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Journal articles on the topic 'Geographic information systems – Namibia'

Author: Grafiati

Published: 4 June 2021

Last updated: 3 February 2022

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1

de Vries, W. T. "How progressive land titling could foster new surveying practices and land information systems––based on case studies in Namibia." Computers, Environment and Urban Systems 28, no. 5 (2004): 531–44. http://dx.doi.org/10.1016/j.compenvurbsys.2003.11.006.

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2

Kamwi, Jonathan, Moses Cho, Christoph Kaetsch, Samuel Manda, Friedrich Graz, and Paxie Chirwa. "Assessing the Spatial Drivers of Land Use and Land Cover Change in the Protected and Communal Areas of the Zambezi Region, Namibia." Land 7, no. 4 (2018): 131. http://dx.doi.org/10.3390/land7040131.

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Understanding the patterns and drivers of land use and land cover (LULC) changes is fundamental for rational and specific planning for sustainable land management. Using remote sensing techniques, geographic information systems (GIS) and statistical modeling via multinomial logistic regression, we sought to identify spatial variables that determine LULC change and their extent over time in the protected and communal areas of the Zambezi Region, Namibia. Multi-temporal satellite imagery of the Landsat series was used to map changes over a period of twenty-six years, divided into three stages (1984–1991, 1991–2000 and 2000–2010). Post classification change detection methodologies were used to determine conversions between LULC classes. Additionally, socio-economic characteristics of the area were used to identify drivers of changes. Four spatial drivers of LULC change that we identified included the distance to the nearest road, distance to settlements, population density and fire return periods. Population density, distance to settlements and fire return period were significantly associated with conversion from crop/grass land to crop/grass land and forest land to crop/grass, forest land to bare land and forest land to forest land in the protected area. In communal areas, distance to the road was found to significantly influence conversion from crop/grass land to crop/grass land. The study concluded that the influence of these drivers is attributable to distinct political and agro-demographical differences during the study period. Policy makers and planners need to take these drivers into consideration together with their subsidiaries to respond and make sound decisions regarding undesirable changes in LULC.

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3

Opoku, Samuel Kwasi, Walter Leal Filho, Fudjumdjum Hubert, and Oluwabunmi Adejumo. "Climate Change and Health Preparedness in Africa: Analysing Trends in Six African Countries." International Journal of Environmental Research and Public Health 18, no. 9 (2021): 4672. http://dx.doi.org/10.3390/ijerph18094672.

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Climate change is a global problem, which affects the various geographical regions at different levels. It is also associated with a wide range of human health problems, which pose a burden to health systems, especially in regions such as Africa. Indeed, across the African continent public health systems are under severe pressure, partly due to their fragile socioeconomic conditions. This paper reports on a cross-sectional study in six African countries (Ghana, Nigeria, South Africa, Namibia, Ethiopia, and Kenya) aimed at assessing their vulnerabilities to climate change, focusing on its impacts on human health. The study evaluated the levels of information, knowledge, and perceptions of public health professionals. It also examined the health systems’ preparedness to cope with these health hazards, the available resources, and those needed to build resilience to the country’s vulnerable population, as perceived by health professionals. The results revealed that 63.1% of the total respondents reported that climate change had been extensively experienced in the past years, while 32% claimed that the sampled countries had experienced them to some extent. Nigerian respondents recorded the highest levels (67.7%), followed by Kenya with 66.6%. South Africa had the lowest level of impact as perceived by the respondents (50.0%) when compared with the other sampled countries. All respondents from Ghana and Namibia reported that health problems caused by climate change are common in the two countries. As perceived by the health professionals, the inadequate resources reiterate the need for infrastructural resources, medical equipment, emergency response resources, and technical support. The study’s recommendations include the need to improve current policies at all levels (i.e., national, regional, and local) on climate change and public health and to strengthen health professionals’ skills. Improving the basic knowledge of health institutions to better respond to a changing climate is also recommended. The study provides valuable insights which may be helpful to other nations in Sub-Saharan Africa.

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4

Konduri, Niranjan, Francis Aboagye-Nyame, David Mabirizi, et al. "Digital health technologies to support access to medicines and pharmaceutical services in the achievement of sustainable development goals." DIGITAL HEALTH 4 (January 2018): 205520761877140. http://dx.doi.org/10.1177/2055207618771407.

