An Assessment of the Potential Use of Forest Residues for the Production of Bio-Oils in the Urban-Rural Interface of Louisiana

Louisiana is endowed with forest resources. Forest wastes generated after thinning, land clearing, and logging operations, such as wood debris, tree trimmings, barks, sawdust, wood chips, and black liquor, among others, can serve as potential fuels for energy production in Louisiana. This paper aims to evaluate the potential annual volumes of forest wastes established on detailed and existing data on the forest structure in the rural-urban interface of Louisiana. It also demonstrates the state’s prospects of utilizing forest wastes to produce bio-oils. The data specific to the study was deduced from secondary data sources to obtain the annual average total residue production in Louisiana and estimate the number of logging residues available for procurement for bioenergy production. The total biomass production per year was modeled versus years by polynomial regression curve fitting using Microsoft Excel. Results of the model show that the cumulative annual total biomass production for 2025 and 2030 in Louisiana is projected to be 80000000 Bone Dry Ton (BDT) and 16000000 (BDT) respectively. The findings of the study depict that Louisiana has a massive biomass supply from forest wastes for bioenergy production. Thus, the potential for Louisiana to become an influential player in the production of bio-based products from forest residues is evident. The author recommends that future research can use Geographic Information Systems (GIS) to create maps displaying the potential locations and utilization centers of forest wastes for bioenergy production in the state.

Fusion of Landsat 8 OLI and PlanetScope Images for Urban Forest Management in Baton Rouge, Louisiana

In recent years image fusion method has been used widely in different studies to improve spatial resolution of multispectral images. This study aims to fuse high resolution satellite imagery with low multispectral imagery in order to assist policymakers in the effective planning and management of urban forest ecosystem in Baton Rouge. To accomplish these objectives, Landsat 8 and PlanetScope satellite images were acquired from United States Geological Survey (USGS) Earth Explorer and Planet websites with pixel resolution of 30m and 3m respectively. The reference images (observed Landsat 8 and PlanetScope imagery) were acquired on 06/08/2020 and 11/19/2020. The image processing was performed in ArcMap and used 6-5-4 band combination for Landsat 8 to visually inspect healthy vegetation and the green spaces. The near-infrared (NIR) panchromatic band for PlanetScope was merged with Landsat 8 image using the Create Pan-Sharpened raster tool in ArcMap and applied the Intensity-Hue-Saturation (IHS) method. In addition, location of urban forestry parks in the study area was picked using the handheld GPS and recorded in an excel sheet. This sheet was converted into Excel (.csv) file and imported into ESRI ArcMap to identify the spatial distribution of the green spaces in East Baton Rouge parish. Results show fused images have better contrast and improve visualization of spatial features than non-fused images. For example, roads, trees, buildings appear sharper, easily discernible, and less pixelated compared to the Landsat 8 image in the fused image. The paper concludes by outlining policy recommendations in the form of sequential measurement of urban forest over time to help track changes and allows for better informed policy and decision making with respect to urban forest management.

Implications of Planting Southern Live Oak Trees in the Wrong Urban Space in East Baton Rouge, Louisiana United States

Afforestation has been observed as a green trend in urban areas. The incorporation of trees in urban infrastructure is highly recommended to act as a solution to outlined environmental problems such as global warming. However, it has been precipitously introduced in cities, towns, and metropolitans. The introduction of the green practice was so abrupt that it became devoid to meeting the essential needs for tree growth, thus, failing to bring out the desired effects. Inappropriately selecting and planting trees in urban spaces has resulted in stressed trees that are deficient at reaching up to the calculated goals and in the long run end up being problematic. The main objective of this study is to evaluate the implications of planting southern live oak (Quercus virginiana) trees in the wrong urban space so as to aid in recommending sustainable green solutions for the urban community. By studying southern live oaks planted in Howell Community Park and three randomly selected areas in Southern University Baton Rouge Campus, this study analyzes how the selection of these tree species in the urban spaces influenced their growth and general well-being. These urban spaces were randomly drafted based on accessibility and availability of several southern live oaks. Planting approaches in the four study areas were explored and the general health condition of the trees was determined using the tree appraisal method presented by the i-tree model: my tree. ArcGIS collector was used to collect the GPS coordinates of the trees and ArcMap was used to generate the maps of the study areas. ArcMap software geolocated the coordinates of the southern live oaks in all the four-study areas. The software was used to generate shapefiles of the four study areas and their location in East Baton Rouge. The analysis of the results proved that none of the southern live oaks had an excellent health condition and most of the trees experienced different issues due to planting them in the wrong urban spaces.

