John Namwamba | Southern University (original) (raw)

Papers by John Namwamba

The Egyptian Journal of Remote Sensing and Space Science, 2018

The Kondapalli reserve forest (KRF) of the Eastern Ghats, India is subjected to severe anthropoge... more The Kondapalli reserve forest (KRF) of the Eastern Ghats, India is subjected to severe anthropogenic interference, despite its status as reserve forest. The present research focuses on assessing the land use and land cover changes in and around KRF using temporal satellite data. It is evident from the current study that there has been a considerable decrease in the forest cover from 1990 to 2015; as seen from 2017 data, huge urban expansions and development activities were observed around KRF. This increase is linked to the growth in population, thereby consuming land available for their basic needs. To assess the rate of urban expansion around the forest, Land consumption rate and Land absorption coefficient were computed. The result of this analysis showed a rapid growth in built-up land between 1990 and 2017 while the periods between 1990 and 2015 witnessed a reduction in the forest class. Further, the study projected adverse impact of the growth of the new capital city-Amaravati on the KRF and proposed requiring suitable conservation measures with respect to its current deforestation and degradation trends.

Journal of Sustainable Bioenergy Systems

Rising greenhouse gas emissions are causing climate change, and the world's focus has... more Rising greenhouse gas emissions are causing climate change, and the world's focus has shifted to the need to reduce our reliance on fossil fuels. There has been a rise in the published literature on the utilization of crops for bioenergy production in Louisiana. However, very few scholarly documents have used Geographic Information Systems (GIS) to map the distribution of potential bioenergy crops in Louisiana. This study seeks to fill the void by evaluating the potential of bioenergy crops in Louisiana for energy production using GIS. Given this objective, the agricultural census data for 1999, 2009, 2019, and 2020 obtained from the U.S. Department of Agriculture were used in the analysis. The quantities of various crops produced in the state were loaded into an attribute table and joined to a shapefile using ArcGIS software. The symbology tool's graduated option was used to create five maps representing each of the bioenergy crops in Louisiana. The findings of the GIS analysis show that some of the parishes, such as Franklin produced the most bushels of corn (13,795,416), Iberia produced the most tons of sugarcane (1,697,980), East Carroll produced the most bushels of soybean (8,237,991), Tensas harvested the most bales of cotton (80,898) and Avoyelles produced the most bushels of sorghum (630,694). The abundance and availability of crops as raw materials for energy production will translate into lower prices in terms of energy use, making bioenergy crops a promising alternative to fossil fuels. In addition, gasoline price data from 1993-2022 was obtained from U.S. Energy Information Administration. A regression model for the average annual gasoline price over the years was constructed. The results show that the average How to cite this paper: Twumasi, Y.A.,

Advances in Remote Sensing, 2022

that the NDWI is higher for flood areas and lower for non-flooded ones. The ETS algorithm results... more that the NDWI is higher for flood areas and lower for non-flooded ones. The ETS algorithm results indicate that the population of Mozambique would nearly double by 2047. Human population along the coastal zone in the country is also on the rise exponentially. The paper concludes by outlining policy recommendations in the form of uniform distribution of economic activities across the country and prohibition of inland migration to the coastal areas where tropical cyclonic activities are very high.

Journal of Geographic Information System

A detailed study is presented of the expected performance of the ATLAS detector. The reconstructi... more A detailed study is presented of the expected performance of the ATLAS detector. The reconstruction of tracks, leptons, photons, missing energy and jets is investigated, together with the performance of b-tagging and the trigger. The physics potential for a variety of interesting physics processes, within the Standard Model and beyond, is examined. The study comprises a series of notes based on simulations of the detector and physics processes, with particular emphasis given to the data expected from the first years of operation of the LHC at CERN.

Advances in Remote Sensing, 2020

The study aimed to assess the potential of using Remote Sensing (RS) data to evaluate the changes... more The study aimed to assess the potential of using Remote Sensing (RS) data to evaluate the changes of urban green spaces in Lagos, Nigeria. Landsat Thematic Mapper and Landsat 8 (Operational Land Imager) data pair of May 4, 1986, December 12, 2002 and January 1, 2019 covering Lagos Government Authority (LGA) were used for this study. Supervised image classification technique using Maximum Likelihood Classifier (MLC) was used to create base map which was then used for ground truthing. Random Forest (RF) classification technique using RF classifier was utilized in this study to generate the final land use land cover map. RF is an ensemble learning method for classification that operates by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes (classification). Lagos census population data was also used in this study to model population projection. Extrapolation of the model was used to predict data for the years, 2020 and 2040. Results of the study revealed a reduction of urban green spaces due to agriculture and settlement. While the remote mapping revealed the gradual dispersion of ecosystem degradation indicators spread across the state, there exists clusters of areas vulnerable to environmental hazards across Lagos. To mitigate these risks, the paper offered recommendations ranging from the need for effective policy to green planning education for city managers, developers and risk assessment.

