Urbanization is one of the most impactful human activities across the world today affecting the quality of urban life and its sustainable development.Urbanization in Africa is occurring at an unprecedented rate and it...Urbanization is one of the most impactful human activities across the world today affecting the quality of urban life and its sustainable development.Urbanization in Africa is occurring at an unprecedented rate and it threatens the attainment of Sustainable Development Goals(SDGs).Urban sprawl has resulted in unsustainable urban development patterns from social,environmental,and economic perspectives.This study is among the first examples of research in Africa to combine remote sensing data with social media data to determine urban sprawl from 2011 to 2017 in Morogoro urban municipality,Tanzania.Random Forest(RF)method was applied to accomplish imagery classification and location-based social media(Twitter usage)data were obtained through a Twitter Application Programming Interface(API).Morogoro urban municipality was classified into built-up,vegetation,agriculture,and water land cover classes while the classification results were validated by the generation of 480 random points.Using the Kernel function,the study measured the location of Twitter users within a 1 km buffer from the center of the city.The results indicate that,expansion of the city(built-up land use),which is primarily driven by population expansion,has negative impacts on ecosystem services because pristine grasslands and forests which provide essential ecosystem services such as carbon sequestration and support for biodiversity have been replaced by built-up land cover.In addition,social media usage data suggest that there is the concentration of Twitter usage within the city center while Twitter usage declines away from the city center with significant spatial and numerical increase in Twitter usage in the study area.The outcome of the study suggests that the combination of remote sensing,social sensing,and population data were useful as a proxy/inference for interpreting urban sprawl and status of access to urban services and infrastructure in Morogoro,and Africa city where data for urban planning is often unavailable,inaccurate,or stale.展开更多
The discovery of oil and gas in Uganda has attracted many investors, leading to increase in fuel/gas distributing companies and fueling stations creating rapid demand for land to locate the stations compared to availa...The discovery of oil and gas in Uganda has attracted many investors, leading to increase in fuel/gas distributing companies and fueling stations creating rapid demand for land to locate the stations compared to available open urban land. Because of the explosive and combustion characteristics of fuel stored and dispensed at stations, several studies have been conducted on different fires at fueling stations such as static fire, jet fire, vapor cloud explosions, open fires, etc. but there was need to assess spatially the risk of fire from stations, its consequences and sovereignty on buildings surrounding them. This was done basing on seven parameters—proximity of buildings to stations, building materials, distance between buildings, wind speed, temperature, slope and vegetation. Analytical hierarchy process and pairwise comparison were used to weight the parameters based on their relative importance. Weighted sum tool was applied to generate the fire risk maps for the quarters—December to February, March to May, June to August, and September to November from 2008 to 2013. The parameters were overlaid with the buildings in each risk zone for all the four quarters and their influences determined. The highest contributors were proximity of the buildings to stations, building materials and separation between buildings. Most of the affected buildings were made of rusted corrugated iron sheets and wood;the separation distance from one building to another ranged from 0 - 4 m. Most of buildings located within 100 m from stations were at moderate risk level and within 50 m were at highest risk level. The period of December to February and June to August had the highest risk. The findings can be used to guide planners and policy makers on building location vs. material vs. separation. It can also guide developers on where, when and how to carry out their developments.展开更多
Estimating magnetic properties of water samples by first measuring the Anhysteretic Remanent Magnetization (ARM) before Isothermal Remanent Magnetization (IRM) is induced has been costly due to the discard of samples ...Estimating magnetic properties of water samples by first measuring the Anhysteretic Remanent Magnetization (ARM) before Isothermal Remanent Magnetization (IRM) is induced has been costly due to the discard of samples measured by staring with the latter before the former. However, no clear understanding exists on the effect of measuring magnetic properties values by first inducing IRM before ARM. This study explored the effect of measuring concentration related parameters (χlf, χfd and χARM), a mineral related parameter (S-300) and grain size parameters (χfd% and χARM/SIRM ratio) fromwater samples by starting with IRM before ARM. Forty three surface water samples were collected from the estuarine of Yangtze River (China) with the aim of measuring magnetic characteristics by starting with IRM before ARM. The results indicated that, measuring magnetic properties by either starting with ARM or IRM led to similar values for χlf, χfd, χfd%, χARM, S-300 and χARM/SIRM ratio (p > 0.05). These results imply that, measuring concentrationrelated parameters does not necessarily require measuring ARM first and then IRM. Researchers can start by measuring any parameter between ARM and IRM without affecting the final results of the water samples, but with proper demagnetization when started with IRM.展开更多
基金This work is supported by the National Natural Science Foundation of China[Grants Number 41771452,41771454 and 41890820]the Natural Science Fund of Hubei Province in China[Grant Number 2018CFA007].