Assessing the Impact of Population Growth in Louisiana on Diminishing Water Quantity and Quality within the State

This study explores the intricate relationship between population growth and water resource management in Louisiana, emphasizing the spatial distribution of water quality. Human activities, particularly urbanization, have significantly impacted the state’s water resources, with population growth driving increased water withdrawals for public supply, industry, and power generation. By employing a Geographic Information System (GIS)-centered approach, this research utilizes Louisiana’s census data from 1999 to 2020 to illustrate population shifts and their effects on water resource distribution. The study also incorporated advanced remote sensing techniques, using Sentinel 2 imagery to assess the water quality through the Trophic State Index (TSI). The TSI, calculated based on the near-infrared (NIR) and Red bands of Sentinel-2 imagery, provided a nuanced understanding of the nutrient levels and clarity/ quality of water bodies across the state. The study reveals a significant correlation between population density and water withdrawals, with higher populations leading to greater extraction from both groundwater and surface water sources. For instance, densely populated parishes like East Baton Rouge and Orleans showed substantially higher water withdrawals for public supply, industry, and power generation compared to less populated areas. The water quality analysis indicated that many water bodies in Louisiana are experiencing high levels of nutrient enrichment, with rivers and streams accounting for 86% of the impaired water bodies, and lakes, reservoirs, and coastal waters showing hypereutrophic conditions in up to 96% of cases. These results underscore the significant impact of human activities on Louisiana’s water resources, highlighting the need for effective water management practices that consider both quantity and quality. The study therefore advocates for the implementation of water conservation measures, responsible consumption, and pollution prevention strategies to ensure the sustainable use of water resources and the preservation of water quality across Louisiana.

The Impacts of Louisiana’s Changing Climate on Food Crop Production

While various prior studies have delved into the potential consequences of climate change on crop production in specific areas, notably in southeastern Louisiana, limited investigation has been carried out concerning some crops within the state of Louisiana. Consequently, there exists a dearth of knowledge regarding the specific hurdles and potential benefits confronting agricultural producers in this region. Therefore, the primary aim of this study was to explore and measure the impact of climate change on the yields of corn, rice, soybeans, and cotton in Louisiana, thereby addressing this informational void. The study uses data on average high temperatures and precipitation to assess the impact of climate change on these specific food crops in Louisiana. The researchers used ArcGIS and its symbology tool to create three separate maps depicting the spatial distribution of harvested cropland in Louisiana. The graduated color option was used on each map, which represented the years 2007, 2012, and 2017. Similarly, eight separate maps were created using the graduated color option to visually present the distribution patterns of Louisiana’s corn, cotton, rice, and soybean crops. These maps provided a visual representation of the state’s total crop production between 2007 and 2017. The researchers also created six bar charts to show the distribution of corn, cotton, rice, and soybean production in Louisiana over three time periods: 2007, 2012, and 2017. These charts also included information about the average high temperature and annual precipitation in each parish. The study revealed decreasing trends in Louisiana corn and cotton yields alongside consistent increases in rice and soybean yields, with projections suggesting future temperature rises may negatively impact crop yields, highlighting the need for research into climate-smart agricultural practices to mitigate these effects and safeguard global crop production. Louisiana’s response to climate change in food crop production involves implementing a comprehensive Climate-Resilient Agriculture Program, focusing on developing climate-adaptive crop varieties, sustainable water management, climate-responsive insurance, farmer education, and outreach to safeguard food security, enhance agricultural resilience, and ensure sustainable crop production.