Advances in Remote Sensing, 2021

This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to com... more This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to compare land surface temperature of two cities in Ghana: Accra and Kumasi. These cities have human populations above 2 million and the corresponding anthropogenic impact on their environments significantly. Images were acquired with minimum cloud cover (<10%) from both dry and rainy seasons between December to August. Image preprocessing and rectification using ArcGIS 10.8 software were used. The shapefiles of Accra and Kumasi were used to extract from the full scenes to subset the study area. Thermal band data numbers were converted to Top of Atmospheric Spectral Radiance using radiance rescaling factors. To determine the density of green on a patch of land, normalized difference vegetation index (NDVI) was calculated by using red and near-infrared bands i.e. Band 4 and Band 5. Land surface emissivity (LSE) was also calculated to determine the efficiency of transmitting thermal energy across the surface into the atmosphere. Results of the study show variation of temperatures between different locations in two urban areas. The study found Accra to have experienced higher and lower dry season and wet season temperatures, respectively. The temperature ranges corresponding to the dry and wet seasons were found to be 21.0985˚C to 46.1314˚C, and, 18.3437˚C to 30.9693˚C respectively. Results of Kumasi also show a higher range of temperatures from 32.6986˚C to 19.1077˚C during the dry season. In the wet season, temperatures ranged from 26.

2006 GSW Proceedings

In this work studies were carried out on effect of temperature and air velocity (for low flow rat... more In this work studies were carried out on effect of temperature and air velocity (for low flow rates) on drying kinetics of English potatoes (batata inglesa). English potato slices of dimensions 4cm by 4cm by 5mm were put in four trays and air at different conditions and flow rates passed through them for analysis of corresponding drying characteristics. Air flow and source of heat were provided by a suction pump. Though low air flow rates were used, increase in their quantity resulted in increase in the drying rate. Increase in drying air temperature resulted in increase in rate of loss of moisture. A unique method of prediction (interpolation) is also attempted here. Experiments of drying at 1000 l/min and 2000 l/min were carried out. Best curves of fit for resulting data were plotted. The prediction for drying curves at 1500 l/min was done by interpolation between curves of 1000 l/min and 2000 l/min and results compared with experimental data (see Figure 4). The averages of three experimental data at 1500 l/min were, 0.7781, 0.7759 and 0.7741. The percentage error between each of experimental data set and corresponding values from predicted data was less than 1%. Another unique method used here is prediction of drying characteristics by polynomial models. Polynomial models gave the best fit when moisture content was defined in wet basis.

Advances in Remote Sensing, 2021

This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to com... more This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to compare land surface temperature of two cities in Ghana: Accra and Kumasi. These cities have human populations above 2 million and the corresponding anthropogenic impact on their environments significantly. Images were acquired with minimum cloud cover (<10%) from both dry and rainy seasons between December to August. Image preprocessing and rectification using ArcGIS 10.8 software were used. The shapefiles of Accra and Kumasi were used to extract from the full scenes to subset the study area. Thermal band data numbers were converted to Top of Atmospheric Spectral Radiance using radiance rescaling factors. To determine the density of green on a patch of land, normalized difference vegetation index (NDVI) was calculated by using red and near-infrared bands i.e. Band 4 and Band 5. Land surface emissivity (LSE) was also calculated to determine the efficiency of transmitting thermal energy across the surface into the atmosphere. Results of the study show variation of temperatures between different locations in two urban areas. The study found Accra to have experienced higher and lower dry season and wet season temperatures, respectively. The temperature ranges corresponding to the dry and wet seasons were found to be 21.0985˚C to 46.1314˚C, and, 18.3437˚C to 30.9693˚C respectively. Results of Kumasi also show a higher range of temperatures from 32.6986˚C to 19.1077˚C during the dry season. In the wet season, temperatures ranged from 26.

