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Статті в журналах з теми "Sub-Saharan Remote sensing":

1
Marshall, M., K. Tu, C. Funk, J. Michaelsen, P. Williams, C. Williams, J. Ardö, et al. "Combining surface reanalysis and remote sensing data for monitoring evapotranspiration." Hydrology and Earth System Sciences Discussions 9, no. 2 (February 2012): 1547–87. http://dx.doi.org/10.5194/hessd-9-1547-2012.
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Abstract. Climate change is expected to have the greatest impact on the world's poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled actual evapotranspiration (AET), a key input in continental-scale hydrologic models. In this study, a model driven by dynamic canopy AET was combined with the Global Land Data Assimilation System realization of the NOAH Land Surface Model (GNOAH) wet canopy and soil AET for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against AET from the GNOAH model and dynamic model using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance are at humid sites with dense vegetation, while performance at semi-arid sites is poor, but better than individual models. The reduction in errors using the hybrid model can be attributed to the integration of a dynamic vegetation component with land surface model estimates, improved model parameterization, and reduction of multiplicative effects of uncertain data.
2
Sibanda, Mbulisi, Timothy Dube, Khoboso Seutloali, and Samuel Adelabu. "Operational applications of remote sensing in groundwater mapping across sub-Saharan Africa." Transactions of the Royal Society of South Africa 70, no. 2 (March 2015): 173–79. http://dx.doi.org/10.1080/0035919x.2015.1017024.
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3
Dube, T., O. Mutanga, K. Seutloali, S. Adelabu, and C. Shoko. "Water quality monitoring in sub-Saharan African lakes: a review of remote sensing applications." African Journal of Aquatic Science 40, no. 1 (January 2015): 1–7. http://dx.doi.org/10.2989/16085914.2015.1014994.
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4
Ebhuoma, Osadolor, and Michael Gebreslasie. "Remote Sensing-Driven Climatic/Environmental Variables for Modelling Malaria Transmission in Sub-Saharan Africa." International Journal of Environmental Research and Public Health 13, no. 6 (June 2016): 584. http://dx.doi.org/10.3390/ijerph13060584.
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Marshall, M., K. Tu, C. Funk, J. Michaelsen, P. Williams, C. Williams, J. Ardö, et al. "Improving operational land surface model canopy evapotranspiration in Africa using a direct remote sensing approach." Hydrology and Earth System Sciences 17, no. 3 (March 2013): 1079–91. http://dx.doi.org/10.5194/hess-17-1079-2013.
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Abstract. Climate change is expected to have the greatest impact on the world's economically poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled evapotranspiration (ET), a key input in continental-scale hydrologic models. In this study, a remote sensing model of transpiration (the primary component of ET), driven by a time series of vegetation indices, was used to substitute transpiration from the Global Land Data Assimilation System realization of the National Centers for Environmental Prediction, Oregon State University, Air Force, and Hydrology Research Laboratory at National Weather Service Land Surface Model (GNOAH) to improve total ET model estimates for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against GNOAH ET and the remote sensing method using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance were at humid sites with dense vegetation, while performance at semi-arid sites was poor, but better than the models before hybridization. The reduction in errors using the hybrid model can be attributed to the integration of a simple canopy scheme that depends primarily on low bias surface climate reanalysis data and is driven primarily by a time series of vegetation indices.
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Yiran, Gerald Albert Baeribameng, Austin Dziwornu Ablo, Freda Elikplim Asem, and George Owusu. "Urban Sprawl in sub-Saharan Africa: A review of the literature in selected countries." Ghana Journal of Geography 12, no. 1 (July 2020): 1–28. http://dx.doi.org/10.4314/gjg.v12i1.1.
