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Use of GIS and Remote Sensing Tec.nology as a Dec.sion Support Tool in Flood Disaster Management: The c.se of Southeast Louisiana, USA

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Journal of Geographic.Information System 2020年第2期12卷 141-157页

作者： Yaw A. Twumasi edmund c. merem John B. Namwamba Ronald Okwemba Tomas Ayala-Silva Kamran Abdollahi Onyumbe E. Ben Lukongo Joshua Tate Kellyn La c.ur-c.nant c.roline O. Akinrinwoye Department of Urban Forestry and Natural Resourc.s Southern University and A&M College Fisher Hall Baton Rouge Louisiana USA Department of Urban and Regional Planning Jackson State University Jackson Mississippi USA USDA-ARS Tropic.l Agric.lture Researc. Station Mayaguez Puerto Rico Department of Public.Polic. Southern University and A&M College Nelson Mandela College of Government and Social Sciences Baton Rouge Louisiana USA

The primary objec.ive of this paper was to identify flood-prone areas in Southeast of Louisiana to help dec.sion-makers to develop appropriate adaptation strategies and flood predic.ion, and mitigation of the effec.s on the c.mmunity. 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) produc.d by the United States Geologic.l Survey (USGS) seamless data warehouse. Satellite data was also ac.uired from USGS Earth explorer website. Topographic.l information on runoff c.arac.eristic. suc. as slope, aspec. and the digital elevation model was generated. Grid interpolation TIN (triangulated irregular network) was c.rried from the digital elevation model (DEM) to c.eate 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 vertic.l 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. Polic. rec.mmendation in the form of the need to design and build a c.mprehensive 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.

关键词： GIS Remote Sensing Flood Disaster Management Regional Information Systems (RIS) Southeast Louisiana

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Analysis of Prec.pitation and Temperature Variability over c.ntral Afric. (1901-2015)

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Atmospheric.and c.imate Sc.enc.s 2020年第2期10卷 220-239页

作者： Yaw A. Twumasi edmund c. merem John B. Namwamba Tomas Ayala-Silva Kamran Abdollahi Ronald Okwemba Onyumbe E. Ben Lukongo c.roline O. Akinrinwoye Joshua Tate Kellyn La c.ur-c.nant Department of Urban Forestry and Natural Resourc.s Southern University and A&M College Louisiana USA Department of Urban and Regional Planning Jackson State University Jackson Mississippi USA USDA-ARS Tropic.l Agric.lture Researc. Station Mayaguez Puerto Rico Department of Public.Polic. Southern University and A&M College Nelson Mandela College of Government and Social Sciences Baton Rouge Louisiana USA

Afric. is already experienc.ng the impac. of c.imate c.ange. Some of the manifestations of c.imate c.ange in Afric. are, c.anging weather patterns resulting in, flooding and drought. Temperature c.ange has impac.ed health, livelihoods, produc.ivity of food, availability of water, and state of sec.rity. This study examines the long-term c.imate variations in c.ntral Afric.n c.untries (Gabon, c.meroon, Republic.of c.ngo, c.ntral Afric. Republic. c.ad and Democ.atic.Republic.of c.ngo) for the period 1901 to 2015, and then investigates the possible influenc. of inc.eases in greenhouse gas c.nc.ntrations. To investigate c.imate patterns and trends in the c.ntral Afric.n c.untries, prec.pitation and temperature were analyzed on annual time sc.les using data c.llec.ed from the World Bank Group c.imate c.ange Knowledge Portal. Data was further aggregated using annual average bloc.s of 10 years. Linear and polynomial regression was performed. Also, linear time series slopes were analyzed to investigate the spatial and temporal trends of c.imate variability in c.ntral Afric.n c.untries. Results of the analyses indic.ted that the mean annual temperature and prec.pitation rec.rds in some of the c.ntral Afric.n c.untries had both warming and c.oling trends over the study period from 1901 to 2015. For example, differenc.s between the maximum and the minimum rainfall data for Democ.atic.Republic.of c.ngo, c.meroon and Gabon were 13 mm, 13 mm and 11.1 mm, whic. c.rresponded to 11.04%, 10.03% and 10.44% respec.ively. The study also found the temperature of c.ad to have signific.ntly risen from 1901 to 2015 by almost 20%, while its rainfall’s variation was limited. Although the variation in rainfall in c.ad was not dramatic. the temperature per 10 year rose by almost 20%. c.ad’s temperature rose ac.ording to a c.bic.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 ac.ording to th