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Objectives The objective of this study was to describe the conceptual and implementation approach of selected digital health technologies that were tailored in various resource-constrained countries. To provide insights from a donor-funded project implementer perspective on the practical aspects based on local context and recommendations on future directions. Methods Drawing from our multi-year institutional experience in more than 20 high disease-burden countries that aspire to meet the 2030 United Nations Sustainable Development Goal 3, we screened internal project documentation on various digital health tools that provide clarity in the conceptual and implementation approach. Taking into account geographic diversity, we provide a descriptive review of five selected case studies from Bangladesh (Asia), Mali (Francophone Africa), Uganda (East Africa), Mozambique (Lusophone Africa), and Namibia (Southern Africa). Findings A key lesson learned is to harness and build on existing governance structures. The use of data for decision-making at all levels needs to be cultivated and sustained through multi-stakeholder partnerships. The next phase of information management development is to build systems for triangulation of data from patients, commodities, geomapping, and other parameters of the pharmaceutical system. A well-defined research agenda must be developed to determine the effectiveness of the country- and regional-level dashboards as an early warning system to mitigate stock-outs and wastage of medicines and commodities. Conclusion The level of engagement with users and stakeholders was resource-intensive and required an iterative process to ensure successful implementation. Ensuring user acceptance, ownership, and a culture of data use for decision-making takes time and effort to build human resource capacity. For future United Nations voluntary national reviews, countries and global stakeholders must establish appropriate measurement frameworks to enable the compilation of disaggregated data on Sustainable Development Goal 3 indicators as a precondition to fully realize the potential of digital health technologies.

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5

Bogale, Mekonnen, Muluken Ayalew, and Wubishet Mengesha. "The Competitiveness of Travel and Tourism Industry of Sub-Saharan African Countries in the World Market." African Journal of Hospitality, Tourism and Leisure 10(1), no. 10(1) (2021): 131–44. http://dx.doi.org/10.46222/ajthl.19770720-91.

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The purpose of this study was to investigate competitiveness of Travel and Tourism industry of Sub-Saharan African countries in the world market. The study used Normalized Revealed Comparative Advantage (NRCA) and Relative Trade Advantage (RTA) indexes as a measure of competitiveness based on secondary data from ITC trade database covering between 2000 and 2019. The findings of the study revealed that SSA countries like Mauritius, South Africa, Seychelles and Namibia have competitive T&T industry consistently in the years between 2000 and 2019. However, SSA countries such as Botswana, Tanzania, Senegal, Kenya and Rwanda have competitiveness vary by years. Moreover, South Africa has highest comparative advantage followed by Tanzania and Mauritius. The study provided valuable information to industry leaders, policy makers, business owners and international organizations such as UN and UNESCO to design appropriate strategies and systems aiming to sustain and improve travel and tourism industry competitiveness in SSA countries. It is the first study in applying NRCA and RTA indexes to investigate the competitiveness of T&T Industry in SSA countries. Keywords: Competitiveness; export; import; performance; tourism; travel

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6

Nengomasha, Cathrine Tambudzai, Ruth Abankwah, Wilhelm Uutoni, and Lilian Pazvakawambwa. "Health information systems in Namibia." Information and Learning Science 119, no. 7/8 (2018): 358–76. http://dx.doi.org/10.1108/ils-03-2018-0015.

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Purpose This paper aims to report some findings of a study that investigated health information systems (HISs) in Namibia with a view of establishing the nature of these systems and coming up with recommendations on how these could be enhanced. Design/methodology/approach This study applied a mixed methods research approach, using interviews and survey questionnaire to collect data. Survey data were analysed for descriptive statistics using SPSS and data from interviews were analysed applying content analysis for data analysis. Findings The findings of this study indicate fragmented HISs resulting in duplication of diagnosis, tests and treatment. The findings show that there were errors in capturing data into the systems, which could compromise the reliability of the data and compromise service delivery. Research limitations/implications This study was limited to two (Khomas and Oshana) of the fourteen regions in Namibia; therefore, further studies could look at other regions, as the study findings cannot be generalised to the entire country. Practical implications The findings and recommendations, particularly those relating to the public health sector, could inform policies and procedures, especially those relating to the patient health passport (card), and the way health information is shared within and across health sectors. Originality/value This study focused on health information sharing, whereas a previous study on HISs concentrated on quality of healthcare.

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7

Cornelius, Sarah, and Tor Bernhardsen. "Geographic Information Systems." Geographical Journal 163, no. 1 (1997): 104. http://dx.doi.org/10.2307/3059709.

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8

Sweeney, Michael W. "Geographic Information Systems." Water Environment Research 72, no. 6 (2001): 134–40. http://dx.doi.org/10.2175/106143000x138382.

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9

Khan, O. A. "Geographic information systems." American Journal of Public Health 89, no. 7 (1999): 1125. http://dx.doi.org/10.2105/ajph.89.7.1125.

