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Modeling the Risks of Climate Change and Global Warming to Humans Settled in Low Elevation Coastal Zones in Louisiana, USA
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作者 Yaw A. Twumasi Edmund C. Merem +8 位作者 John B. Namwamba Tomas Ayala-Silva Ronald Okwemba Olipa S. Mwakimi Kamran Abdollahi Onyumbe E. Ben Lukongo Kellyn LaCour-Conant joshua tate Caroline O. Akinrinwoye 《Atmospheric and Climate Sciences》 2020年第3期298-318,共21页
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 coast... 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: <em>y</em> = 6.6667<em>x</em> - 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: <em>y</em> = 0.1219<em>x</em> + 1944.1 with R square equal to 0.9995. 展开更多
关键词 Coastal Flooding Climate Change Sea Level Rise ELEVATION Global Warming GIS POPULATION Regression Analysis LOUISIANA
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Use of GIS and Remote Sensing Technology as a Decision Support Tool in Flood Disaster Management: The Case of Southeast Louisiana, USA 被引量:1
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作者 Yaw A. Twumasi Edmund C. Merem +7 位作者 John B. Namwamba Ronald Okwemba Tomas Ayala-Silva Kamran Abdollahi Onyumbe E. Ben Lukongo joshua tate Kellyn La Cour-Conant Caroline O. Akinrinwoye 《Journal of Geographic Information System》 2020年第2期141-157,共17页
The primary objective of this paper was to identify flood-prone areas in Southeast of Louisiana to help decision-makers to develop appropriate adaptation strategies and flood prediction, and mitigation of the effects ... The primary objective of this paper was to identify flood-prone areas in Southeast of Louisiana to help decision-makers to develop appropriate adaptation strategies and flood prediction, and mitigation of the effects on the community. In doing so, the paper uses satellite remote sensing and Geographic Information System (GIS) data for this purpose. Elevation data was obtained from the National Elevation Dataset (NED) produced by the United States Geological Survey (USGS) seamless data warehouse. Satellite data was also acquired from USGS Earth explorer website. Topographical information on runoff characteristics such as slope, aspect and the digital elevation model was generated. Grid interpolation TIN (triangulated irregular network) was carried from the digital elevation model (DEM) to create slope map. Image Drape was performed using ERDAS IMAGINE Virtual GIS. The output image was then draped over the NED elevation data for visualization purposes with vertical exaggeration of 16 feet. Results of the study revealed that majority of the study area lies in low-lying and very low-lying terrain below sea level. Policy recommendation in the form of the need to design and build a comprehensive Regional Information Systems (RIS) in the form of periodic inventorying, monitoring and evaluation with full support of the governments was made for the study area. 展开更多
关键词 GIS Remote Sensing FLOOD DISASTER MANAGEMENT Regional Information Systems (RIS) SOUTHEAST LOUISIANA
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Spatial Distribution of Toxic Sites in Louisiana, USA: The GIS Perspectives 被引量:1
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作者 Yaw A. Twumasi Edmund C. Merem +8 位作者 John B. Namwamba Sabrina A. Welch Tomas Ayala-Silva Ronald Okwemba Kamran Abdollahi Onyumbe E. Ben Lukongo Kellyn LaCour-Conant joshua tate Caroline O. Akinrinwoye 《International Journal of Geosciences》 2020年第4期288-303,共16页
This study uses geographic Information System (GIS) techniques to spatially geocode the affected toxic site areas in Louisiana and use the results to help policy-makers plan for removal. Data for this study was acquir... This study uses geographic Information System (GIS) techniques to spatially geocode the affected toxic site areas in Louisiana and use the results to help policy-makers plan for removal. Data for this study was acquired from the United States Environmental Protection Agency (EPA) website including names and locations of National Priorities List (NPL). Also, publicly available EPA database that contains information on toxic chemical releases and other waste management activities reported annually by regulated industry groups and federal facilities was acquired. Data obtained from EPA website was converted to geographic co-ordinates (latitude and longitude). Results showed geocoded toxic wastes maps in Louisiana. Results also revealed that most of the toxic sites were clustered around major waterways in both southern and northern Louisiana. Policy recommendations include strict enforcement of the State laws that deal with fracking and flaring, use of emission inventories and air quality reports to assist policy makers in developing cost-effective emission control strategies that are necessary for tracking the progress of policies towards gas emissions reduction and finally, the need to increase funding for the clean-up of the chemical waste. 展开更多
关键词 GIS TOXIC Waste SUPERFUND LOUISIANA
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Analysis of Precipitation and Temperature Variability over Central Africa (1901-2015) 被引量:1