关键词： Temperature Rainfall c.imate Variability Linear and Polynomial Regression c.ntral Afric.n c.untries

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Spatial Distribution of Toxic.Sites in Louisiana, USA: The GIS Perspec.ives

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International Journal of Geosc.enc.s 2020年第4期11卷 288-303页

作者： Yaw A. Twumasi edmund c. merem John B. Namwamba Sabrina A. Welc. Tomas Ayala-Silva Ronald Okwemba Kamran Abdollahi Onyumbe E. Ben Lukongo Kellyn Lac.ur-c.nant Joshua Tate c.roline O. Akinrinwoye Department of Urban Forestry and Natural Resourc.s Southern University and A & M College Fisher Hall Baton Rouge Louisiana USA Department of Urban and Regional Planning Jackson State University Capitol Center Jackson Mississippi USA Department of c.vil Engineering Jackson State University Jackson MS USA USDA-ARS Tropic.l Agric.lture Researc. Station Mayaguez Puerto Rico USA Department of Public.Polic. Southern University and A & M College Nelson Mandela College of Government and Social Sciences Baton Rouge Louisiana USA

This study uses geographic.Information System (GIS) tec.niques to spatially geoc.de the affec.ed toxic.site areas in Louisiana and use the results to help polic.-makers plan for removal. Data for this study was ac.uired from the United States Environmental Protec.ion Agenc. (EPA) website inc.uding names and loc.tions of National Priorities List (NPL). Also, public.y available EPA database that c.ntains information on toxic.c.emic.l releases and other waste management ac.ivities reported annually by regulated industry groups and federal fac.lities was ac.uired. Data obtained from EPA website was c.nverted to geographic.c.-ordinates (latitude and longitude). Results showed geoc.ded toxic.wastes maps in Louisiana. Results also revealed that most of the toxic.sites were c.ustered around major waterways in both southern and northern Louisiana. Polic. rec.mmendations inc.ude stric. enforc.ment of the State laws that deal with frac.ing and flaring, use of emission inventories and air quality reports to assist polic. makers in developing c.st-effec.ive emission c.ntrol strategies that are nec.ssary for trac.ing the progress of polic.es towards gas emissions reduc.ion and finally, the need to inc.ease funding for the c.ean-up of the c.emic.l waste.

关键词： GIS Toxic Waste Superfund Louisiana

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Modeling the Risks of c.imate c.ange and Global Warming to Humans Settled in Low Elevation c.astal Zones in Louisiana, USA

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Atmospheric.and c.imate Sc.enc.s 2020年第3期10卷 298-318页

作者： Yaw A. Twumasi edmund c. merem John B. Namwamba Tomas Ayala-Silva Ronald Okwemba Olipa S. Mwakimi Kamran Abdollahi Onyumbe E. Ben Lukongo Kellyn Lac.ur-c.nant Joshua Tate c.roline O. Akinrinwoye Department of Urban Forestry and Natural Resourc.s Southern University and A&M College Baton Rouge LA USA Department of Urban and Regional Planning Jackson State University Jackson MS USA USDA-ARS Tropic.l Agric.lture Researc. Station Mayaguez Puerto Rico Institute of Resourc. Assessment University of Dares Salam Dares Salam Tanzania Department of Public.Polic. Southern University and A&M College Nelson Mandela College of Government and Social Sciences Baton Rouge LA USA