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Urban sprawl has gained popularity in academic discourse in recent times, but the majority of the research was conducted in developed countries. There is a marginal body of works on the character and nature of urban sprawl in Sub-Saharan Africa (SSA), although the region isexperiencing one of the fastest rates of sprawl. Urbanisation in SSA is very rapid, and in addition to the emerging challenges of globalisation, climate change and poverty, SSA cities have an enormous task to manage urban sprawl. This paper reviews the literature on urban sprawl in SSAto identify research gaps and propose a research agenda. Published articles from five Anglophone countries in three of the four regional blocks in SSA were selected. The literature was organised into the causes and effects of urban sprawl and showed that the previous research on the subjectfocused mainly on its environmental impacts. Few studies have looked at the effects of sprawl on rural livelihoods, agriculture and food security considering the challenges of global climate change and poverty. Other studies have used Remote Sensing and Geographic InformationSystems, but these were conducted largely for change detection. The paper recommends the deployment of a more comprehensive methodology incorporating remote sensing/GIS with ethnographic methods to capture better the complexity and impacts of urban sprawl in SSA.Additionally, further research attention must be paid to the effects of urban sprawl on rural livelihoods and overall sprawl-induced agrarian change.
7
Jacob, Benjamin G., Robert J. Novak, Laurent D. Toe, Moussa Sanfo, Daniel A. Griffith, Thomson L. Lakwo, Peace Habomugisha, Moses N. Katabarwa, and Thomas R. Unnasch. "Validation of a Remote Sensing Model to Identify Simulium damnosum s.l. Breeding Sites in Sub-Saharan Africa." PLoS Neglected Tropical Diseases 7, no. 7 (July 2013): e2342. http://dx.doi.org/10.1371/journal.pntd.0002342.
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Djurfeldt, Göran, Ola Hall, Magnus Jirström, Maria Archila Bustos, Björn Holmquist, and Sultana Nasrin. "Using panel survey and remote sensing data to explain yield gaps for maize in sub-Saharan Africa." Journal of Land Use Science 13, no. 3 (May 2018): 344–57. http://dx.doi.org/10.1080/1747423x.2018.1511763.
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Buck, Paul E., Donald E. Sabol, and Alan R. Gillespie. "Sub-pixel artifact detection using remote sensing." Journal of Archaeological Science 30, no. 8 (August 2003): 973–89. http://dx.doi.org/10.1016/s0305-4403(02)00284-4.
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Christopher, Sundar A., and Thomas A. Jones. "Satellite and surface-based remote sensing of Saharan dust aerosols." Remote Sensing of Environment 114, no. 5 (May 2010): 1002–7. http://dx.doi.org/10.1016/j.rse.2009.12.007.
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Дисертації з теми "Sub-Saharan Remote sensing":

1
Symeonakis, Elias. "Soil erosion modelling over sub Saharan Africa using remote sensing and geographical information systems." Electronic Thesis or Dissertation, King's College London (University of London), 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.248386.
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Stephen, Haroon. "Microwave Remote Sensing of Saharan Ergs and Amazon Vegetation." Text, BYU ScholarsArchive, 2007. https://scholarsarchive.byu.edu/etd/495.
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This dissertation focuses on relating spaceborne microwave data to the geophysical characteristics of the Sahara desert and the Amazon vegetation. Radar and radiometric responses of the Saharan ergs are related to geophysical properties of sand formations and near surface winds. The spatial and temporal variability of the Amazon vegetation is studied using multi-frequency and multi-polarization data. The Sahara desert includes large expanses of sand dunes called ergs that are constantly reshaped by prevailing winds. Radar backscatter measurements observed at various incidence and azimuth angles from the NASA Scatterometer (NSCAT), the ERS scatterometer (ESCAT), the SeaWinds scatterometer aboard QuikScat (QSCAT), and the Precipitation Radar (TRMM-PR) aboard the Tropical Rain Monitoring Mission (TRMM) are used to model the backscatter response from sand dunes. Backscatter incidence and azimuth angle variation depends upon the slopes and orientations of the dune slopes. Sand dunes are modeled as a composite of tilted rough facets, which are characterized by a probability distribution of tilt. The small ripples are modeled as cosinusoidal surface waves that contribute to the return signal at Bragg angles. The backscatter response is high at look angles equal to the mean tilts of the rough facets and is lower elsewhere. The modeled backscatter response is similar to NSCAT and ESCAT observations. Backscatter also varies spatially and reflects the spatial inhomogeneity of the sand surface. A model incorporating