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Littérature scientifique sur le sujet « Sub-Saharan Remote sensing »

Auteur : Grafiati
Publié le 4 juin 2021
Mis à jour le 8 février 2022

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Articles de revues sur le sujet "Sub-Saharan Remote sensing"

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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 2, 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.
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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 18, 2015): 173–79. http://dx.doi.org/10.1080/0035919x.2015.1017024.

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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 12, 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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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 14, 2016): 584. http://dx.doi.org/10.3390/ijerph13060584.

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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 2, 2015): 1–7. http://dx.doi.org/10.2989/16085914.2015.1014994.

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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 25, 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.
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Bhaga, Trisha Deevia, Timothy Dube, Munyaradzi Davis Shekede, and Cletah Shoko. "Impacts of Climate Variability and Drought on Surface Water Resources in Sub-Saharan Africa Using Remote Sensing: A Review." Remote Sensing 12, no. 24 (December 21, 2020): 4184. http://dx.doi.org/10.3390/rs12244184.

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Climate variability and recurrent droughts have caused remarkable strain on water resources in most regions across the globe, with the arid and semi-arid areas being the hardest hit. The impacts have been notable on surface water resources, which are already under threat from massive abstractions due to increased demand, as well as poor conservation and unsustainable land management practices. Drought and climate variability, as well as their associated impacts on water resources, have gained increased attention in recent decades as nations seek to enhance mitigation and adaptation mechanisms. Although the use of satellite technologies has, of late, gained prominence in generating timely and spatially explicit information on drought and climate variability impacts across different regions, they are somewhat hampered by difficulties in detecting drought evolution due to its complex nature, varying scales, the magnitude of its occurrence, and inherent data gaps. Currently, a number of studies have been conducted to monitor and assess the impacts of climate variability and droughts on water resources in sub-Saharan Africa using different remotely sensed and in-situ datasets. This study therefore provides a detailed overview of the progress made in tracking droughts using remote sensing, including its relevance in monitoring climate variability and hydrological drought impacts on surface water resources in sub-Saharan Africa. The paper further discusses traditional and remote sensing methods of monitoring climate variability, hydrological drought, and water resources, tracking their application and key challenges, with a particular emphasis on sub-Saharan Africa. Additionally, characteristics and limitations of various remote sensors, as well as drought and surface water indices, namely, the Standardized Precipitation Index (SPI), Palmer Drought Severity Index (PDSI), Normalized Difference Vegetation (NDVI), Vegetation Condition Index (VCI), and Water Requirement Satisfaction Index (WRSI), Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), Land Surface Water Index (LSWI+5), Modified Normalized Difference Water Index (MNDWI+5), Automated Water Extraction Index (shadow) (AWEIsh), and Automated Water Extraction Index (non-shadow) (AWEInsh), and their relevance in climate variability and drought monitoring are discussed. Additionally, key scientific research strides and knowledge gaps for further investigations are highlighted. While progress has been made in advancing the application of remote sensing in water resources, this review indicates the need for further studies on assessing drought and climate variability impacts on water resources, especially in the context of climate change and increased water demand. The results from this study suggests that Landsat-8 and Sentinel-2 satellite data are likely to be best suited to monitor climate variability, hydrological drought, and surface water bodies, due to their availability at relatively low cost, impressive spectral, spatial, and temporal characteristics. The most effective drought and water indices are SPI, PDSI, NDVI, VCI, NDWI, MNDWI, MNDWI+5, AWEIsh, and AWEInsh. Overall, the findings of this study emphasize the increasing role and potential of remote sensing in generating spatially explicit information on drought and climate variability impacts on surface water resources. However, there is a need for future studies to consider spatial data integration techniques, radar data, precipitation, cloud computing, and machine learning or artificial intelligence (AI) techniques to improve on understanding climate and drought impacts on water resources across various scales.
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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 4, 2018): 344–57. http://dx.doi.org/10.1080/1747423x.2018.1511763.

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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 25, 2013): e2342. http://dx.doi.org/10.1371/journal.pntd.0002342.

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Atai, Godwin, Ayansina Ayanlade, Isaac Ayo Oluwatimilehin, and Oluwatoyin Seun Ayanlade. "Geospatial Distribution and Projection of Aerosol over Sub-Saharan Africa: Assessment from Remote Sensing and Other Platforms." Aerosol Science and Engineering 5, no. 3 (June 15, 2021): 357–72. http://dx.doi.org/10.1007/s41810-021-00107-4.