Atmospheric and Climate Sciences, 2020

Journal of Geographic Information System, 2020

Advances in Remote Sensing

This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to com... more This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to compare land surface temperature of two cities in Ghana: Accra and Kumasi. These cities have human populations above 2 million and the corresponding anthropogenic impact on their environments significantly. Images were acquired with minimum cloud cover (<10%) from both dry and rainy seasons between December to August. Image preprocessing and rectification using ArcGIS 10.8 software were used. The shapefiles of Accra and Kumasi were used to extract from the full scenes to subset the study area. Thermal band data numbers were converted to Top of Atmospheric Spectral Radiance using radiance rescaling factors. To determine the density of green on a patch of land, normalized difference vegetation index (NDVI) was cal-How to cite this paper: Twumasi, Y.A.,

Journal of Sustainable Bioenergy Systems

Mississippi State is renowned for its land resource areas (LRA) and production of bioenergy crops... more Mississippi State is renowned for its land resource areas (LRA) and production of bioenergy crops which generate both agricultural and economic benefits. Agricultural commodities play a key role in economic growth, therefore the ability to produce more would enhance development. This paper offers an analysis of the production of bioenergy crops in Mississippi. Relative measures, time series graphs and descriptive statistics coupled with geographic information systems (GIS) mapping using ArcMap were employed to generate the outcome of this research. The outcome of the statistical analysis indicated that corn and soybeans were the most produced crops in Agricultural Districts 10 and 40. These districts produced more bioenergy crops than the other districts. GIS mapping results also showed that the potential area for bioenergy crops is in zone 131 of the Mississippi Land Resource Area (MLRA). This zone has an absolute advantage in the production of these crops which includes the diversity of biomass production such as corn, cotton, soybeans, wheat, rice, barley, grain sorghum, canola, camelina, algae, hardwoods, and softwood. The paper recommends a constant GIS mapping and land management systems for each agricultural district in Mississippi to enable researchers and farmers to determine the factors which contribute towards the increasing and decreasing trends in the production of the bioenergy crops.

Advances in Remote Sensing, 2021

This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to com... more This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to compare land surface temperature of two cities in Ghana: Accra and Kumasi. These cities have human populations above 2 million and the corresponding anthropogenic impact on their environments significantly. Images were acquired with minimum cloud cover (<10%) from both dry and rainy seasons between December to August. Image preprocessing and rectification using ArcGIS 10.8 software were used. The shapefiles of Accra and Kumasi were used to extract from the full scenes to subset the study area. Thermal band data numbers were converted to Top of Atmospheric Spectral Radiance using radiance rescaling factors. To determine the density of green on a patch of land, normalized difference vegetation index (NDVI) was cal-How to cite this paper: Twumasi, Y.A.,

Journal of Sustainable Bioenergy Systems

Mississippi State is renowned for its land resource areas (LRA) and production of bioenergy crops... more Mississippi State is renowned for its land resource areas (LRA) and production of bioenergy crops which generate both agricultural and economic benefits. Agricultural commodities play a key role in economic growth, therefore the ability to produce more would enhance development. This paper offers an analysis of the production of bioenergy crops in Mississippi. Relative measures, time series graphs and descriptive statistics coupled with geographic information systems (GIS) mapping using ArcMap were employed to generate the outcome of this research. The outcome of the statistical analysis indicated that corn and soybeans were the most produced crops in Agricultural Districts 10 and 40. These districts produced more bioenergy crops than the other districts. GIS mapping results also showed that the potential area for bioenergy crops is in zone 131 of the Mississippi Land Resource Area (MLRA). This zone has an absolute advantage in the production of these crops which includes the diversity of biomass production such as corn, cotton, soybeans, wheat, rice, barley, grain sorghum, canola, camelina, algae, hardwoods, and softwood. The paper recommends a constant GIS mapping and land management systems for each agricultural district in Mississippi to enable researchers and farmers to determine the factors which contribute towards the increasing and decreasing trends in the production of the bioenergy crops.