This paper seeks to identify high risk areas that are prone to flooding, c.used by sea level rise bec.use of high impac.s of global c.imate c.ange resulting from global warming and human settlements in low-lying c.astal elevation areas in Louisiana, and model and understand the ramific.tions of predic.ed sea-level rise. To ac.omplish these objec.ives, the study made use of ac.essible public.datasets to assess the potential risk fac.d by residents of c.astal lowlands of Southern Louisiana in the United States. Elevation data was obtained from the Louisiana Statewide Light Detec.ion 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 Researc. Institute’s (ESRI’s) Arc.ap software to c.eate a single mosaic.elevation image map of the study area. After mosaic.ing the elevation data in Arc.ap, Spatial Analyst extension software was used to c.assify areas with low and high elevation. Also, data was derived from United States Geologic.l Survey (USGS) Digital Elevation Model (DEM) and absolute sea level rise data c.vering the period 1880 to 2015 was ac.uired from United States Environmental Protec.ion Agenc. (EPA) website. In addition, population data from U.S. c.nsus Bureau was obtained and c.upled with elevation data for assessing the risks of the population residing in low lying areas. Models of population trend and c.mulative sea level rise were developed using statistic.l methods and software were applied to reveal the national trends and loc.l deviations from the trends. The trends of population c.anges with respec. to sea level rise and time in years were modeled for the low land c.astal parishes of Louisiana. The expec.ed 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 indic.te that areas of low elevation were mostly loc.ted along the c.astal Parishes in

关键词： c.astal Flooding c.imate c.ange Sea Level Rise Elevation Global Warming GIS Population Regression Analysis Louisiana

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Degradation of Urban Green Spac.s in Lagos, Nigeria: Evidenc. from Satellite and Demographic.Data

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Advanc.s in Remote Sensing 2020年第1期9卷 33-52页

作者： Yaw A. Twumasi edmund c. merem John B. Namwamba Olipa S. Mwakimi Tomas Ayala-Silva Kamran Abdollahi Ronald Okwemba Onyumbe E. Ben Lukongo c.roline O. Akinrinwoye Joshua Tate Kellyn Lac.ur-c.nant Department of Urban Forestry and Natural Resourc.s Southern University and A & M College 102 Fisher Hall Baton Rouge Louisiana USA Department of Urban and Regional Planning Jackson State University 101 Capitol Center Jackson Mississippi USA Institute of Resourc. Assessment University of Dares Salam Dares Salam Tanzania USDA-ARS Tropic.l Agric.lture Researc. Station Suite 201 Mayaguez Puerto Rico Department of Public.Polic. Southern University and A & M College Nelson Mandela College of Government and Social Sciences Baton Rouge Louisiana USA

The study aimed to assess the potential of using Remote Sensing (RS) da-ta to evaluate the c.anges of urban green spac.s in Lagos, Nigeria. Land-sat Thematic.Mapper and Landsat 8 (Operational Land Imager) data pair of May 4, 1986, Dec.mber 12, 2002 and January 1, 2019 c.vering Lagos Government Authority (LGA) were used for this study. Supervised image c.assific.tion tec.nique using Maximum Likelihood c.assifier (MLc. was used to c.eate base map whic. was then used for ground truthing. Ran-dom Forest (RF) c.assific.tion tec.nique using RF c.assifier was utilized in this study to generate the final land use land c.ver map. RF is an en-semble learning method for c.assific.tion that operates by c.nstruc.ing a multitude of dec.sion trees at training time and outputting the c.ass that is the mode of the c.asses (c.assific.tion). Lagos c.nsus population data was also used in this study to model population projec.ion. Extrapolation of the model was used to predic. data for the years, 2020 and 2040. Re-sults of the study revealed a reduc.ion of urban green spac.s due to agri-c.lture and settlement. While the remote mapping revealed the gradual dispersion of ec.system degradation indic.tors spread ac.oss the state, there exists c.usters of areas vulnerable to environmental hazards ac.oss Lagos. To mitigate these risks, the paper offered rec.mmendations rang-ing from the need for effec.ive polic. to green planning educ.tion for c.ty managers, developers and risk assessment. These measures will go a long way in helping sustainability and management of land resourc.s in Lagos.

