UNIGIS MSc IN GEOGRAPHICAL INFORMATION SYSTEMS SPECIMEN PROJECT PROPOSAL FORM Before completing this form you are advised to read the MSc Study Guide.
Name: Jo Bloggs	Date: Feb. 1st 2006
Topic Title:  The potential of GIS and remote sensing technologies to model rainfall distribution data for malaria mitigation activities in Mozambique
Why is this topic acceptable for a research project? Why bother doing this research?  Throughout the world, around 2.5 million people die of malaria each year, with some 90% of those cases in Africa (WHO, 2004). Amongst those countries most greatly affected is Mozambique – which is also one of the poorest nations in the continent. Large areas of Mozambique are subject to malaria transmission often triggered by summer rainfall which provides the breeding sites of the female mosquito (of the genus Anopheles) that requires water to fulfill the aquatic stage in its life-cycle. Malaria mitigation activities rely heavily on knowledge of where water has fallen and how long pools of water will remain after a rainfall event (their residency time). As yet climate forecasts are not sufficiently accurate in the most part and the infrastructure makes the use of ground based meteorological stations an unrealistic option.  In common with a number of African nations, data from meteorological satellites is available (Meteosat and NOAA-AVHRR) and a small number of staff within ministries of health have already been exposed to GIS during workshops held in the UK. This research will seek to identify what specific role a rainfall modelling system might have for Mozambique’s malaria control activities and will prototype the necessary linkages between the satellite information, GIS models and existing (and anticipated) user skills for a more effective means of aiding mosquito control activities. In the future, adoption of this new technology and the associated methods and techniques may hopefully yield a more rapid and cost-effective means of monitoring and modelling the most important variable associated with malaria and other vector-borne diseases. Continue on a separate sheet if necessary
Aim: (Your research question) To ascertain the potential of GIS/RS technology for malaria mitigation activities by examination of data availability, methods and techniques required and future user needs.
Objectives: (How you intend to address the aim) Complete a literature review which addresses areas such as remote sensing technologies, GIS and RS systems, environmental influences on malaria transmission and existing disease mitigation systems Examine what GIS infrastructure exists (or might exist in the near future with some funding) and which remotely sensed data is available suitable for rainfall estimation Research, test and analyse appropriate rainfall estimation methods that can be incorporated within a GIS in a way that generates output meaningful to a malaria specialist Prototype the rainfall distribution model, dissemination of its output and how this information might be used effectively by the health end users in Mozambique Analyse the overall potential and feasibility of a future implementation of rainfall monitoring system for malaria modelling, addressing the specific infrastructure needs and constraints of Mozambique Continue on a separate sheet if necessary
Scientific Content: state areas of originality and science (as opposed to technical issues) your work will deal with   No previous work has been conducted within Mozambique to test if an automated rainfall monitoring/modelling system can be set-up. This will be the first time space-borne technology has been used directly to deal with a humanitarian issue within the region of the African continent.  In order to complete this work, a discussion and analysis of science relating to the following specific areas will be required: 1) Rainfall estimation using remote sensing. Either by direct means (radar and microwave sensors) or indirectly (Cold Cloud Duration using infrared data). 2) Simple precipitation-surface models that take account of infiltration (using knowledge of soil type), evaporation and interception 3) Calculation of rainfall pool residency times (the breeding sites of the female mosquito) 4) Synergy between remotely sensed data and GIS. Combining simple mathematical models requiring real-time RS data input and appropriate visual (spatial) output within a GIS and with a query interface easily used by a health end user 5) Issues and constraints relating to technical, infrastructure and financial aspects of the work