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作者 Yaw A. Twumasi Edmund C. Merem +7 位作者 John B. Namwamba Tomas Ayala-Silva Kamran Abdollahi Ronald Okwemba Onyumbe E. Ben Lukongo Caroline O. Akinrinwoye joshua tate Kellyn La Cour-Conant 《Atmospheric and Climate Sciences》 2020年第2期220-239,共20页
Africa is already experiencing the impact of climate change. Some of the manifestations of climate change in Africa are, changing weather patterns resulting in, flooding and drought. Temperature change has impacted he... Africa is already experiencing the impact of climate change. Some of the manifestations of climate change in Africa are, changing weather patterns resulting in, flooding and drought. Temperature change has impacted health, livelihoods, productivity of food, availability of water, and state of security. This study examines the long-term climate variations in Central African Countries (Gabon, Cameroon, Republic of Congo, Central Africa Republic, Chad and Democratic Republic of Congo) for the period 1901 to 2015, and then investigates the possible influence of increases in greenhouse gas concentrations. To investigate climate patterns and trends in the Central African Countries, precipitation and temperature were analyzed on annual time scales using data collected from the World Bank Group Climate Change Knowledge Portal. Data was further aggregated using annual average blocks of 10 years. Linear and polynomial regression was performed. Also, linear time series slopes were analyzed to investigate the spatial and temporal trends of climate variability in Central African countries. Results of the analyses indicated that the mean annual temperature and precipitation records in some of the Central African Countries had both warming and cooling trends over the study period from 1901 to 2015. For example, differences between the maximum and the minimum rainfall data for Democratic Republic of Congo, Cameroon and Gabon were 13 mm, 13 mm and 11.1 mm, which corresponded to 11.04%, 10.03% and 10.44% respectively. The study also found the temperature of Chad to have significantly risen from 1901 to 2015 by almost 20%, while its rainfall’s variation was limited. Although the variation in rainfall in Chad was not dramatic, the temperature per 10 year rose by almost 20%. Chad’s temperature rose according to a cubic model from about 24.5°C to just below 27°C during the period 1901-1940. This was followed by a brief drop between 1940 and 1960. From 1960 to 2015 it rose according to the model to almost 28°C. By 2040 the temperature is expected to reach about 29.5°C if this trend continues. Gabon was found to be the wettest country in Central Africa. Between 1901 and 1960, its average rainfall rose from about 144 mm to a maximum of approximately 160 mm. It had a general average rainfall/10 year’s increase from 1901 to 2015. The paper concludes by outlining policy recommendations in the form of improving national and regional environmental policies and regulations in the region, community involvement in decision making processes both at local and the national levels so as to contribute their input in the daily management of the forest resources, poverty alleviation in the region as well as building regional information system (RIS) incorporating Geographic Information System (GIS), remote sensing and other environmental and socio-economic data to help reduce anthropogenic emissions of greenhouse gases. 展开更多
关键词 Temperature RAINFALL CLIMATE VARIABILITY Linear and POLYNOMIAL Regression Central AFRICAN COUNTRIES
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Degradation of Urban Green Spaces in Lagos, Nigeria: Evidence from Satellite and Demographic Data
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作者 Yaw A. Twumasi Edmund C. Merem +8 位作者 John B. Namwamba Olipa S. Mwakimi Tomas Ayala-Silva Kamran Abdollahi Ronald Okwemba Onyumbe E. Ben Lukongo Caroline O. Akinrinwoye joshua tate Kellyn LaCour-Conant 《Advances in Remote Sensing》 2020年第1期33-52,共20页
The study aimed to assess the potential of using Remote Sensing (RS) da-ta to evaluate the changes of urban green spaces in Lagos, Nigeria. Land-sat Thematic Mapper and Landsat 8 (Operational Land Imager) data pair of... The study aimed to assess the potential of using Remote Sensing (RS) da-ta to evaluate the changes of urban green spaces in Lagos, Nigeria. Land-sat 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. Ran-dom Forest (RF) classification technique using RF classifier was utilized in this study to generate the final land use land cover map. RF is an en-semble 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. Re-sults of the study revealed a reduction of urban green spaces due to agri-culture 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 rang-ing from the need for effective policy to green planning education for city managers, developers and risk assessment. These measures will go a long way in helping sustainability and management of land resources in Lagos. 展开更多
关键词 Remote Sensing Urban Green SPACES POPULATION PROJECTION LAGOS
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