Open Journal of Statistics

Precipitation is very important for both the environment and its inhabitants. Agricultural activi... more Precipitation is very important for both the environment and its inhabitants. Agricultural activities mostly depend on precipitation and its availability. Therefore, the ability to predict future precipitation values at specific stations is key for environmental and agricultural decision making. This research developed Autoregressive Integrated Moving Average (ARIMA) models for selected stations with Integrated component and Autoregressive Moving Average (ARMA) for selected stations without Integrated component at Louisiana State. The ARIMA module is represented as ARIMA(p, d, q)(P,D,Q). The selected lag order for the Autoregressive (AR) component is represented with p and P for seasonal AR component, while the integrated form (number of times data were differenced) is d and D for seasonal differencing, and the Moving Average (MA) lag order is q and Q for seasonal MA component. Data from 1950 to 2020 were employed in this research. Results of the analysis indicated that Baton Rouge (ARIMA (0,1,1) (0,0,2)12), Abbeville (ARMA (0,0,1) (0,0,2)12), Monroe Regional (ARMA (0,0,1) (0,0,0)12), New Orleans Airport (ARMA (1,0,0) (0,0,2)12), Alexandria (ARMA (1,0,1) (0,0,0)12), Logansport (ARIMA (0,1,2) (0,0,0)12), New Orleans Audubon (ARMA (1,0,0) (0,0,0)12), Lake Charles Airport (ARMA (2,0,2) (0,0,0)12) are the best ARIMA models for predicting precipitation in Louisiana. The models were used to predict the average monthly rainfall at each station. The highest precipitation observed in Louisiana was recorded in 1991. The Precipitation in Louisiana fluctuated over the years but has adopted a decreasing trend from the year 2000 to 2020. It was recommended that the government, researchers, and individuals take note of these models to make future plans to help increase the production of agricultural commodities and prevent destructions caused by excessive precipitation.

The Egyptian Journal of Remote Sensing and Space Science, 2018

The Kondapalli reserve forest (KRF) of the Eastern Ghats, India is subjected to severe anthropoge... more The Kondapalli reserve forest (KRF) of the Eastern Ghats, India is subjected to severe anthropogenic interference, despite its status as reserve forest. The present research focuses on assessing the land use and land cover changes in and around KRF using temporal satellite data. It is evident from the current study that there has been a considerable decrease in the forest cover from 1990 to 2015; as seen from 2017 data, huge urban expansions and development activities were observed around KRF. This increase is linked to the growth in population, thereby consuming land available for their basic needs. To assess the rate of urban expansion around the forest, Land consumption rate and Land absorption coefficient were computed. The result of this analysis showed a rapid growth in built-up land between 1990 and 2017 while the periods between 1990 and 2015 witnessed a reduction in the forest class. Further, the study projected adverse impact of the growth of the new capital city-Amaravati on the KRF and proposed requiring suitable conservation measures with respect to its current deforestation and degradation trends.

Journal of Sustainable Bioenergy Systems

Rising greenhouse gas emissions are causing climate change, and the world&amp;#39;s focus has... more Rising greenhouse gas emissions are causing climate change, and the world&amp;#39;s focus has shifted to the need to reduce our reliance on fossil fuels. There has been a rise in the published literature on the utilization of crops for bioenergy production in Louisiana. However, very few scholarly documents have used Geographic Information Systems (GIS) to map the distribution of potential bioenergy crops in Louisiana. This study seeks to fill the void by evaluating the potential of bioenergy crops in Louisiana for energy production using GIS. Given this objective, the agricultural census data for 1999, 2009, 2019, and 2020 obtained from the U.S. Department of Agriculture were used in the analysis. The quantities of various crops produced in the state were loaded into an attribute table and joined to a shapefile using ArcGIS software. The symbology tool&amp;#39;s graduated option was used to create five maps representing each of the bioenergy crops in Louisiana. The findings of the GIS analysis show that some of the parishes, such as Franklin produced the most bushels of corn (13,795,416), Iberia produced the most tons of sugarcane (1,697,980), East Carroll produced the most bushels of soybean (8,237,991), Tensas harvested the most bales of cotton (80,898) and Avoyelles produced the most bushels of sorghum (630,694). The abundance and availability of crops as raw materials for energy production will translate into lower prices in terms of energy use, making bioenergy crops a promising alternative to fossil fuels. In addition, gasoline price data from 1993-2022 was obtained from U.S. Energy Information Administration. A regression model for the average annual gasoline price over the years was constructed. The results show that the average How to cite this paper: Twumasi, Y.A.,

Advances in Remote Sensing, 2022

that the NDWI is higher for flood areas and lower for non-flooded ones. The ETS algorithm results... more that the NDWI is higher for flood areas and lower for non-flooded ones. The ETS algorithm results indicate that the population of Mozambique would nearly double by 2047. Human population along the coastal zone in the country is also on the rise exponentially. The paper concludes by outlining policy recommendations in the form of uniform distribution of economic activities across the country and prohibition of inland migration to the coastal areas where tropical cyclonic activities are very high.