Research Method(s)  Specific methods are likely to change as the work progresses. However, methods most likely to be required are currently identified as: 1) A simple postal questionnaire targeted at health end users to ascertain what aspects of rainfall information they would find most useful 2) An audit of current GIS resources held by MoH in Mozambique and their access to remotely sensed data (e.g. TRMM or Meteosat products) 3) Formulation of simple mathematical model to process input RS data into desired output products (either using Visual Basic or macro/script language in an appropriate software package) 4) Methods to combine a simple model with a query and visualization interface within a suitable GIS software package 5) Appropriate analysis of feasibility in terms of resources available and anticipated technical/financial/political issues to be overcome. Continue on a separate sheet if necessary
Bibliography (please do not include UNIGIS Postgraduate Diploma units) You should include some recently published scientific journal conference proceedings, reports and book articles. Internet resources are not acceptable) Adejuwon J, Balogun E and Adejuwon S (1990). On the annual and seasonal patterns of rainfall fluctuations in sub-Saharan West Africa. International Journal of Climatology. 10: 839-848. Amissah-Arthur A and Jagtap SS (1999). Geographic variation in growing season rainfall during three decades in Nigeria using principal component and cluster analyses. Theoretical and Applied Climatology. 63: 107-116. Black E (2001). An observational study of the relationship between Indian Ocean temperatures and East African rainfall. I. College. Bonifacio R, Dugdale G and Milford JR (1993). Sahelian rangeland production in relation to rainfall estimates from Meteosat. International Journal of Remote Sensing. 14(14): 2695-2711. Bradley D (1997). From chilly summer afternoons to global warming. Climate as a determinant of human disease. Tropical Medicine and International Health. 2(9): 823-824. Connor S.J, Thomson M.C, Flasse S.P and Perryman A.H (1998). Environmental information systems in malaria risk mapping and epidemic forecasting. Disasters. 22(1): 39-56. Connor SJ, Flasse SP, Perryman AH and Thomson MC (1997). The contribution of satellite derived information to malaria stratification, monitoring and early warning. World Health Organization. : 1-31. Cresswell MP, Thomson MC, Morse AP, Connor SJ and Graham RJ. (1999) New advances in climate forecasting tools and satellite imagery for disease modelling. Transactions of the Royal Society of Tropical Medicine and Hygiene, 93, (2), 118 Dugdale G, Hardy S and Milford JR (1991). Daily catchment rainfall estimated from METEOSAT. Hydrological Processes. 5: 261-270. Dugdale G, McDougall V and Thorne V (1995). The TAMSAT method for estimating rainfall over Africa and its applications. RSS 21st Annual meeting, Remote Sensing Society. Flitcroft ID, Milford JR and Dugdale G (1989). Relating point to area average rainfall in semiarid West Africa and the implications for rainfall estimates derived from satellite data. Journal of Applied Meteorology. 28: 252-266. Hay SI and Lennon JJ (1999). Deriving meteorological variables across Africa for the study and control of vector-borne disease: a comparison of remote sensing and spatial interpolation of climate. Tropical Medicine and International Health. 4(1): 58-71. Hay SI, Packer MJ and Rogers DJ (1997). The impact of remote sensing on the study and control of invertebrate intermediate hosts and vectors for disease. International Journal of Remote Sensing. 18(14): 2899-2930. Hay SI, Snow RB and Rogers DJ (1998). Predicting malaria seasons in Kenya using multitemporal meteorological satellite sensor data. Transactions of the Royal Society of Tropical Medicine and Hygiene. 92: 12-20. Hay SI, Tucker CJ, Rogers DJ and Packer MJ (1996). Remotely sensed surrogates of meteorological data for the study of the distribution and abundance of arthropod vectors of disease. Annals of Tropical Medicine and Parasitology. 90(1): 1-19. Herman A, Kumar VB, Arkin PA and Kousky JV (1997). Objectively determined 10-day African rainfall estimates created for famine early warning systems. International Journal of Remote Sensing. 18(10): 2147-2159. Robinson T, Rogers D and Williams B (1997). Mapping tsetse habitat suitability in the common fly belt of Southern Africa using multivariate analysis of climate and remotely sensed vegetation data. Medical and Veterinary Entomology. 11: 235-245. Rogers DJ and Randolph SE (1991). Mortality rates and population density of tsetse flies correlated with satellite imagery. Nature. 351: 739-741. Continue on a separate sheet if necessary
Please contact Mark Cresswell, MSc Coordinator, or Tracy McKenna at the UNIGIS Office, Manchester Metropolitan University, if you require assistance in completing this form. This is only a preliminary project proposal and you should continue to work on your project whilst your proposal is processed.