenomenon in the unplanned settlements in Greater Cairo Metropolitan region (GMCR) which embodied in the alternative use of space (AUS). This phenomenon represents the way for the poor communities to meet their needs of space for living, working, and entertainment purposes for free or for low costs. It is considered the first research which included clarification for this phenomenon although the main role of AUS to meet the poor communities needs of lands in GCMR. By field survey and direct interviews with users and surrounding residents we have identified AUS types, times of use and Frequency for each type in addition to impacts of it on the prices of essential needs. Based on the goals of urban sustainability we have identified positive and negative aspects of AUS on our case study district. AUS provide lands for various needs of essential activities in free or low-cost rent which reduced the price of essential needs to 13 time...
Natural disasters cause extensive economic losses every year. Rapid detection of earthquake-induc... more Natural disasters cause extensive economic losses every year. Rapid detection of earthquake-induced building damages is crucial for disaster response. Remote sensing (RS) has been widely used to assess the impacts of natural disasters i.e. earthquakes and its implications on building damages. Deep Learning (DL) techniques have become increasingly popular for detecting building damages from RS data and have achieved significant success in detecting disaster implications. This paper examines the ability of DL to detect building damages caused by Kumamoto earthquake in Mashiki town, Japan using RS data. The findings indicate that the newly trained model demonstrated effective performance in discriminating between different levels of building damages, including no damage, damage, and collapse. 1
IEEE International Geoscience and Remote Sensing Symposium, 2023
Land cover mapping is essential for various applications, and the integration of satellite imager... more Land cover mapping is essential for various applications, and the integration of satellite imagery and deep learning techniques offers an accurate and efficient solution. This study focuses on mapping land cover and change detection in the new extensions of Greater Cairo, Egypt, using Sentinel-2 imagery and convolutional neural networks (CNNs). The CNN model was trained on the BigEarthNet dataset, and transfer learning was applied using a pre-trained U-Net model. The results reveal significant land cover changes in Greater Cairo, particularly in the eastern region due to the construction of the New Administrative Capital. The accuracy assessment metrics, including precision, recall, and F1-score, demonstrate high accuracy levels exceeding 90%. These findings contribute to the advancement of land cover mapping and its applications in urban development.
ABSTRACT Land use/land cover (LULC) has changed dramatically in the peri-urban area (PUA) of grea... more ABSTRACT Land use/land cover (LULC) has changed dramatically in the peri-urban area (PUA) of greater Cairo (GC) since the Egyptian revolution of 2011. This study analyzes LULC change in the PUA of GC using two Landsat images from 2010 and 2018. The spatial trends of LULC change and visualizations of the gains and losses in LULC were analyzed using TerrSet software. The driving forces of LULC change from 2010–2018 were quantified using the logistic regression model (LRM). The results revealed that the processes of LULC change and urban sprawl have directly impacted the natural resources, particularly agricultural land. In addition, the study showed that the population growth and land value have the highest regression coefficients, 0.660 and 0.292, respectively, and were the most significant driving forces of LULC from 2010–2018. The outcomes of this study are important for decision-makers to adopt appropriate strategies for sustainable land use in this area.
International Journal of Sustainable Development and Planning
During the last few decades, sustainable development (SD) has increasingly received attention glo... more During the last few decades, sustainable development (SD) has increasingly received attention globally. Therefore, international organizations and researchers sought to assess progress towards SD at different territorial levels. However, most of the studies were conducted at the city level and a very small number of studies has conducted at the urban periphery territory. This study aims to fill the current research gap through assessing the progress towards SD in the urban periphery of Greater Cairo (GC) in Egypt between 1996-2017. Eight composite indicators have been employed to assess the progress towards SD in this territory. These composite indicators were constructed based on the 14 individual indicators associated with sustainable development goals. The results showed meaningful progress achieved in the peripheral municipalities of GC, particularly in infrastructure and education indicators, while the economic and environmental indicators have deteriorated, particularly after ...
The peri-urban area (PUA) of the Greater Cairo Region (GCR) in Egypt has witnessed a rapid urban ... more The peri-urban area (PUA) of the Greater Cairo Region (GCR) in Egypt has witnessed a rapid urban expansion during the last few years. This urban expansion has led to the loss of wide, areas of agriculture lands and the annexation of many peripheral villages into the boundary of the GCR. This study analyzed the driving factors causing the urban expansion in the GCR during the period 2007–2017 using the logistic regression model (LRM). Eight independent variables were applied in this model: distance to the nearest urban center, distance to the nearest center of regional services, distance to water streams, distance to the main agglomeration, distance to industrial areas, distance to nearest road, number of urban cells within a 3 × 3 cell window and population density. The analysis was conducted using LOGISTICREG module in Terrset software. This research showed that the population density and distance to the nearest road have the highest regression coefficients, 0.540 and 0.114, respec...
Sustainable development (SD) has become a crucial challenge globally, particularly in developing ... more Sustainable development (SD) has become a crucial challenge globally, particularly in developing countries and cities. SD of peri-urban areas (PUA) has been tackled by a limited number of studies, unlike that of urban areas or cities. The PUAs of Greater Cairo (GC) are no exception; no study had addressed the state of the PUAs in terms of SD. Thus, this study sought to measure and evaluate the progress towards the SD in the PUAs of Greater Cairo, Egypt. Thirteen indicators were extracted from selected documents of the competent international organizations to measure and evaluate the performance of SD in the study area. The study resulted in a variety of charts and maps to explain the progress of SD in each municipality of the PUAs and then classify these municipalities based on their performance in sustainability indicators. The results revealed a wide gap between PUAs’ municipalities and the urban core of Greater Cairo. These results can help urban planners and decision-makers to b...
World Academy of Science, Engineering and Technology, International Journal of Transport and Vehicle Engineering, 2017
One of the most risky areas in Aswan is Abouelreesh, which is suffering from flood disasters, as ... more One of the most risky areas in Aswan is Abouelreesh, which is suffering from flood disasters, as heavy deluge inundates urban areas causing considerable damage to buildings and infrastructure. Moreover, the main problem was the urban sprawl towards this risky area. This paper aims to identify the urban areas located in the risk areas prone to flash floods. Analyzing this phenomenon needs a lot of data to ensure satisfactory results; however, in this case the official data and field data were limited, and therefore, free sources of satellite data were used. This paper used ArcGIS tools to obtain the storm water drains network by analyzing DEM files. Additionally, historical imagery in Google Earth was studied to determine the age of each building. The last step was to overlay the urban area layer and the storm water drains layer to identify the vulnerable areas. The results of this study would be helpful to urban planners and government officials to make the disasters risk estimation...
This book chapter aims to investigate the urban landscape in the peri-urban area (PUA) of Greater... more This book chapter aims to investigate the urban landscape in the peri-urban area (PUA) of Greater Cairo (GC), Egypt by exploring the driving factors contributing to uncontrolled growth, assessing the impacts of urban sprawl on the landscape, and analyzing the resulting urban growth patterns. To achieve this, remote sensing and geospatial analysis were utilized to explore the urban sprawl and landscape structure in the PUA of GC from 2000 to 2020. The study revealed that modifications in land use/cover have resulted in the loss of 51,660 hectares of arable land, leading to a detrimental effect on natural resources. The landscape expansion index revealed that edge expansion was the predominant type of urban expansion. Moreover, geospatial metrics showed that the study area was characterized by landscape fragmentation. The findings of this study provide valuable insights for policymakers, urban planners, and researchers interested in promoting sustainable urban development in the PUA.
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Papers by Muhammad Salem