文摘Urbanization is one of the most impactful human activities across the world today affecting the quality of urban life and its sustainable development.Urbanization in Africa is occurring at an unprecedented rate and it threatens the attainment of Sustainable Development Goals(SDGs).Urban sprawl has resulted in unsustainable urban development patterns from social,environmental,and economic perspectives.This study is among the first examples of research in Africa to combine remote sensing data with social media data to determine urban sprawl from 2011 to 2017 in Morogoro urban municipality,Tanzania.Random Forest(RF)method was applied to accomplish imagery classification and location-based social media(Twitter usage)data were obtained through a Twitter Application Programming Interface(API).Morogoro urban municipality was classified into built-up,vegetation,agriculture,and water land cover classes while the classification results were validated by the generation of 480 random points.Using the Kernel function,the study measured the location of Twitter users within a 1 km buffer from the center of the city.The results indicate that,expansion of the city(built-up land use),which is primarily driven by population expansion,has negative impacts on ecosystem services because pristine grasslands and forests which provide essential ecosystem services such as carbon sequestration and support for biodiversity have been replaced by built-up land cover.In addition,social media usage data suggest that there is the concentration of Twitter usage within the city center while Twitter usage declines away from the city center with significant spatial and numerical increase in Twitter usage in the study area.The outcome of the study suggests that the combination of remote sensing,social sensing,and population data were useful as a proxy/inference for interpreting urban sprawl and status of access to urban services and infrastructure in Morogoro,and Africa city where data for urban planning is often unavailable,inaccurate,or stale.
文摘The discovery of oil and gas in Uganda has attracted many investors, leading to increase in fuel/gas distributing companies and fueling stations creating rapid demand for land to locate the stations compared to available open urban land. Because of the explosive and combustion characteristics of fuel stored and dispensed at stations, several studies have been conducted on different fires at fueling stations such as static fire, jet fire, vapor cloud explosions, open fires, etc. but there was need to assess spatially the risk of fire from stations, its consequences and sovereignty on buildings surrounding them. This was done basing on seven parameters—proximity of buildings to stations, building materials, distance between buildings, wind speed, temperature, slope and vegetation. Analytical hierarchy process and pairwise comparison were used to weight the parameters based on their relative importance. Weighted sum tool was applied to generate the fire risk maps for the quarters—December to February, March to May, June to August, and September to November from 2008 to 2013. The parameters were overlaid with the buildings in each risk zone for all the four quarters and their influences determined. The highest contributors were proximity of the buildings to stations, building materials and separation between buildings. Most of the affected buildings were made of rusted corrugated iron sheets and wood;the separation distance from one building to another ranged from 0 - 4 m. Most of buildings located within 100 m from stations were at moderate risk level and within 50 m were at highest risk level. The period of December to February and June to August had the highest risk. The findings can be used to guide planners and policy makers on building location vs. material vs. separation. It can also guide developers on where, when and how to carry out their developments.
文摘Estimating magnetic properties of water samples by first measuring the Anhysteretic Remanent Magnetization (ARM) before Isothermal Remanent Magnetization (IRM) is induced has been costly due to the discard of samples measured by staring with the latter before the former. However, no clear understanding exists on the effect of measuring magnetic properties values by first inducing IRM before ARM. This study explored the effect of measuring concentration related parameters (χlf, χfd and χARM), a mineral related parameter (S-300) and grain size parameters (χfd% and χARM/SIRM ratio) fromwater samples by starting with IRM before ARM. Forty three surface water samples were collected from the estuarine of Yangtze River (China) with the aim of measuring magnetic characteristics by starting with IRM before ARM. The results indicated that, measuring magnetic properties by either starting with ARM or IRM led to similar values for χlf, χfd, χfd%, χARM, S-300 and χARM/SIRM ratio (p > 0.05). These results imply that, measuring concentrationrelated parameters does not necessarily require measuring ARM first and then IRM. Researchers can start by measuring any parameter between ARM and IRM without affecting the final results of the water samples, but with proper demagnetization when started with IRM.