Estimation of Land Surface Temperature from Landsat-8 OLI Thermal Infrared Satellite Data. A Comparative Analysis of Two Cities in Ghana

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 21.0985oC to 46.1314oC, and, 18.3437oC to 30.9693oC respectively. Results of Kumasi also show a higher range of temperatures from 32.6986oC to 19.1077oC during the dry season. In the wet season, temperatures ranged from 26.4142oC to -0.898728oC. Among the reasons for the cities of Accra and Kumasi recorded higher than corresponding rural areas’ values can be attributed to the urban heat islands’ phenomenon.

Land Resource Areas and Spatial Analysis of Potential Location of Bioenergy Crops Production in Mississippi

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.

Spatiotemporal Analysis of COVID-19 Lockdown Impact on the Land Surface Temperatures of Different Land Cover Types in Louisiana

The COVID-19 pandemic posed a serious threat to life on the entire planet, necessitating the imposition of a lockdown mechanism that restricted people’s movements to stop the disease’s spread. This period experienced a decline in air pollution emissions and some environmental changes, offering a rare opportunity to understand the effects of fewer human activities on the earth’s temperature. Hence, this study compares the changes in Land Surface Temperature (LST) that were observed prior to the pandemic (March & April 2019) and during the pandemic lockdown (March & April 2020) of three parishes in Louisiana. The data for this study was acquired using Landsat 8 Thermal Infrared Sensor (TIRS) Level 2, Collection 2, Tier 2 from the Google Earth Engine Catalog. For better visualization, the images that were derived had a cloud cover of less than 10%. Also, images for the three study areas were processed and categorized into four main classes: water, vegetation, built-up areas, and bare lands using a Random Forest Supervised Classification Algorithm. To improve the accuracy of the image classifications, three Normalized Difference Indices namely the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI) and Normalized Difference Built-Up Index (NDBI) were employed using the Near Infrared (NIR), Red, Green and SWIR bands for the calculations. After, these images were processed in Google Earth Engine to generate the LST products gridded at 30 m with a higher spatial resolution of 100 m according to the pre-pandemic (2019) and lockdown (2020) periods for the three study areas. Results of this study showed a decrease in LST values of the land cover classes from 2019 to 2020, with LST values in East Baton Parish decreasing from 44°C to 38°C, 42°C to 38°C in Lafayette Parish, and 43°C to 38°C in Orleans Parish. The variations in the LST values therefore indicate the impact of fewer anthropogenic factors on the earth’s temperature which requires regulatory and mitigative measures to continually reduce LST and control microclimate, especially in urban areas.

Analysis of Forest Waste Management and Recycling Potential in Nigeria

Forest wastes are renewable resources that can serve as sources of energy for heat and electricity generation. How these materials are managed in order to reduce their contribution to the release of greenhouse gases, reduce subsequent climate change challenges and their potential use in bio-energy production has remained a myth in Nigeria. In this paper, extensive review of the literature was carried out to arrive at the findings. More than 93% of all wood processing industries in Nigeria are sawmills. In addition to sawmills there are the plywood mills, furniture processing industries, and particleboard mills. Sawdust is the major waste generated from wood processing in the various processing units. Currently, the most popular waste management practice in Nigeria is burning. Dumping in open spaces, riverbanks, and water bodies is also obtainable. There is no record of wood waste recycling for bio-fuel production at the moment. Wood wastes are reused for agricultural production (mulching, manure) and as firewood. These actions contribute to the release of greenhouse gases and subsequently contribute to global warming. There are policies and agencies put in place to address this menace but implementation is a problem. An increase in proper waste management education and awareness, and aid from developed countries in terms of providing the technology needed for recycling and incineration, will go a long way in ensuring the safety (from climate change and consequences) of the local people, the environment, and the world at large.