Journal of Geographic Information System

A detailed study is presented of the expected performance of the ATLAS detector. The reconstructi... more A detailed study is presented of the expected performance of the ATLAS detector. The reconstruction of tracks, leptons, photons, missing energy and jets is investigated, together with the performance of b-tagging and the trigger. The physics potential for a variety of interesting physics processes, within the Standard Model and beyond, is examined. The study comprises a series of notes based on simulations of the detector and physics processes, with particular emphasis given to the data expected from the first years of operation of the LHC at CERN.

Advances in Remote Sensing, 2020

The study aimed to assess the potential of using Remote Sensing (RS) data to evaluate the changes... more The study aimed to assess the potential of using Remote Sensing (RS) data to evaluate the changes of urban green spaces in Lagos, Nigeria. Landsat Thematic Mapper and Landsat 8 (Operational Land Imager) data pair of May 4, 1986, December 12, 2002 and January 1, 2019 covering Lagos Government Authority (LGA) were used for this study. Supervised image classification technique using Maximum Likelihood Classifier (MLC) was used to create base map which was then used for ground truthing. Random Forest (RF) classification technique using RF classifier was utilized in this study to generate the final land use land cover map. RF is an ensemble learning method for classification that operates by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes (classification). Lagos census population data was also used in this study to model population projection. Extrapolation of the model was used to predict data for the years, 2020 and 2040. Results of the study revealed a reduction of urban green spaces due to agriculture and settlement. While the remote mapping revealed the gradual dispersion of ecosystem degradation indicators spread across the state, there exists clusters of areas vulnerable to environmental hazards across Lagos. To mitigate these risks, the paper offered recommendations ranging from the need for effective policy to green planning education for city managers, developers and risk assessment.

Advances in Remote Sensing, 2021

This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to com... more This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to compare land surface temperature of two cities in Ghana: Accra and Kumasi. These cities have human populations above 2 million and the corresponding anthropogenic impact on their environments significantly. Images were acquired with minimum cloud cover (<10%) from both dry and rainy seasons between December to August. Image preprocessing and rectification using ArcGIS 10.8 software were used. The shapefiles of Accra and Kumasi were used to extract from the full scenes to subset the study area. Thermal band data numbers were converted to Top of Atmospheric Spectral Radiance using radiance rescaling factors. To determine the density of green on a patch of land, normalized difference vegetation index (NDVI) was calculated by using red and near-infrared bands i.e. Band 4 and Band 5. Land surface emissivity (LSE) was also calculated to determine the efficiency of transmitting thermal energy across the surface into the atmosphere. Results of the study show variation of temperatures between different locations in two urban areas. The study found Accra to have experienced higher and lower dry season and wet season temperatures, respectively. The temperature ranges corresponding to the dry and wet seasons were found to be 21.0985˚C to 46.1314˚C, and, 18.3437˚C to 30.9693˚C respectively. Results of Kumasi also show a higher range of temperatures from 32.6986˚C to 19.1077˚C during the dry season. In the wet season, temperatures ranged from 26.

2006 GSW Proceedings

In this work studies were carried out on effect of temperature and air velocity (for low flow rat... more In this work studies were carried out on effect of temperature and air velocity (for low flow rates) on drying kinetics of English potatoes (batata inglesa). English potato slices of dimensions 4cm by 4cm by 5mm were put in four trays and air at different conditions and flow rates passed through them for analysis of corresponding drying characteristics. Air flow and source of heat were provided by a suction pump. Though low air flow rates were used, increase in their quantity resulted in increase in the drying rate. Increase in drying air temperature resulted in increase in rate of loss of moisture. A unique method of prediction (interpolation) is also attempted here. Experiments of drying at 1000 l/min and 2000 l/min were carried out. Best curves of fit for resulting data were plotted. The prediction for drying curves at 1500 l/min was done by interpolation between curves of 1000 l/min and 2000 l/min and results compared with experimental data (see Figure 4). The averages of three experimental data at 1500 l/min were, 0.7781, 0.7759 and 0.7741. The percentage error between each of experimental data set and corresponding values from predicted data was less than 1%. Another unique method used here is prediction of drying characteristics by polynomial models. Polynomial models gave the best fit when moisture content was defined in wet basis.