the backscatter azimuth modulation and spatial inhomogeneity is proposed. The maxima of the azimuth modulation at 33 degrees incidence angle reflect the orientation of the slip-sides on the sand surface. These slip-side orientations are consistent with the European Centre for Medium-Range Weather Forecasts wind directions spatially and temporally. Radiometric emissions from the ergs have strong dependence on the surface geometry. The radiometric temperature (Tb) of ergs is modeled as the weighted sum of the Tb from all the composite tilted rough facets. The dual polarization Tb measurements at 19 GHz and 37 GHz from the Special Sensor Microwave Imager (SSM/I) aboard the Defense Meteorological Satellite Program and the Tropical Rainfall Measuring Mission Microwave Imager are used to analyze the radiometric response of erg surfaces and compared to the model results. It is found that longitudinal and transverse dune fields are differentiable based on their polarization difference azimuth modulation, which reflects type and orientation of dune facets. Polarization difference at 19 GHz and 37 GHz provide consistent results. In the Amazon, backscatter measurements from Seasat A scatterometer (SASS), ESCAT, NSCAT, QSCAT and TRMM-PR; and Tb measurements from SSM/I are used to study the multi-spectral microwave response of vegetation. Backscatter versus incidence angle signatures of data combined from scatterometers and the precipitation radar depend upon vegetation density. The multi-frequency signatures of backscatter and Tb provide unique responses for different vegetation densities. Backscatter and Tb spatial inhomogeneity is related to spatial geophysical characteristics. Temporal variability of the Amazon basin is studied using C-band ERS data and a Ku-band time series formed by SASS, NSCAT and QSCAT data. Although the central Amazon forest represents an area of very stable radar backscatter measurements, portions of the southern region exhibit backscatter changes over the past two decades.
3
Forget, Yann. "Mapping 20 Years of Urbanization in Sub-Saharan Africa from Space: An approach based on multi-sensor satellite imagery and volunteered geographic information." DoctoralThesis, Universite Libre de Bruxelles, 2005. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/305158.
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Between 2015 and 2050, half of the net increase in the world's urban populationis expected to take place in Sub-Saharan Africa (SSA), driving drastic landcover changes and challenging the spatial organization of human societies.Understanding past and present dynamics of this urbanization process is criticalto achieve a sustainable pattern of urban development, yet is limited by thelack of accurate and multi-temporal spatial data on urban expansion. Since the2000s, the rise of satellite-based Earth Observation (EO) enabled the productionof several global urban maps, thereby mitigating the issue of data scarcity. ButSSA is still characterized by lower accuracies in satellite-based maps becauseof various issues, such as: a lower satellite imagery availability, a lack ofreference datasets, and a high heterogeneity across the urban areas of theregion.In this thesis, I propose to leverage open-access satellite catalogs along withvolunteered geographic information to improve large-scaled and automated mappingof the built environment in SSA. The proposed approach makes use ofOpenStreetMap to support model training and calibration, thereby bypassing theneed for reference datasets or manual digitization campaigns. This method wasassessed in 10 urban areas of SSA, reaching classification performances similarto manual approaches.Moreover, the combined use of multispectral and synthetic-aperture radar (SAR)imagery was explored. In 11 out of 12 case studies in SSA, multi-sensorclassification schemes outperformed single-sensor approaches. More specifically,multi-sensor classification dramatically increased built-up detection rates inarid and semi-arid regions---where bare soil and buildings may share a similarspectral signature.These findings were implemented to map the built environment of 46 urban areasat five different dates from 1995 to 2015, with an average F1-score of 0.93. Thestatistical interpretation of the produced dataset revealed the highheterogeneity that characterizes urban areas in SSA, and confirmed that thespatial patterns of urbanization highly depends on demographic and economicfactors. Overall, the present thesis provides promising insights for large-scaled andautomated mapping of the built environment in data-scarce regions. Severalissues are still affecting the mapping accuracies, such as: multi-temporalinconsistencies caused by the use of imagery from 7 different sensors, lowavailability of historical imagery in SSA, or missing data in OpenStreetMap.Still, with the growing availability of open-access EO catalogs and theincreasingly completeness of OpenStreetMap, the proposed approach is expected tobecome even more relevant in the near future.