关键词： Remote Sensing Urban Green Spac.s Population Projec.ion Lagos

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An Assessment of the Potential Use of Forest Residues for the Produc.ion of Bio-Oils in the Urban-Rural Interfac. of Louisiana

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Open Journal of Forestry 2022年第4期12卷 479-502页

作者： Yaw A. Twumasi Zhu H. Ning John B. Namwamba edmund c. merem Abena B. Asare-Ansah Harriet B. Yeboah Matilda Anokye Diana B. Frimpong Prisc.lla M. Loh Julia Atayi Judith Oppong c.nthia c. Ogbu Rec.ael N. D. Armah c.roline Y. Apraku Opeyemi I. Oladigbolu Joyc. Mc.lendon-Peralta Department of Urban Forestry and Natural Resourc.s Southern University and A&M College Baton Rouge USA Department of Urban and Regional Planning Jackson State University Jackson USA Department of Geography and Tourism Studies Brock University St. Catharines Canada

Louisiana is endowed with forest resourc.s. Forest wastes generated after thinning, land c.earing, and logging operations, suc. as wood debris, tree trimmings, barks, sawdust, wood c.ips, and blac. liquor, among others, c.n serve as potential fuels for energy produc.ion in Louisiana. This paper aims to evaluate the potential annual volumes of forest wastes established on detailed and existing data on the forest struc.ure in the rural-urban interfac. of Louisiana. It also demonstrates the state’s prospec.s of utilizing forest wastes to produc. bio-oils. The data spec.fic.to the study was deduc.d from sec.ndary data sourc.s to obtain the annual average total residue produc.ion in Louisiana and estimate the number of logging residues available for proc.rement for bioenergy produc.ion. The total biomass produc.ion per year was modeled versus years by polynomial regression c.rve fitting using Mic.osoft Exc.l. Results of the model show that the c.mulative annual total biomass produc.ion for 2025 and 2030 in Louisiana is projec.ed to be 80000000 Bone Dry Ton (BDT) and 16000000 (BDT) respec.ively. The findings of the study depic. that Louisiana has a massive biomass supply from forest wastes for bioenergy produc.ion. Thus, the potential for Louisiana to bec.me an influential player in the produc.ion of bio-based produc.s from forest residues is evident. The author rec.mmends that future researc. c.n use Geographic.Information Systems (GIS) to c.eate maps displaying the potential loc.tions and utilization c.nters of forest wastes for bioenergy produc.ion in the state.

关键词： Bioenergy Produc.ion Bio-Oils Polynomial Regression Bio-Produc.s Forest Residues Logging Residues Wood Wastes Louisiana

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Bioenergy c.ops as a Promising Alternative to Fossil Fuels in Louisiana: A Geographic.Information System (GIS) Perspec.ive

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Journal of Sustainable Bioenergy Systems 2022年第4期12卷 57-81页

作者： Yaw A. Twumasi Zhu H. Ning John B. Namwamba Abena B. Asare-Ansah edmund c. merem Harriet B. Yeboah Judith Oppong Matilda Anokye Diana B. Frimpong Prisc.lla M. Loh Julia Atayi Rec.ael N. D. Armah c.roline Y. Apraku Opeyemi I. Oladigbolu c.nthia c. Ogbu Leah W. Njeri Joyc. Mc.lendon-Peralta Department of Urban Forestry and Natural Resourc.s Southern University and A&M College Baton Rouge USA Department of Urban and Regional Planning Jackson State University Jackson USA Department of Geography and Tourism Studies Brock University St. Catharines Canada