Assessing the Impact of Land Use and Land Cover Change on Air Quality in East Baton Rouge—Louisiana Using Earth Observation Techniques

There has been significant research in recent decades on Land use Land cover (LULC) changes and their influence on biodiversity but little to no research on its impact on air quality. This research seeks to demonstrate how geospatial technologies such as geographic information system (GIS) and remote sensing can be used to assess the effects of LULC changes on particulate matter emissions and their impact on air quality in the East Baton Rouge area. In pursuit of these objectives, this study uses LANDSAT imageries from the past 30 years specifically Landsat Thematic Mapper (TM C2L2) and Landsat 8 Operational Land Imager/Thermal Infrared (OLI/TIRS C2L2) covering 1991, 2001, 2011 and 2021 were collected, processed, and analyzed for the LULC change analysis using QGIS software. Additionally, Sentinel 5P and the Air quality index from the U.S. Environmental Protection Agency (EPA) were used to assess the air quality trend over the years to establish the correlation between LULC and air quality. Results showed an increasing trend in air quality over the past 3 decades with concentrations of CO, NO2, and PM2.5 abruptly falling however, urbanization and the population expanded throughout the time. The paper concludes by outlining a policy recommendation in the form of encouraging Louisiana residents to use alternative renewable energies rather than the over-dependence on coal-fired electric generating plants that have an impact on the environment.

Modeling the Risks of Climate Change and Global Warming to Humans Settled in Low Elevation Coastal Zones in Louisiana, USA

This paper seeks to identify high risk areas that are prone to flooding, caused by sea level rise because of high impacts of global climate change resulting from global warming and human settlements in low-lying coastal elevation areas in Louisiana, and model and understand the ramifications of predicted sea-level rise. To accomplish these objectives, the study made use of accessible public datasets to assess the potential risk faced by residents of coastal lowlands of Southern Louisiana in the United States. Elevation data was obtained from the Louisiana Statewide Light Detection and Ranging (LiDAR) with resolution of 16.4 feet (5 m) distributed by Atlas. The data was downloaded from Atlas website and imported into Environmental Systems Research Institute’s (ESRI’s) ArcMap software to create a single mosaic elevation image map of the study area. After mosaicking the elevation data in ArcMap, Spatial Analyst extension software was used to classify areas with low and high elevation. Also, data was derived from United States Geological Survey (USGS) Digital Elevation Model (DEM) and absolute sea level rise data covering the period 1880 to 2015 was acquired from United States Environmental Protection Agency (EPA) website. In addition, population data from U.S. Census Bureau was obtained and coupled with elevation data for assessing the risks of the population residing in low lying areas. Models of population trend and cumulative sea level rise were developed using statistical methods and software were applied to reveal the national trends and local deviations from the trends. The trends of population changes with respect to sea level rise and time in years were modeled for the low land coastal parishes of Louisiana. The expected years for the populations in the study area to be at risk due to rising sea level were estimated by models. The geographic information systems (GIS) results indicate that areas of low elevation were mostly located along the coastal Parishes in the study area. Further results of the study revealed that, if the sea level continued to rise at the present rate, a population of approximately 1.8 million people in Louisiana’s coastal lands would be at risk of suffering from flooding associated with the sea level having risen to about 740 inches by 2040. The population in high risk flood zone was modeled by the following equation: y = 6.6667x - 12,864, with R squared equal to 0.9964. The rate of sea level rise was found to increase as years progressed. The slopes of models for data for time periods, 1880-2015 (entire data) and 1970-2015 were found to be, 4.2653 and 6.6667, respectively. The increase reflects impacts of climate change and land management on rate of sea level rise, respectively. A model for the variation of years with respect to cumulative sea level was developed for use in predicting the year when the cumulative sea level would equal the elevation above sea level of study area parishes. The model is given by the following equation: y = 0.1219x + 1944.1 with R square equal to 0.9995.

