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Flood Mapping in Mozambique Using Copernicus Sentinel-2 Satellite Data
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作者 Yaw A. Twumasi Edmund C. Merem +19 位作者 John b. Namwamba Abena b. Asare-Ansah Jacob b. Annan Zhu H. Ning Rechael N. D. Armah Caroline Y. Apraku harriet b. yeboah Julia Atayi Matilda Anokye Diana b. Frimpong Ronald Okwemba Olipa S. Mwakimi Judith Oppong brilliant M. Petja Janeth Mjema Priscilla M. Loh Lucinda A. Kangwana Valentine Jeruto Leah Wangari Njeri Joyce McClendon-Peralta 《Advances in Remote Sensing》 2022年第3期80-105,共26页
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, elevati... 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. 展开更多
关键词 Tropical Cyclones Floods Remote Sensing NDWI Exponential Smoothing (ETS) Digital Elevation Model (DEM) Sentinel-2 Satellite Mozambique
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An Assessment of the Potential Use of Forest Residues for the Production of Bio-Oils in the Urban-Rural Interface of Louisiana
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作者 Yaw A. Twumasi Zhu H. Ning +13 位作者 John b. Namwamba Edmund C. Merem Abena b. Asare-Ansah harriet b. yeboah Matilda Anokye Diana b. Frimpong Priscilla M. Loh Julia Atayi Judith Oppong Cynthia C. Ogbu Rechael N. D. Armah Caroline Y. Apraku Opeyemi I. Oladigbolu Joyce McClendon-Peralta 《Open Journal of Forestry》 2022年第4期479-502,共24页
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 other... 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. 展开更多
关键词 Bioenergy Production BIO-OILS Polynomial Regression Bio-Products Forest Residues Logging Residues Wood Wastes LOUISIANA
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Bioenergy Crops as a Promising Alternative to Fossil Fuels in Louisiana: A Geographic Information System (GIS) Perspective
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作者 Yaw A. Twumasi Zhu H. Ning +14 位作者 John b. Namwamba Abena b. Asare-Ansah Edmund C. Merem harriet b. yeboah Judith Oppong Matilda Anokye Diana b. Frimpong Priscilla M. Loh Julia Atayi Rechael N. D. Armah Caroline Y. Apraku Opeyemi I. Oladigbolu Cynthia C. Ogbu Leah W. Njeri Joyce McClendon-Peralta 《Journal of Sustainable Bioenergy Systems》 CAS 2022年第4期57-81,共25页
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 o... 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. 展开更多
关键词 Bioenergy Crops BIOMASS Fossil Fuel GASOLINE Geographic Information Sys-tem (GIS) Regression Analysis LOUISIANA
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Analysis of Precipitation Trends and Prediction in Selected Cities in the Southeast Louisiana
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作者 Yaw A. Twumasi John b. Namwamba +17 位作者 Zhu H. Ning Edmund C. Merem Priscilla M. Loh Abena b. Asare-Ansah Jacob b. Annan Ronald Okwemba harriet b. yeboah Caroline Y. Apraku Janeth Mjema Rechael N. D. Armah Matilda Anokye Lucinda A. Kangwana Judith Oppong Julia Atayi Cynthia C. Ogbu Opeyemi I. Oladigbolu Diana b. Frimpong Joyce McClendon-Peralta 《Atmospheric and Climate Sciences》 CAS 2022年第4期698-727,共30页
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 other... 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. 展开更多
关键词 PRECIPITATION Linear and Polynomial Regression Extrapolating Models Southeastern Louisiana
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