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Thèses sur le sujet "Sub-Saharan Remote sensing"

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Symeonakis, Elias. "Soil erosion modelling over sub Saharan Africa using remote sensing and geographical information systems." Thesis, King's College London (University of London), 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.248386.

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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." Doctoral thesis, Universite Libre de Bruxelles, 2020. 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.<br>Doctorat en Sciences agronomiques et ingénierie biologique<br>info:eu-repo/semantics/nonPublished
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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." Scholar Commons, 2016. 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.
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Georganos, Stefanos. "The use of very-high-resolution earth observation satellite data for multi-thematic urban mapping in sub-Saharan Africa: Applications in population, household wealth and epidemiological modeling." Doctoral thesis, Universite Libre de Bruxelles, 2021. https://dipot.ulb.ac.be/dspace/bitstream/2013/317404/3/ToC.pdf.

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Sub-Saharan African (SSA) cities are some of the most rapid-growing regions inthe world. As estimated by the United Nations, more than 50% of the Africanpopulation will reside in cities by 2030 while in absolute numbers, its population willhave doubled - from 1.2 billion in 2015 to 2.5 billion by 2050. This ongoing shift hasdramatically affected the capacity of several SSA cities to provide essential servicesfor its residents, such as durable housing, employment and healthcare accessibility.On the contrary, the proliferation of slums, further marginalizing the urban poor hasbeen an undisputed observation of the last years. It is therefore profound, that effortsto improve the quality of life of urban dwellers are needed. A starting point to do so,it to provide relevant authorities, stakeholders and organizations with useful socioeconomic,demographic and health indicators of the urban dwellers. Nonetheless, Inlarge parts of SSA, this type of critical information is at best scarce and at worstnon-existent and certainly not suited for sophisticated intra-urban analyses.This thesis harnesses the strength of very-high-resolution (VHR) satellite remotesensing to provide multi-level (physical, socio-economic, demographic and epidemiological)representations of the urban surface in several major SSA cities. First, cuttingedge advances relevant to the classification of urban land cover are presented.Afterwards, an assessment and evaluation of the potential of VHR satellite imageryas input to population estimation, household wealth and malaria risk models atunprecedented resolutions is investigated. The conclusions of this work encouragethe systematic exploitation of VHR data to support evidence-based decision makingshaping the sustainable future of SSA cities.<br>Doctorat en Sciences<br>In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not endorse any of ULB’s products or services. Internal or personal use of this material is permitted. If interested in reprinting/republishing IEEE copyrighted material for advertising or promotional purposes or for creating new collective works for resale or redistribution, please go to http://www.ieee.org/publications_standards/publications/rights/rights_link.html to learn how to obtain a License from RightsLink. If applicable, University Microfilms and/or ProQuest Library, or the Archives of Canada may supply single copies of the dissertation<br>info:eu-repo/semantics/nonPublished
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Grippa, Taïs. "Very‑high resolution earth observation data and open‑source solutions for mapping urban areas in sub-Saharan Africa. Implementation of an operational framework for production of geoinformation. Application on Ouagadougou (Burkina Faso) and Dakar (Senegal)." Doctoral thesis, Universite Libre de Bruxelles, 2019. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/284464.

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Nowadays, in sub-Saharan Africa (SSA), about 40% of the population is urban and this region is expected to face the highest growth rates during the next decades. By 2100, the three most populated cities in the world will be located in SSA. As a consequence of the extremely fast transformations experienced during the last decades, SSA cities are facing social and environmental issues combined with a lack of financial means and capacity in urban planning and management. The poorest often constitute a large part of the urban population that is extremely vulnerable to health and disaster risks.In SSA cities, up-to-date and spatially detailed geographic information is often missing. This lack of information is an important issue for many scientific studies focusing on different urban issues and there is a real need to improve the availability of geoinformation for these cities in order to support urban planning, urban management, environment monitoring, epidemiology or risk assessment, etc. The work presented in this thesis aims to develop different frameworks for the production of geoinformation. For this purpose, advantage is taken of Very-High Resolution Remote Sensing imagery (0.5 meters) and open-source software. These frameworks implement cutting-edge methods and can handle a large amount of data in a semi-automated fashion to produce maps covering very large areas of interest. In the spirit of open science, the processing chains are entirely based on open-source software and are released publicly in open-access for any interested researchers, in order to make the methods developed completely transparent and in order to contribute to the creation of a pool of common tools and scientific knowledge. These frameworks are used to produce very detailed land-cover and land-use maps that provide essential information such as the built-up density, or the fact that a neighborhood is residential or not. This detailed geoinformation is then used as indicators of presence of populated places to improve existing population models at the intra-urban level.<br>Option Géographie du Doctorat en Sciences<br>info:eu-repo/semantics/nonPublished
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Lukong, Paul Forka. "The diffusion of HIV/AIDS in sub Saharan Africa : the role of social, economic and cultural factors." 2000. http://web4.library.adelaide.edu.au/theses/09ENV/09envl954.pdf.