Analysis of Precipitation Trends and Prediction in Selected Cities in the Southeast Louisiana

The impacts of climate change are being felt in Louisiana, in the form of changing weather patterns that have resulted in changes in floods, hurricanes, tornadoes frequencies of occurrence, and magnitudes, among others resulting in, flooding. The variabilities in rainfall in a drainage basin affect water availability and sustainability. This study analyzed the precipitation data of Southeastern Louisiana, United States, for the period 1990 to 2020. Data used in the study was from, Donaldsonville, Galliano, Lafourche, Gonzales, Ascension, Morgan, New Orleans, Audubon, Plaquemine, and Ponchatoula, Tangipahoa, weather stations. These stations were selected because the differences between each of their highest and lowest average annual rainfall data were greater than 20 inches. To investigate climate patterns and trends for the given weather stations in Southeastern Louisiana, precipitation data were analyzed on annual time scales using data collected from the World Bank Group Climate Change Knowledge Portal for Development Practitioners and Policy Makers and the Applied Climate Information System (ACIS) of the National Weather Service Prediction Center. The data were further aggregated using annual average blocks of 4 years, and linear and polynomial regression was performed to establish trends. The highest and lowest average annual rainfall data for Donaldsonville, Galliano, Lafourche, Gonzales, Ascension, Morgan, New Orleans, Audubon, Plaquemine, and Ponchatoula, Tangipahoa, weather stations were, 75 and 48, 71 and 44, 73.5 and 52.7, 75 and 46.4, 72 and 41.3, 94 and 55.3, Ponchatoula, and 78.6 and 44, respectively. Plaquemine recorded the highest average annual average rainfall while New Orleans, Audubon station recorded the lowest. The projection of the precipitation in 2030 has been carried out to inform scientists and stakeholders about the approximate quantity of rainfall expected and enable them to make their expected impacts on agriculture, economy, etc. The precipitation for 2030 was predicted by extrapolating models for the weather stations. The data used for the modeling was selected based on the data entries most representative. Hence, the coefficient of correlation and the number of data entries were both considered. Extrapolating results for 2030 precipitation in Donaldsonville, Galliano, Gonzales, Morgan, New Orleans, Audubon, and Plaquemine were found to be within the ranges, (85.6 - 86.7), (75.55 - 76.60), (89.7 - 90.67), (99.9 - 100.5), (71.68 - 72.66), and (107.7 - 108.8) inches, respectively. Hence, the average annual precipitations in areas covered by these stations except for Plaquemine station are expected to significantly increase. A restively low increase in average precipitation is expected for Plaquemine station. The increase could impact agriculture negatively or positively depending on the crop’s soil moisture tolerance.

Bioenergy: Examining the Efficient Utilization of Agricultural Biomass as a Source of Sustainable Renewable Energy in Louisiana

The use of renewable energy is steadily being adopted as a mitigative measure for reducing greenhouse gas emissions. By assessing biomass production and consumption estimates from Louisiana parishes, this study examines the utilization of agricultural biomass as a convenient renewable energy source, and the potential of marginal lands for growing bioenergy crops in Louisiana. This was achieved by retrieving parish-level acreage production of some biofuel crops recorded in 2021 using the Quick Stats Database, to map out the spatial locations and distribution of the biofuel crops. To examine the potential of Louisiana’s marginal lands in bioenergy crop production, data was obtained from the Soil Survey Geographic (SSURGO) database and mapped-out according to the eight Land Capability Classes numbered I-VIII. The results of the mapped-out acreage data revealed that 25% of the 64 parishes including Morehouse recorded high corn production estimates, while 43%, such as East Carroll, recorded high soybean production. Meanwhile, cotton production estimates were relatively low, as recorded in only 9 parishes, with one parish, Tensas, having the highest acreage production of around 23,000. Although the identified marginal lands in parishes such as Allen and Vernon had no records of corn, soybean, or cotton production, the soil survey database revealed that these marginal lands have high nutrient soils like Alfisols, Entisols and Inceptisols with optimal nutrient balance essential for high yield bioenergy crop production. Hence, this paper highlights Louisiana’s agricultural biomass to be leveraged as sustainable renewable sources while adhering to clear production guidelines, biofuel sustainability certification, and internationally agreed sustainability criteria.