Doctorat en Sciences agronomiques et ingénierie biologique
info:eu-repo/semantics/nonPublished
4
Schepanski, Kerstin [Verfasser]. "Characterising Saharan dust sources and export using remote sensing and regional modelling / Kerstin Schepanski." Online-Ressource, Kiel : Universitätsbibliothek Kiel, 2009. http://d-nb.info/1019811358/34.
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Abushufa, Tarek. "Evaluating different remote sensing techniques for detection of Saharan dust and characterisation of dust sources." Electronic Thesis or Dissertation, King's College London (University of London), 2012. https://kclpure.kcl.ac.uk/portal/en/theses/evaluating-different-remote-sensing-techniques-for-detection-of-saharan-dust-and-characterisation-of-dust-sources(c3e6c6f3-3483-4d92-8b37-c728474d3f7c).html.
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Mineral dust aerosols play an important role in climate and the Earth's energy budget. However, the nature and complexity of dust sources is poorly understood. Traditional techniques used for mapping the Sahara dust sources like the analysis of surface dust observations, back trajectory analysis of isobar data, and mineral tracers all tell a different story regarding the location of dust sources, they only agree that the Bodélé Depression and western Hoggar Mountains are important sources. Remote sensing techniques have more recently been used to identify Saharan dust sources and the different methods provide more agreement about more Saharan dust sources and also identify the Bodélé Depression and the western Hoggar Mountains as important source of dust. While there are several remote sensing techniques that can be used to identify desert dust sources yet no comprehensive comparison has yet been done to evaluate their utility. This thesis has evaluated the utility of nine different methods that can be employed to detect dust using MODIS have been investigated by comparing them to sun-photometer aerosol optical thickness (AOT) measurements at a wavelength of 1020μm from Banizoumbou (Niger). The five established techniques that were evaluated, these were: Ackerman (1989), Miller (2003), Handley (2004), Hansell et al., (2007) and the Deep Blue NASA aerosol product Hsu et al., (2003). Many of these methods employ brightness temperature differences (BTD). To determine the effectiveness of this approach all possible MODIS BTD’s were computed and evaluated, these were: BTD (12 μm-11 μm), BTD (3.7 μm-12 μm), BTD (8.6 μm-11 μm), and BTD (8.6 μm-12 μm). To evaluate the accuracy of these dust indices the correlation between the sun-photometer AOT and the result of each MODIS dust index were determined. The results show that the Deep Blue Algorithm gives the highest correlation (R²= 0.91), however the deep blue product has a 10km spatial resolution and thus is not good at locating dust sources, the ultimate aim of this project, furthermore the cloud mask applied to the product routinely masks out most of the dust. The other methods all have a spatial resolution of 1km and thus are more appropriate for this purpose. Of these methods the Ackerman (1989) shows a high R2 value (R²= 0.71) as do many other methods. The effect of different surface materials on dust detection was evaluate by studying five different backgrounds in order to see how the dust can be distinguished from these backgrounds using the M test. Over Limestone background, Miller (2003) has got the highest M value followed by Deep Blue and Ackerman (1989), excluding Deep Blue due to the poor cloud mask and visually difficult to trace the dust to their sources, Ackerman (1989) comes second and has an M value close to Miller (2003). However, Ackerman (1989) shows the best result visually. Based on the five tested backgrounds result using different techniques (visually, M test, and statistically) Deep Blue, Miller, and Ackerman present reasonable results. Based on these results Ackerman (1989) was selected to detect the dust sources over Cyrenaica (Libya) with using MODIS and SEVIRI data. SEVIRI images are also used to study the meteorology of the dust storms in order to provide more information on the wind direction, cause, and lifetime of dust storm. The highest percentage of the dust storms generated from Cyrenaica are caused by Anticyclone 70%. The majority last for six hours, starting at 8:00 am and ending at 14:00 pm. MODIS is used to detect the location of the dust sources and Landsat and Google Earth images are used to identify the geomorphology of the dust sources. Total of 53 dust sources are detected during 2008, 45% from alluvial fans, 15% from lake, 13% from alluvial plains, 6% from agriculture, 6% from river, 2% from multiple landforms in a single MODIS pixel and thus their nature could not be determined, while 13% were diffuse and no source could be detected. Alluvial fans were the most active sources and almost half of these dust sources are located at one large fan located south east of Benghazi.