Advances in Remote Sensing, 2021

This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to com... more This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to compare land surface temperature of two cities in Ghana: Accra and Kumasi. These cities have human populations above 2 million and the corresponding anthropogenic impact on their environments significantly. Images were acquired with minimum cloud cover (<10%) from both dry and rainy seasons between December to August. Image preprocessing and rectification using ArcGIS 10.8 software were used. The shapefiles of Accra and Kumasi were used to extract from the full scenes to subset the study area. Thermal band data numbers were converted to Top of Atmospheric Spectral Radiance using radiance rescaling factors. To determine the density of green on a patch of land, normalized difference vegetation index (NDVI) was calculated by using red and near-infrared bands i.e. Band 4 and Band 5. Land surface emissivity (LSE) was also calculated to determine the efficiency of transmitting thermal energy across the surface into the atmosphere. Results of the study show variation of temperatures between different locations in two urban areas. The study found Accra to have experienced higher and lower dry season and wet season temperatures, respectively. The temperature ranges corresponding to the dry and wet seasons were found to be 21.0985˚C to 46.1314˚C, and, 18.3437˚C to 30.9693˚C respectively. Results of Kumasi also show a higher range of temperatures from 32.6986˚C to 19.1077˚C during the dry season. In the wet season, temperatures ranged from 26.

Atmospheric and Climate Sciences, 2020

Journal of Geographic Information System, 2020

Advances in Remote Sensing

This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to com... more This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to compare land surface temperature of two cities in Ghana: Accra and Kumasi. These cities have human populations above 2 million and the corresponding anthropogenic impact on their environments significantly. Images were acquired with minimum cloud cover (<10%) from both dry and rainy seasons between December to August. Image preprocessing and rectification using ArcGIS 10.8 software were used. The shapefiles of Accra and Kumasi were used to extract from the full scenes to subset the study area. Thermal band data numbers were converted to Top of Atmospheric Spectral Radiance using radiance rescaling factors. To determine the density of green on a patch of land, normalized difference vegetation index (NDVI) was cal-How to cite this paper: Twumasi, Y.A.,

Journal of Sustainable Bioenergy Systems

Mississippi State is renowned for its land resource areas (LRA) and production of bioenergy crops... more Mississippi State is renowned for its land resource areas (LRA) and production of bioenergy crops which generate both agricultural and economic benefits. Agricultural commodities play a key role in economic growth, therefore the ability to produce more would enhance development. This paper offers an analysis of the production of bioenergy crops in Mississippi. Relative measures, time series graphs and descriptive statistics coupled with geographic information systems (GIS) mapping using ArcMap were employed to generate the outcome of this research. The outcome of the statistical analysis indicated that corn and soybeans were the most produced crops in Agricultural Districts 10 and 40. These districts produced more bioenergy crops than the other districts. GIS mapping results also showed that the potential area for bioenergy crops is in zone 131 of the Mississippi Land Resource Area (MLRA). This zone has an absolute advantage in the production of these crops which includes the diversity of biomass production such as corn, cotton, soybeans, wheat, rice, barley, grain sorghum, canola, camelina, algae, hardwoods, and softwood. The paper recommends a constant GIS mapping and land management systems for each agricultural district in Mississippi to enable researchers and farmers to determine the factors which contribute towards the increasing and decreasing trends in the production of the bioenergy crops.

Advances in Remote Sensing, 2021

This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to com... more This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to compare land surface temperature of two cities in Ghana: Accra and Kumasi. These cities have human populations above 2 million and the corresponding anthropogenic impact on their environments significantly. Images were acquired with minimum cloud cover (<10%) from both dry and rainy seasons between December to August. Image preprocessing and rectification using ArcGIS 10.8 software were used. The shapefiles of Accra and Kumasi were used to extract from the full scenes to subset the study area. Thermal band data numbers were converted to Top of Atmospheric Spectral Radiance using radiance rescaling factors. To determine the density of green on a patch of land, normalized difference vegetation index (NDVI) was cal-How to cite this paper: Twumasi, Y.A.,