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Bibliography: leaves 103-113. Uses GIS to map the pattern of widespread transmission, commercial sex workers, poverty prevalence, illiteracy rate, population displacement and other social indicators to show the vulnerability of the region's population; and to demonstrate that there is no single point of radiation of HIV/AIDS in the sub region. Discusses mitigation and prevention strategies and proposes the use of GIS be incorporated in the fight against HIV/AIDS in sub Saharan Africa.
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(9174146), Jessica Abbie Eisma. "From impacts to implementation: A survey of sand dams in sub-Saharan Africa." Thesis, 2020.

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<div>International development projects are a massive business, with billions invested annually in the Global South. However, such projects have an unacceptably long record of high failure rates. The problem perpetuates, in part, due to the success factors by which international development projects are judged. Often, projects are assessed on the basis of donor-identified priorities that are not aligned with local impacts. One such international development project involves the construction of small-scale water harvesting structures known as sand dams. Non-governmental organizations (NGOs) continue to raise sufficient funds to build thousands of sand dams across sub-Saharan Africa, and yet 50% of sand dams are estimated to be non-functioning.</div><div><br></div><div>Sand dams are small, reinforced concrete dams built across an impermeable stream-bed. Over time, sand settles behind the dam, creating an upstream sand reservoir that fills with rainwater and surface runoff. The sand helps filter the water, protects it from evapotranspiration, and can provide water to the local community for domestic and agricultural use during the dry season. Sand dams often fail due to poor construction, inadequate siting, and siltation.</div><div><br></div><div>This dissertation explores methodologies for studying the regional and local impacts of sand dams and investigates the feasibility of developing model-based site selection guidelines for sand dams. Three objectives of this study are: (1) to develop a methodology to assess the ability of sand dams in improving the overall water availability in the region; (2) to examine claims made by non-scientific bodies about sand dam impacts by investigating how diverse sand dams influence macroinvertebrate habitat, vegetation, erosion, and local water availability; and (3) to create guidelines for siting new sand dams based on a fully integrated surface and groundwater flow model.</div><div><br></div><div>For the first objective, two multiple regression models are developed to compare (1) water storage and (2) vegetation in an area with a high density of sand dams, termed the sand dam counties (SDC), to those in a control area. The models analyze remotely sensed datasets to assess whether evidence exists of significantly increased storage in the SDC relative to the control area. The results show that the remotely sensed water storage data is unable to consistently detect higher levels of water storage in the SDC. This is likely due to the low resolution of the dataset combined with the small magnitude of sand dams' impact on regional water storage. The results of the vegetation model show that the sand dams have a consistent, positive impact on vegetation within the SDC relative to the control area. Because vegetation health and cover is often correlated with groundwater levels, these results likely indicate that the sand dams are also increasing local groundwater levels. Overall, this study shows that remotely sensed dataset can provide a useful basis to assess the impact of international development projects, particularly those that involve the natural environment. </div><div><br></div><div>For the second objective, data relating to macroinvertebrates, vegetation, erosion, and water table elevations at three sand dams were collected and analyzed during a year-long field study in Tanzania. These study subjects were specifically selected to test an NGO claim that sand dams revitalize the entire ecosystem. The results of this study show that sand dams are not a suitable habitat for macroinvertebrates due to their homogeneity. The impact of sand dams on vegetation cover can be significant, but may be limited by the slope of the surrounding land. Functioning sand dams likely have little impact on streambank erosion, but non-functioning sand dams may contribute to the erosion of streambanks in unstable reaches. Lastly, the water table is locally raised by recharge from sand dams, however, the spatial and temporal extent of the impact is more limited than conveyed by NGOs and previous studies. This study adds to the limited body of knowledge on the environmental responses to sand dams and demonstrates the importance of examining the local impacts of individual international development projects. </div><div><br></div><div>For the third objective, results from four different simulations of a watershed-based model with three cascading sand dams are analyzed to identify overland features that improve vadose zone storage and groundwater recharge and reduce evapotranspiration. Results from this study show that sand dams constructed in a low-lying area that collects surface runoff from adjacent steep slopes, such as in a U-shaped valley, will likely collect and store sufficient water for use by a local community. Watersheds with relatively more area cultivated with low-water-need crops will similarly be beneficial to sand dam performance. In addition, the analysis revealed that the volume of water a sand dam receives during a rainy season is less important for water storage than the duration of dry seasons. Lastly, the simulations showed that sand dams constructed in an area with sandier soils will perform better than those in an area with loamy soils. This study produced a set of guidelines that can be used to identify locations where sand dams are likely to capture and store sufficient water for community use during the dry season.</div>
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Twisa, Sekela Simon. "Sustainability of Rural Water Supply in Sub-Saharan Africa: GIT-Based Studies in East-Central Tanzania." 2021. https://tud.qucosa.de/id/qucosa%3A76133.