6
Hyatt, Carly Adeline. "Development and Regional Application of Sub-Seasonal Remote- Sensing Chlorophyll Detection Models." Text, BYU ScholarsArchive, 2003. https://scholarsarchive.byu.edu/etd/4390.
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Remote sensing has been used as an effective chlorophyll-a detection method in inland lakes and reservoirs. Concentration estimates of chlorophyll-a approximate the amounts of algae and phytoplankton in a body of water, can indicate the existence of large blooms and high nutrient loading, and can be used as an indicator of water quality. These biomasses pose potential threats to the quality of the water and the local environment by depleting oxygen, influencing the taste of the drinking water and detrimentally affecting aesthetics and recreation. Deer Creek Reservoir exhibited eutrophic tendencies in the early 1990's, caused by phosphorus pollution. This was made evident by accelerated algae growth. Following remediation efforts, Deer Creek Reservoir, as well as nearby Jordanelle Reservoir have been closely monitored with regular field sampling. These field data have been used to develop remote sensing methods using Landsat images to provide supplementary information for reservoir management. These remote sensing methods allow for mapping of the distribution of chlorophyll-a, which provides spatial distribution average, and maximum estimates of chlorophyll-a concentrations, data and information that are not feasible with in-field sampling. In this thesis, traditional methods for remote sensing models are discussed, and a novel sub-seasonal approach based on seasonal algal succession is proposed and demonstrated. Each seasonal model is created using a standard stepwise regression using historic field data and the associated Landsat images and is statistically tested for leverage to ensure unbiased model development. These sub-seasonal detection models are applied to 5 reservoirs in the central-Utah region to provide a more comprehensive description of reservoir behavior and water quality trends over the past 30 years. Historic trends of the average and maximum chlorophyll-a estimates are provided for each of the reservoirs. Example color maps are presented to demonstrate the ability of remote sensing to represent the spatial distribution of algae (using chlorophyll as an indicator). Limitations for this approach are discussed, as well as applications for remotely sensed water quality data on a regional scale.
7
Allsopp, Catherine E. M. "HLA in sub-Saharan Africa." Electronic Thesis or Dissertation, Open University, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.316694.
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Kukat, James Pkemoi. "Development and Validation of a Remote Sensing Model to Identify Anthropogenic Boreholes that Provide Dry Season, Refuge Habitat for Anopheles Vector Mosquitoes in Sub-Saharan Africa." Text, Scholar Commons, 2006. http://scholarcommons.usf.edu/etd/6287.
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A lack of surveillance systems is an impediment to public health intervention for perennial vector-borne disease transmission in northern tropical savanna region of Kenya. The population in this area are mostly poor nomadic pastoralists with little acquired functional immunity to Plasmodium falciparum, due to infrequent challenges with the parasite. A common characteristic in tropical savanna climatic zone is the availability of riverbeds that have anthropogenic boreholes that provide malaria vector mosquitoes, such as Anopheles gambiae s.l and Anopheles funestus, with aquatic refuge habitats for proliferation and endemic transmission to proximity human households during the dry-season. Unfortunately, currently there have been no entomological investigations employing field or remotely sensed data that can characterize and model anthropogenic borehole habitats focusing on the dry-land ecology of immature Anopheles mosquitoes in sub-Sahara Africa. The goal of this investigation was three-fold: (I) to employ WorldView-3 (0.31 meter spatial resolution) visible and near infra-red waveband sensor data to image sub-Saharan land cover associated with vector-borne disease transmission; (II) to remotely identify anthropogenic boreholes in three riverbeds that were surveyed to determine whether they provide malaria vectors with refuge habitat and maintain their population during the dry season in Chemolingot, Kenya, and (III) to obtain a radiometric/spectral signature model representing boreholes from the remotely-sensed data. The signature model was then interpolated to predict unknown locations of boreholes with the same spectral signature in Nginyang Riverbed, Kenya. Ground validation studies were subsequently conducted to assess model’s precision based on sensitivity and specificity tests.