Journal of Sustainable Bioenergy Systems

Mississippi State is renowned for its land resource areas (LRA) and production of bioenergy crops... more Mississippi State is renowned for its land resource areas (LRA) and production of bioenergy crops which generate both agricultural and economic benefits. Agricultural commodities play a key role in economic growth, therefore the ability to produce more would enhance development. This paper offers an analysis of the production of bioenergy crops in Mississippi. Relative measures, time series graphs and descriptive statistics coupled with geographic information systems (GIS) mapping using ArcMap were employed to generate the outcome of this research. The outcome of the statistical analysis indicated that corn and soybeans were the most produced crops in Agricultural Districts 10 and 40. These districts produced more bioenergy crops than the other districts. GIS mapping results also showed that the potential area for bioenergy crops is in zone 131 of the Mississippi Land Resource Area (MLRA). This zone has an absolute advantage in the production of these crops which includes the diversity of biomass production such as corn, cotton, soybeans, wheat, rice, barley, grain sorghum, canola, camelina, algae, hardwoods, and softwood. The paper recommends a constant GIS mapping and land management systems for each agricultural district in Mississippi to enable researchers and farmers to determine the factors which contribute towards the increasing and decreasing trends in the production of the bioenergy crops.

Open Journal of Statistics

Precipitation is very important for both the environment and its inhabitants. Agricultural activi... more Precipitation is very important for both the environment and its inhabitants. Agricultural activities mostly depend on precipitation and its availability. Therefore, the ability to predict future precipitation values at specific stations is key for environmental and agricultural decision making. This research developed Autoregressive Integrated Moving Average (ARIMA) models for selected stations with Integrated component and Autoregressive Moving Average (ARMA) for selected stations without Integrated component at Louisiana State. The ARIMA module is represented as ARIMA(p, d, q)(P,D,Q). The selected lag order for the Autoregressive (AR) component is represented with p and P for seasonal AR component, while the integrated form (number of times data were differenced) is d and D for seasonal differencing, and the Moving Average (MA) lag order is q and Q for seasonal MA component. Data from 1950 to 2020 were employed in this research. Results of the analysis indicated that Baton Rouge (ARIMA (0,1,1) (0,0,2)12), Abbeville (ARMA (0,0,1) (0,0,2)12), Monroe Regional (ARMA (0,0,1) (0,0,0)12), New Orleans Airport (ARMA (1,0,0) (0,0,2)12), Alexandria (ARMA (1,0,1) (0,0,0)12), Logansport (ARIMA (0,1,2) (0,0,0)12), New Orleans Audubon (ARMA (1,0,0) (0,0,0)12), Lake Charles Airport (ARMA (2,0,2) (0,0,0)12) are the best ARIMA models for predicting precipitation in Louisiana. The models were used to predict the average monthly rainfall at each station. The highest precipitation observed in Louisiana was recorded in 1991. The Precipitation in Louisiana fluctuated over the years but has adopted a decreasing trend from the year 2000 to 2020. It was recommended that the government, researchers, and individuals take note of these models to make future plans to help increase the production of agricultural commodities and prevent destructions caused by excessive precipitation.

Namwamba (Southern University and A&M College) 1 , Dr. Yaw Twumasi (Southern University and A&M C... more Namwamba (Southern University and A&M College) 1 , Dr. Yaw Twumasi (Southern University and A&M College) 2 , Dr. Fulbert Namwamba (Salisburry University) 3 , Justin Egbe (Southern University and A&M College) 4 and Ronald Okwemba (Southern University and A&M College) 5 Lake Turkana, Africa's fourth largest lake and the world's largest desert lake, is in Kenya's northern arid and semi-arid lands. It is also the world's largest desert lake. The people in this region subsist mainly through pastoralism. The human and livestock population has significantly risen. This area suffers frequent droughts, leading to death of livestock in large numbers and destitution. Hence, for a period of over 40 years, this area has been a regular recipient of humanitarian relief food. Lake Turkana's catchment has an area of 130,860 square kilometers, both Kenya and Ethiopia. The lake is mainly sustained by the inflows of Ethiopia's Omo River. The river's contributions are about 90% of the lake's inflow. Since Lake Turkana is a closed watershed; gradual eventual evaporation of the inflows renders the lake water almost saline and hence, unfit for human consumption. The water is also unfitting for agriculture. It however, provides habitat for a thriving and diverse fish population. The Gibe III Project which includes damming of the Omo river to create of one of the world's largest dams is ongoing. The project threatens the livelihood of communities depending on Lake Turkana and its ecosystem. By the end of the project, the annual Omo river's inflow will be significantly reduced. The aim of this study is to quantify the negative impact of damming the Omo river on the people settled around Lake Turkana and resulting conflicts. The impact on the average depth of lake Turkana will also studied.