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The achievement of sustainable and lasting effects from projects is a significant challenge for donors and the agencies implementing and supporting water supply in developing countries. The current estimations for Sub-Saharan Africa (SSA) suggest that only two out of three water points in rural areas on the continent are functioning at any given time. The region of SSA includes many of the world’s poorest countries, and sustainability of water supply services is vital concerning people without access to safe drinking water. Not surprisingly, many policies and planning decisions are taken without access to adequate data, a situation that increases the risk of inappropriate measures being adopted. The objective of the present study is to address the potential of applying geospatial technology to monitor the sustainability of rural water supply services. It focused on the Wami River Basin in Tanzania due to its diversified use, which benefits a multi-diversity of stakeholders and its role as a vital area for providing water, food and other natural resources. It is in the interest of this study to understanding reasons for “success” and “failure” of water points using Geographic Information Technologies (GIT) based approach to analyse factors of biophysical and human domains that respond to both in time and space. The study analyses the trends in annual and seasonal rainfall time series in the Wami River Basin during 1983–2017 for any significant changes in the patterns and how they affect the access to water supply services in rural areas. First, waterpoint mapping datasets were analysed considering seasonal variation. Later, the study focused on changes in land-use/land-cover patterns upstream and downstream and explored the spatial econometric technique by analysing the impact of land-use/land-cover change on water ecosystem services for domestic use in the basin. Lastly, I provide my vision of the water-food-land nexus giving attention to how it relates to agriculture expansion. I identify trade-offs between and assess the synergies associated with the influence of agriculture intensification and anticipation of water services concerning data availability. The results showed that water points were significantly affected by seasonal changes, both in terms of availability and water quality. There also exists a strong relationship between rural water services and seasons. With a time series of maps, change analysis can reveal the overall development of the land distribution, including the detection of sites of different types of changes. In general, net gain and net loss were observed downstream, indicating that this region was more affected than upstream. I found that all measured land-use/land-cover changes and water point characteristic correlations were statistically significant; therefore, I concluded that land-use/land-cover change affects the water ecosystem in the basin. These findings provide baseline information for decision-makers and stakeholders concerning water supply services for better planning and management decisions in the basin. Furthermore, the approach has contributed to the application of geospatial technologies in rural water supply services and might help pursue sustainability strategies in other basins. The approach based on detailed large-area field data to identify variations in the spatial distribution of the water service supply regarding quality and quantity to a reasonable degree of accuracy. Hence, it presents an excellent opportunity to provide relevant information about water supply services performance in response to spatially and temporally critical importance. However, due to the lack of up-to-date information, it does not cover other essential access aspects concerning the vulnerability of the water services like lack of financial and governance components that play a significant role in the sustainability of rural water supply services. Therefore, more studies should be undertaken to explore the use of Remote Sensing (RS) and Geographic Information Systems (GIS) with different temporal and spatial scales in future research, integrating institutional and socio-economic analyses of environmental sustainability.:Note on the Commencement of the Doctoral Procedure ii Declaration of conformity iii AckAcknowledgements v Abstract vi Zusammenfassung viii 1. Introduction 1 1.1 Background 1 1.2 The Motivation for Research Issues 3 1.3 Objectives of the Study 7 1.4 Description of the Study Area 7 1.5 The Organisation of the Chapters 11 1.6 References 12 2. Seasonal and Annual Rainfall Variability and Their Impact on Rural Water Supply Services in the Wami River Basin 22 2.1 Abstract 22 2.2 Introduction 23 2.3 Methods and Data 24 2.3.1 Statistical Test for Trend Analysis 25 2.3.2 Simple Regression Model 26 2.3.3 Water Point Mapping System 2.4 Results 29 2.4.1 Annual and Seasonal Rainfall Trends Analysis 29 2.4.2 Dry and Wet Seasonal Variation and Use of Water Points 34 2.5 Discussion 43 2.6 Conclusions 45 2.7 References 46 3. Land-Use and Land-Cover (LULC) Change Detection in the Wami River Basin, Tanzania 54 3.1 Abstract 54 3.2 Introduction 55 3.3 Materials and Methods 57 3.3.1 Data Acquisitions and Preparation 57 3.3.2 Classification and Change Detection 58 3.4 Results 59 3.4.1 Accuracy Assessment 59 3.4.2 Upstream Sub-Catchment (Kinyasungwe) 60 3.4.3 Downstream Sub-Catchment (Wami) 65 3.5 Discussion 68 3.6 Conclusions 70 3.7 References 70 4. Impact of Land-Use/Land-Cover Change on Drinking Water Ecosystem Services in Wami River Basin, Tanzania 78 4.1 Abstract 78 4.2 Introduction 79 4.3 Material and Methods 81 4.3.1 Spatial Regression Analysis 81 4.4 Results 83 4.4.1 Accuracy Assessment 83 4.4.2 Kinyasungwe Sub-Catchment 83 4.4.3 Wami Sub-Catchment 89 4.5 Discussion 95 4.6 Conclusion 97 4.7 References 98 5. Water-Food-Land Nexus and Agriculture Expansion: Prospects for Enhancing Water Ecosystem Services in Tanzania 106 5.1 Abstract 106 5.2 Introduction 107 5.3 Nexus Concept and Interlinkage 109 5.4 Exploring Agriculture Expansion and Drinking Water Supply Services Challenges. 112 5.4.1 Agriculture Expansion Challenges. 112 5.4.2 Water Supply Services Challenges. 113 5.5 Trade-off between Agriculture Expansion and Water Ecosystem Services 114 5.6 Synergies and Role of Data to Improve Accountability in Governance for Sustainable Water Ecosystem Services 116 5.7 The Nexus Approach and Synergies based on improved Management Information Systems (MIS) 118 5.8 Monitoring Drought Resilience based on typologies and a composite Nexus Index 119 5.9 Conclusions 120 5.10 References 121 6. Conclusion, Recommendations and Outlook 134 6.1 Conclusion and Recommendations 134 6.2 Outlook 136
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Livres sur le sujet "Sub-Saharan Remote sensing"