9
Peltier, Jean-Philippe N. "State development in Sub-Saharan Africa." Thesis, Monterey, California. Naval Postgraduate School, 2003. http://hdl.handle.net/10945/5836.
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The universal theory of state formation, as discussed by Weber, Tilly and others, is relevant and appropriate to Africa when properly applied. Africa has her own unique history and the variables affecting state development, such as land tenure, remain the same. The value of these variables is what differs from the European experience. As such, state development in Africa remains strikingly similar throughout its history. It is a struggle between the center and the periphery in which the center is hindered by three commonalities: lack of centralization, communal land ownership and patron-client systems. These commonalities worked against centralization, each building on the other and helping the periphery maintain a degree of independence rarely seen in other regions of the world. To understand modern Africa is to look at her past and see how remarkably constant her society has been. After reviewing the available literature, this thesis delves into Africaαs past and shows how important it is to the understanding of her present condition. In the end, it will draw out both domestic and international policy implications for sub-Saharan Africa.
10
Wingo, Michelle L. "SOCIAL UNDERDEVELOPMENT IN SUB-SAHARAN AFRICA." Master's thesis, University of Central Florida, 2001. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4365.
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For the past thirty years Africa has produced a more noticeably inferior reserve of human capital than other developing regions. This is puzzling because at the inception of independence, the future of Africa looked promising. However, during the 1970s both the political and economic situation in Africa began to deteriorate, and since 1980, the aggregate per capita GDP in sub-Saharan Africa has declined at almost one percent per fiscal year. Thirty-two countries are poorer now than they were twenty years ago, and sub-Saharan Africa is now the lowest-income region in the world despite the fact that during the last two decades Africa has attracted more aid per capita than other developing regions. I hypothesize that focusing primarily on economic growth as the primary means of development has undermined and deterred social development in sub-Saharan Africa. I believe that as foreign investment and debt increase, social development stagnates and even declines. I argue that because of the focus on economics and lack of focus on social and cultural considerations sustained economic growth has been devitalized in sub-Saharan Africa. For this research I employed time-series, cross-sectional regression analysis to test the relative importance of the economic development model on social development in sub-Saharan Africa. My analysis of the forty-eight countries over thirty years gives leverage to the critique of economic growth centered development policies.
M.A.
Department of Political Science
Arts and Sciences
Political Science

Книги з теми "Sub-Saharan Remote sensing":

1
Falloux, François. Land information and remote sensing for renewable resource management in sub-Saharan Africa: A demand-driven approach. Washington, D.C: World Bank, 1989.
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2
Khorram, Siamak. Remote Sensing. Boston, MA: Springer US, 2012.
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3
Khorram, Siamak. Remote sensing. Berkeley, CA: Springer, 2012.
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4
Fridell, Ron. Remote sensing. Minneapolis: Lerner Publications, 2009.
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5
Clifton, Margaret. Remote sensing. Washington, D.C. (101 Independence Ave., S.E., Washington 20540-4750): Science Reference Section, Science, Technology, and Business Division, Library of Congress, 2005.
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6
Fridell, Ron. Remote sensing. Minneapolis: Lerner Publications, 2009.
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7
Buydos, John F. Remote sensing. Washington, D.C. (10 First St., S.E., Washington 20540-5232): Science Reference Section, Science and Technology Division, Library of Congress, 1993.
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8
Fridell, Ron. Remote sensing. Minneapolis: Lerner Publications, 2009.
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9
Khorram, Siamak, Stacy A. C. Nelson, Frank H. Koch, and Cynthia F. van der Wiele. Remote Sensing. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-3103-9.
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10
Maddox, Gregory. Sub-Saharan Africa. Santa Barbara: ABC-CLIO, 2008.
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Автореферати дисертацій з теми "Sub-Saharan Remote sensing":

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Семенець, Анастасія Сергіївна. "Функціонування системи quorum sensing у штамів Pseudomonas aeruginosa з різним рівнем циклічного дигуанозинмонофасфату". Автореф. дис. канд. біол. наук, М-во освіти і науки України, Одес. нац. ун-т ім. І.І. Мечникова, 2020.