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10

Sweeney, Michael W. "Geographic information systems." Water Environment Research 68, no. 4 (1996): 416–20. http://dx.doi.org/10.2175/106143096x135272.

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11

Sweeney, Michael W. "Geographic information systems." Water Environment Research 70, no. 4 (1998): 424–28. http://dx.doi.org/10.2175/106143098x134163.

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12

Sweeney, Michael W. "Geographic Information Systems." Water Environment Research 71, no. 5 (1999): 551–56. http://dx.doi.org/10.2175/106143099x133631.

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13

Sweeney, Michael W. "Geographic information systems." Water Environment Research 69, no. 4 (1997): 419–22. http://dx.doi.org/10.2175/106143097x134740.

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14

Ward, MH, JR Nuckols, SJ Weigel, SK Maxwell, KP Cantor, and RS Miller. "Geographic information systems." Annals of Epidemiology 10, no. 7 (2000): 477. http://dx.doi.org/10.1016/s1047-2797(00)00152-6.

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15

Brody, Roberta. "Geographic Information Systems." Journal of Business & Finance Librarianship 5, no. 1 (1999): 3–18. http://dx.doi.org/10.1300/j109v05n01_02.

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16

Chen, Jim X. "Geographic Information Systems." Computing in Science & Engineering 12, no. 1 (2010): 8–9. http://dx.doi.org/10.1109/mcse.2010.13.

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17

Zhang, Wendy, and Theresa Beaubouef. "Geographic information systems." ACM SIGCSE Bulletin 40, no. 2 (2008): 124–27. http://dx.doi.org/10.1145/1383602.1383650.

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18

Wikle, Thomas A. "Geographic information systems." ACM SIGCAS Computers and Society 21, no. 2-4 (1991): 28–32. http://dx.doi.org/10.1145/122652.122657.

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19

Wieczorek, William F., and Alan M. Delmerico. "Geographic information systems." Wiley Interdisciplinary Reviews: Computational Statistics 1, no. 2 (2009): 167–86. http://dx.doi.org/10.1002/wics.21.

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20

Goodchild, M. F. "Geographic information systems." Progress in Human Geography 12, no. 4 (1988): 560–66. http://dx.doi.org/10.1177/030913258801200407.

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21

Goodchild, Michael F. "Geographic information systems." Progress in Human Geography 15, no. 2 (1991): 194–200. http://dx.doi.org/10.1177/030913259101500205.

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22

Felke, Thomas P. "Geographic Information Systems." Journal of Evidence-Based Social Work 3, no. 3-4 (2006): 103–13. http://dx.doi.org/10.1300/j394v03n03_08.

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23

Dada, Maria. "Queering Geographic Information information Systems." A Peer-Reviewed Journal About 8, no. 1 (2019): 58–68. http://dx.doi.org/10.7146/aprja.v8i1.115415.

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What’s the relationship between GIS and the political subject? In an effort to address this question, this paper traces the movement from the map to GIS. The map is shown to be the performative utterance of the state, one that supports its national discourse and narrative. GIS, on the other hand, is shown to be a device of neoliberal governmentality, its non-representational economic practices, divided discourse and subjectivities. Despite the seemingly hopeless situation surrounding GIS, however, certain simulation and modelling practices are attempting to construct subjectivities out of economic neoliberalism’s fractured narratives. They do this by reading meaning into otherwise mathematical datasets and models. These practices could form a basis for queering GIS.

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24

Robinson, Gary J., Nancy J. Obermeyer, and Jeffrey K. Pinto. "Managing Geographic Information Systems." Geographical Journal 162, no. 1 (1996): 112. http://dx.doi.org/10.2307/3060275.

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25

Wieczorek, William F., and Alan M. Delmerico. "Erratum: Geographic information systems." Wiley Interdisciplinary Reviews: Computational Statistics 2, no. 5 (2010): 635–36. http://dx.doi.org/10.1002/wics.123.

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26

Harris, Britton. "Beyond Geographic Information Systems." Journal of the American Planning Association 55, no. 1 (1989): 85–90. http://dx.doi.org/10.1080/01944368908975408.

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27

Wallington, Edward. "Managing Geographic Information systems." Photogrammetric Record 25, no. 129 (2010): 85–86. http://dx.doi.org/10.1111/j.1477-9730.2009.00562_2.x.

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28

Fowler, Eric. "Exploring Geographic Information Systems." Cartographic Perspectives, no. 28 (September 1, 1997): 32–35. http://dx.doi.org/10.14714/cp28.691.

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29

Tompkins, Paige L., and Linda H. Southward. "Geographic Information Systems (GIS)." Computers in Human Services 15, no. 2-3 (1999): 209–26. http://dx.doi.org/10.1300/j407v15n02_16.