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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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Land survey and large-scale mapping in sub-Saharan Africa. Nairobi: Habitat, 2001.

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Guidelines on the Use of Remote Sensing Products to Improve Agricultural Crop Production Forecast Statistics in Sub-Saharan African Countries. UN, 2018. http://dx.doi.org/10.18356/8703b7b7-en.

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Chapitres de livres sur le sujet "Sub-Saharan Remote sensing"

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Hay, S. I., J. A. Omumbo, M. H. Craig, and R. W. Snow. "Earth observation, geographic information systems and Plasmodium falciparum malaria in sub-Saharan Africa." In Remote Sensing and Geographical Information Systems in Epidemiology, 173–215. Elsevier, 2000. http://dx.doi.org/10.1016/s0065-308x(00)47009-0.

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Actes de conférences sur le sujet "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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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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Vancutsem, C., J. F. Pekel, and F. Kayitakire. "Dynamic mapping of cropland areas in Sub-Saharan Africa using MODIS time series." In 2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp). IEEE, 2011. http://dx.doi.org/10.1109/multi-temp.2011.6005038.

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Hoscilo, A., H. Balzter, E. Bartholome, M. Boschetti, P. A. Brivio, and A. Brink. "Changes in vegetation and rainfall patterns in sub-Saharan Africa over the last decade observed by satellites - a national and sub-national synthesis." In IGARSS 2011 - 2011 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2011. http://dx.doi.org/10.1109/igarss.2011.6049714.

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Lambert, Marie-Julie, Xavier Blaes, Pierre Sibiry Traore, and Pierre Defourny. "Estimate yield at parcel level from S2 time serie in sub-Saharan smallholder farming systems." In 2017 9th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp). IEEE, 2017. http://dx.doi.org/10.1109/multi-temp.2017.8035204.

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