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Частини книг з теми "Sub-Saharan Remote sensing":

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Foody, Giles M. "Sub-Pixel Methods in Remote Sensing." In Remote Sensing Image Analysis: Including The Spatial Domain, 37–49. Dordrecht: Springer Netherlands, 2004. http://dx.doi.org/10.1007/978-1-4020-2560-0_3.
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Powell, K. A., C. R. Trepte, and G. S. Kent. "Observations of Saharan Dust by LITE." In Advances in Atmospheric Remote Sensing with Lidar, 149–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-60612-0_37.
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Harrison, Graham. "Sub-Saharan Africa." In The New Regional Politics of Development, 218–47. London: Macmillan Education UK, 2004. http://dx.doi.org/10.1007/978-1-137-09955-6_9.
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Lutz, Brenda J., and James M. Lutz. "Sub-Saharan Africa." In Globalization and the Economic Consequences of Terrorism, 109–31. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/978-1-137-50394-7_6.
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Moradi, Alexander. "Sub-Saharan Africa." In An Economist’s Guide to Economic History, 285–92. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96568-0_33.
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Stotsky, Janet G. "Sub-Saharan Africa." In Using Fiscal Policy and Public Financial Management to Promote Gender Equality, 64–101. 1st Edition. | New York: Routledge, 2020. | Series: Gender economics: Routledge, 2020. http://dx.doi.org/10.4324/9780429298400-5.
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Deumert, Ana. "Sub-Saharan Africa." In The Routledge Handbook of Pidgin and Creole Languages, 15–32. Other titles: Handbook of Pidgin and Creole languages Description: New York: Routledge, 2020. | Series: Routledge handbooks in linguistics: Routledge, 2020. http://dx.doi.org/10.4324/9781003107224-3.
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Reed, Ira. "Sub-Saharan Africa." In The Other World, 195–253. Tenth edition. | New York, NY : Routledge, 2018. | "Ninth edition published by Pearson Education, Inc. 2011 and Routledge 2016.": Routledge, 2017. http://dx.doi.org/10.4324/9781315543383-6.
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Workneh, Téwodros W. "Sub-Saharan Africa." In Global Media Giants, 287–311. New York; London: Routledge, 2016.: Routledge, 2016. http://dx.doi.org/10.4324/9781315682334-18.
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Archangel, Byaruhanga Rukooko. "Sub-Saharan Africa." In Routledge Handbook of Development Ethics, 401–6. Abingdon, Oxon ; New York, NY : Routledge, 2018.: Routledge, 2018. http://dx.doi.org/10.4324/9781315626796-46.
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Тези доповідей конференцій з теми "Sub-Saharan Remote sensing":

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Papa, M. N., F. Ciervo, Y. Koussoube, G. Di Martino, A. Iodice, D. Riccio, G. Ruello, and I. Zinno. "Use of SAR data for hydro-morphological characterization in sub-Saharan Africa: a case study." In SPIE Remote Sensing, edited by Roland Meynart, Steven P. Neeck, and Haruhisa Shimoda. SPIE, 2011. http://dx.doi.org/10.1117/12.898168.
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Legrand, Michel, Claude N'doume, and Isabelle Jankowiak. "Satellite-derived climatology of the Saharan aerosol." In Satellite Remote Sensing, edited by David K. Lynch. SPIE, 1994. http://dx.doi.org/10.1117/12.196669.
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Sciarra, Roberto, Gianluca Volpe, and Rosalia Santoleri. "SeaWiFS observations of Saharan dust events over the Mediterranean Sea." In Remote Sensing, edited by Charles R. Bostater, Jr. and Rosalia Santoleri. SPIE, 2004. http://dx.doi.org/10.1117/12.516641.
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Talianu, Camelia, Doina Nicolae, Anca Nemuc, Livio Belegante, and Emil Carstea. "Saharan dust event over Bucharest observed by an elastic backscatter lidar." In Remote Sensing, edited by Upendra N. Singh and Gelsomina Pappalardo. SPIE, 2007. http://dx.doi.org/10.1117/12.737886.