Analyzing Climate Change Impacts on Louisiana’s Water Resources Using GIS Techniques

Louisiana possesses a bountiful groundwater reserve, an invaluable and noteworthy asset. Despite extensive literature on climate change implications in Louisiana, there is limited academic research focused on its effects on the state’s water resources. Therefore, this study addresses that gap by using GIS to spatially analyze water usage trends from 1960 to 2014, to examine climate-induced consequences and determine the susceptibility of water utilities’ functions and facilities. This study utilized various online sources to gather data on water withdrawals, temperature trends, and climate impacts in Louisiana. Water usage data from the Lower Mississippi Gulf-Water Science Centre and temperature trends from Meteoblue covering 2023 were also analyzed to assess the state’s water resource challenges. The water withdrawal data was linked to a shapefile within ArcMap, using graduated color symbology to visualize regional variations in water usage. This method highlighted significant water withdrawals across Louisiana from 1960 to 2014, clearly illustrating the differences between regions. Based on the data sources, the results show that groundwater levels in Louisiana have steadily declined over time. For instance, water levels in the Jasper Aquifer in St. Tammany dropped from approximately 125 feet to 50 feet, while levels in the Sparta Aquifer in Lincoln fell from 30 feet to −25 feet. Similarly, the Chicot Aquifer in Acadia experienced a decline from −25 feet to −50 feet. These reductions indicate a concerning trend of groundwater depletion, exacerbated by high temperatures and current drought conditions affecting roughly 73% of the state. To ensure sustainable water management in Louisiana, investing in water storage, transfer infrastructure, and conservation practices are needed to protect surface and groundwater sources. More so, the state’s Reservoir Priority and Development Program (RPDP), which includes the construction of reservoirs, is a key initiative that can address water scarcity, improve water supply, and enhance long-term water security.

Time Series Analysis on Selected Rainfall Stations Data in Louisiana Using ARIMA Approach

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.

Bioenergy Crops as a Promising Alternative to Fossil Fuels in Louisiana: A Geographic Information System (GIS) Perspective

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 annual gasoline price variation with respect to years is statistically significant (p 0.05). This suggests that gasoline prices will generally rise despite a price drop over the years. The paper concludes by outlining policy recommendations in the form of assessing the availability and viability of other crop types, such as wheat, oats, and rice, for energy production in the state.

Flood Mapping in Mozambique Using Copernicus Sentinel-2 Satellite Data

Over the last two decades, Mozambique has experienced tremendous tropical cyclonic activities causing many flooding activities accompanied by disastrous human casualties. Studies that integrate remote sensing, elevation data and coupled with demographic analysis in Mozambique are very limited. This study seeks to fill the void by employing satellite data to map inundation caused by Tropical Cyclones in Mozambique. In pursuit of this objective, Sentinel-2 satellite data was obtained from the United States Geological Survey (USGS)’s Earth Explorer free Online Data Services imagery website covering the months of March 20, 2019, March 25, 2019, and April 16, 2019 for two cities, Maputo and Beira in Mozambique. The images were geometrically corrected to remove, haze, scan lines and speckles, and then referenced to Mozambique ground-based Geographic: Lat/Lon coordinate system and WGS 84 Datum. Data from twelve spectral bands of Sentinel-2 satellite, covering the visible and near infrared sections of the electromagnetic spectrum, were further used in the analysis. In addition, Normalized Difference Water Index (NDWI) within the study area was computed using the green and near infrared bands to highlight water bodies of Sentinel-2 detectors. To project and model the population of Mozambique and see the impact of cyclones on the country, demographic data covering 1980 to 2017 was obtained from the World Bank website. The Exponential Smoothing (ETS) method was adopted to forecast the population of Mozambique. Results from NDWI analysis showed 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.