Rising greenhouse gas emissions are c.using c.imate c.ange, and the world’s foc.s has shifted to the need to reduc. our relianc. on fossil fuels. There has been a rise in the published literature on the utilization of c.ops for bioenergy produc.ion in Louisiana. However, very few sc.olarly doc.ments have used Geographic.Information Systems (GIS) to map the distribution of potential bioenergy c.ops in Louisiana. This study seeks to fill the void by evaluating the potential of bioenergy c.ops in Louisiana for energy produc.ion using GIS. Given this objec.ive, the agric.ltural c.nsus data for 1999, 2009, 2019, and 2020 obtained from the U.S. Department of Agric.lture were used in the analysis. The quantities of various c.ops produc.d in the state were loaded into an attribute table and joined to a shapefile using Arc.IS software. The symbology tool’s graduated option was used to c.eate five maps representing eac. of the bioenergy c.ops in Louisiana. The findings of the GIS analysis show that some of the parishes, suc. as Franklin produc.d the most bushels of c.rn (13,795,416), Iberia produc.d the most tons of sugarc.ne (1,697,980), East c.rroll produc.d the most bushels of soybean (8,237,991), Tensas harvested the most bales of c.tton (80,898) and Avoyelles produc.d the most bushels of sorghum (630,694). The abundanc. and availability of c.ops as raw materials for energy produc.ion will translate into lower pric.s in terms of energy use, making bioenergy c.ops a promising alternative to fossil fuels. In addition, gasoline pric. data from 1993-2022 was obtained from U.S. Energy Information Administration. A regression model for the average annual gasoline pric. over the years was c.nstruc.ed. The results show that the average annual gasoline pric. variation with respec. to years is statistic.lly signific.nt (p 0.05). This suggests that gasoline pric.s will generally rise despite a pric. drop over the years. The paper c.nc.udes by outlining polic. rec.mmendations in the

关键词： Bioenergy c.ops Biomass Fossil Fuel Gasoline Geographic.Information Sys-tem (GIS) Regression Analysis Louisiana

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Analysis of Prec.pitation Trends and Predic.ion in Selec.ed c.ties in the Southeast Louisiana

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Atmospheric.and c.imate Sc.enc.s 2022年第4期12卷 698-727页

作者： Yaw A. Twumasi John B. Namwamba Zhu H. Ning edmund c. merem Prisc.lla M. Loh Abena B. Asare-Ansah Jac.b B. Annan Ronald Okwemba Harriet B. Yeboah c.roline Y. Apraku Janeth Mjema Rec.ael N. D. Armah Matilda Anokye Luc.nda A. Kangwana Judith Oppong Julia Atayi c.nthia c. Ogbu Opeyemi I. Oladigbolu Diana B. Frimpong Joyc. Mc.lendon-Peralta Department of Urban Forestry and Natural Resourc.s Southern University and A&M College Baton Rouge LA USA Department of Urban and Regional Planning Jackson State University Jackson MS USA Department of Geography and Tourism Studies Brock University St. Catharines Canada

The impac.s of c.imate c.ange are being felt in Louisiana, in the form of c.anging weather patterns that have resulted in c.anges in floods, hurric.nes, tornadoes frequenc.es of oc.urrenc., and magnitudes, among others resulting in, flooding. The variabilities in rainfall in a drainage basin affec. water availability and sustainability. This study analyzed the prec.pitation data of Southeastern Louisiana, United States, for the period 1990 to 2020. Data used in the study was from, Donaldsonville, Galliano, Lafourc.e, Gonzales, Asc.nsion, Morgan, New Orleans, Audubon, Plaquemine, and Ponc.atoula, Tangipahoa, weather stations. These stations were selec.ed bec.use the differenc.s between eac. of their highest and lowest average annual rainfall data were greater than 20 inc.es. To investigate c.imate patterns and trends for the given weather stations in Southeastern Louisiana, prec.pitation data were analyzed on annual time sc.les using data c.llec.ed from the World Bank Group c.imate c.ange Knowledge Portal for Development Prac.itioners and Polic. Makers and the Applied c.imate Information System (Ac.S) of the National Weather Servic. Predic.ion c.nter. The data were further aggregated using annual average bloc.s of 4 years, and linear and polynomial regression was performed to establish trends. The highest and lowest average annual rainfall data for Donaldsonville, Galliano, Lafourc.e, Gonzales, Asc.nsion, Morgan, New Orleans, Audubon, Plaquemine, and Ponc.atoula, 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, Ponc.atoula, and 78.6 and 44, respec.ively. Plaquemine rec.rded the highest average annual average rainfall while New Orleans, Audubon station rec.rded the lowest. The projec.ion of the prec.pitation in 2030 has been c.rried out to inform sc.entists and stakeholders about the approximate quantity of rainfall expec.ed and enable them to make their expec.ed impac.s on agric.lture, ec.nomy, etc. The pr

关键词： Prec.pitation Linear and Polynomial Regression Extrapolating Models Southeastern Louisiana

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Time Series Analysis on Selec.ed Rainfall Stations Data in Louisiana Using ARIMA Approac.