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Pisani, Gianluca, Mario Armenante, Antonella Boselli, Maria Grazia Frontoso, Nicola Spinelli, and Xuan Wang. "Atmospheric aerosol characterization during Saharan dust outbreaks at Naples EARLINET station." In Remote Sensing, edited by Adolfo Comerón, Klaus Schäfer, James R. Slusser, Richard H. Picard, and Aldo Amodeo. SPIE, 2007. http://dx.doi.org/10.1117/12.738150.
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Nicolae, Doina, Anca Nemuc, and L. Belegante. "Mix of volcanic ash and Saharan dust over Romania during Eyjafjallajökull eruption." In Remote Sensing, edited by Upendra N. Singh and Gelsomina Pappalardo. SPIE, 2010. http://dx.doi.org/10.1117/12.869021.
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Moser, Linda, Stefan Voigt, and Elisabeth Schoepfer. "Monitoring of critical water and vegetation anomalies of sub-Saharan West-African Wetlands." In IGARSS 2014 - 2014 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2014. http://dx.doi.org/10.1109/igarss.2014.6947322.
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Vanhuysse, Sabine, Tais Grippa, Moritz Lennert, Eleonore Wolff, and Mahamadou Idrissa. "Contribution of nDSM derived from VHR stereo imagery to urban land-cover mapping in Sub-Saharan Africa." In 2017 Joint Urban Remote Sensing Event (JURSE). IEEE, 2017. http://dx.doi.org/10.1109/jurse.2017.7924570.
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Ramos, Antonio G., Emilio Cuevas, Carlos Pérez, J. M. Baldasano, Josep Coca, Alex Redondo, Silvia Alonso-Pérez, et al. "Saharan dust-induced chlorophyll blooms in the northwest African upwelling." In Asia-Pacific Remote Sensing, edited by Robert J. Frouin, Serge Andrefouet, Hiroshi Kawamura, Mervyn J. Lynch, Delu Pan, and Trevor Platt. SPIE, 2008. http://dx.doi.org/10.1117/12.804880.
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Fontenot, Andrew T., Hesham M. El-Askary, and William K. M. Lau. "Hurricane Sandy and Saharan dust." In IGARSS 2014 - 2014 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2014. http://dx.doi.org/10.1109/igarss.2014.6947618.
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Звіти організацій з теми "Sub-Saharan Remote sensing":

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Kornreich, Philipp. Remote Optical Sensing. Fort Belvoir, VA: Defense Technical Information Center, March 1990. http://dx.doi.org/10.21236/ada220780.
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Harris, J., and L. Wickert. Optical remote sensing. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2008. http://dx.doi.org/10.4095/226012.
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Harris, J., E. Grunsky, and V. Singhroy. Radar remote sensing. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2008. http://dx.doi.org/10.4095/226013.
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Schultz, J., S. Czuchlewski, and R. Karl. Advanced laser remote sensing. Office of Scientific and Technical Information (OSTI), November 1996. http://dx.doi.org/10.2172/399674.
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Davis, Curtiss O. Airborne Hyperspectral Remote Sensing. Fort Belvoir, VA: Defense Technical Information Center, September 1999. http://dx.doi.org/10.21236/ada631001.
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Friske, P., and J. Harris. Geochemistry/remote sensing, Labrador. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1994. http://dx.doi.org/10.4095/194048.
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Davis, Curtiss O. Airborne Hyperspectral Remote Sensing. Fort Belvoir, VA: Defense Technical Information Center, September 2001. http://dx.doi.org/10.21236/ada625021.
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Alföldi, T., P. Catt, and P. R. Stephens. Definitions of Remote Sensing. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1993. http://dx.doi.org/10.4095/218103.
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Ouattara, T., R. Couture, P. T. Bobrowsky, and A. Moore. Remote sensing and geosciences. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2004. http://dx.doi.org/10.4095/214995.
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Richards, William L. Engagement for Sub-Saharan Africa. Fort Belvoir, VA: Defense Technical Information Center, April 1998. http://dx.doi.org/10.21236/ada344993.
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