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30

Joerger, Albert, Stephen D. DeGloria, and Malcolm A. Noden. "Applying Geographic Information Systems." Cornell Hotel and Restaurant Administration Quarterly 40, no. 4 (1999): 48–59. http://dx.doi.org/10.1177/001088049904000413.

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31

Popovich, V. V. "Information fusion and geographic information systems." Herald of the Russian Academy of Sciences 77, no. 4 (2007): 429–30. http://dx.doi.org/10.1134/s1019331607040181.

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32

Kenny, Stephen, and David Martin. "Geographic Information Systems: Socioeconomic Applications." Geographical Journal 163, no. 1 (1997): 104. http://dx.doi.org/10.2307/3059708.

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33

Rybaczuk, Krysia, and D. Martin. "Geographic Information Systems. Socioeconomic Applications." Geografiska Annaler. Series B, Human Geography 78, no. 3 (1996): 182. http://dx.doi.org/10.2307/490834.

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34

SHIRAYAMA, Susumu, and Tadao KOYAMA. "Map and Geographic Information Systems." Journal of the Visualization Society of Japan 23, no. 88 (2003): 2. http://dx.doi.org/10.3154/jvs.23.2.

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35

Pileggi, Salvatore, and Robert Amor. "Addressing Semantic Geographic Information Systems." Future Internet 5, no. 4 (2013): 585–90. http://dx.doi.org/10.3390/fi5040585.

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36

Coburn, Timothy C. "Geographic information systems: an introduction." Computers & Geosciences 26, no. 7 (2000): 853–54. http://dx.doi.org/10.1016/s0098-3004(99)00112-0.

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37

Sadiku, Matthew N. O., Mahamadou Tembely, and Sarhan M. Musa. "Geographic Information Systems: A Primer." International Journal of Advanced Research in Computer Science and Software Engineering 7, no. 3 (2017): 47–48. http://dx.doi.org/10.23956/ijarcsse/v7i3/01303.

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38

Muehrcke, Phillip C. "Cartography and Geographic Information Systems." Cartography and Geographic Information Systems 17, no. 1 (1990): 7–15. http://dx.doi.org/10.1559/152304090784005778.

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39

Lam, Nina. "Geographic Information Systems and Science." Annals of the Association of American Geographers 93, no. 1 (2003): 259–61. http://dx.doi.org/10.1111/1467-8306.93127.

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40

Thyne, John. "Geographic information systems in schools." New Zealand Geographer 61, no. 1 (2005): 51–52. http://dx.doi.org/10.1111/j.1745-7939.2005.00015.x.

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41

Freeland, N. P. "Microcomputer‐based geographic information systems." Information Technology for Development 1, no. 4 (1986): 257–64. http://dx.doi.org/10.1080/02681102.1986.9627081.

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42

Star, Jeffrey, and John Estes. "Geographic information systems: An introduction." Geocarto International 6, no. 1 (1991): 46. http://dx.doi.org/10.1080/10106049109354297.

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43

Langran, Gail. "Time in geographic information systems." Geocarto International 7, no. 2 (1992): 40. http://dx.doi.org/10.1080/10106049209354371.

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44

Retalis, A. "Geographic information systems and science." Photogrammetric Record 20, no. 112 (2005): 396–97. http://dx.doi.org/10.1111/j.1477-9730.2005.00343_5.x.

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45

Krygier, J. "Visualization in Geographic Information Systems." Cartographic Perspectives, no. 20 (March 1, 1995): 50–51. http://dx.doi.org/10.14714/cp20.899.

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46

Boyd, Bruce. "Geographic information systems and P2." P2: Pollution Prevention Review 6, no. 3 (1996): 75–80. http://dx.doi.org/10.1002/(sici)1520-6815(199622)6:3<75::aid-ppr7>3.0.co;2-7.

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47

Azzam, Tarek. "Mapping Data, Geographic Information Systems." New Directions for Evaluation 2013, no. 140 (2013): 69–84. http://dx.doi.org/10.1002/ev.20074.

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48

Green, R. "Geographic information systems in Europe." Cartographic Journal 27, no. 1 (1990): 40–42. http://dx.doi.org/10.1179/caj.1990.27.1.40.

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49

Goodchild, Michael F. "Geographic information systems and cartography." Cartography 19, no. 1 (1990): 1–13. http://dx.doi.org/10.1080/00690805.1990.10438482.

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50

Blakemore, Michael. "Cartography and Geographic Information Systems." Progress in Human Geography 9, no. 4 (1985): 566–74. http://dx.doi.org/10.1177/030913258500900406.

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