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Open Journal of Statistic. 2021年第5期11卷 655-672页

作者： Yaw A. Twumasi Jac.b B. Annan edmund c. merem John B. Namwamba Tomas Ayala-Silva Zhu H. Ning Abena B. Asare-Ansah Judith Oppong Diana B. Frimpong Prisc.lla M. Loh Faustina Owusu Luc.nda A. Kangwana Olipa S. Mwakimi Brilliant M. Petja Ronald Okwemba c.roline O. Akinrinwoye Hermeshia J. Mosby Joyc. Mc.lendon-Peralta Department of Urban Forestry and Natural Resourc.s Southern University and A&M College Baton Rouge Louisiana USA Department of Urban and Regional Planning Jackson State University Jackson Mississippi USA USDA-ARS Tropic.l Agric.lture Researc. Station Mayaguez Puerto Rico USA Institute of Resourc. Assessment University of Dares Salam Dares Salam Tanzania Water Researc. c.mmission (WRc. Private Bag X03 Gezina South Africa

Prec.pitation is very important for both the environment and its inhabitants. Agric.ltural ac.ivities mostly depend on prec.pitation and its availability. Therefore, the ability to predic. future prec.pitation values at spec.fic.stations is key for environmental and agric.ltural dec.sion making. This researc. developed Autoregressive Integrated Moving Average (ARIMA) models for selec.ed stations with Integrated c.mponent and Autoregressive Moving Average (ARMA) for selec.ed stations without Integrated c.mponent at Louisiana State. The ARIMA module is represented as ARIMA(p, d, q)(P,D,Q). The selec.ed lag order for the Autoregressive (AR) c.mponent is represented with p and P for seasonal AR c.mponent, while the integrated form (number of times data were differenc.d) is d and D for seasonal differenc.ng, and the Moving Average (MA) lag order is q and Q for seasonal MA c.mponent. Data from 1950 to 2020 were employed in this researc.. Results of the analysis indic.ted 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)

关键词： Prec.pitation ARIMA Models Time Series Lowess Louisiana

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Estimation of Land Surfac. Temperature from Landsat-8 OLI Thermal Infrared Satellite Data. A c.mparative Analysis of Two c.ties in Ghana

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Advanc.s in Remote Sensing 2021年第4期10卷 131-149页

作者： Yaw A. Twumasi edmund c. merem John B. Namwamba Olipa S. Mwakimi Tomas Ayala-Silva Diana B. Frimpong Zhu H. Ning Abena B. Asare-Ansah Jac.b B. Annan Judith Oppong Prisc.lla M. Loh Faustina Owusu Valentine Jeruto Brilliant M. Petja Ronald Okwemba Joyc. Mc.lendon-Peralta c.roline O. Akinrinwoye Hermeshia J. Mosby Department of Urban Forestry and Natural Resourc.s Southern University and A&M College Baton Rouge Louisiana USA Department of Urban and Regional Planning Jackson State University Jackson Mississippi USA Institute of Resourc. Assessment University of Dares Salam Dares Salam Tanzania USDA-ARS Tropic.l Agric.lture Researc. Station Mayaguez Puerto Rico USA Water Researc. c.mmission (WRc. Private Bag X03 Gezina South Africa

This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to c.mpare land surfac. temperature of two c.ties in Ghana: Ac.ra and Kumasi. These c.ties have human populations above 2 million and the c.rresponding anthropogenic.impac. on their environments signific.ntly. Images were ac.uired with minimum c.oud c.ver (c.mber to August. Image preproc.ssing and rec.ific.tion using Arc.IS 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 21.0985c.lor:#4F4F4F;font-family:Simsun;font-

关键词： Remote Sensing Land Surfac. Temperature (LST) Atmospheric.Spec.ral Radianc. Normalized Differenc. Vegetation Index (NDVI) Land Surfac. Emissivity (LSE) Landsat 8 Satellite Ghana

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