Deterministic and stochastic weighting methods are commonly used methods for estimating missing precipitation rain gauge data based on values recorded at neighboring gauges. However, these spatial interpolation methods seldom check for their ability to preserve site and regional statistics. Such statistics and primarily defined by spatial correlations and other site-to-site statistics in a region. Preservation of site and regional statistics represents a means of assessing the validity of missing precipitation estimates at a site. This study evaluates the efficacy of traditional interpolation methods for estimation of missing data in preserving site and regional statistics. New optimal spatial interpolation methods intended to preserve these statistics are also proposed and evaluated in this study. Rain gauge sites in the state of Kentucky are used as a case study, and several error and performance measures are used to evaluate the trade-offs in accuracy of estimation and preservation of site and regional statistics. / by Husayn El Sharif. / Thesis (M.S.C.S.)--Florida Atlantic University, 2012. / Includes bibliography. / Mode of access: World Wide Web. / System requirements: Adobe Reader.

Made available in DSpace on 2014-12-17T14:13:35Z (GMT). No. of bitstreams: 1 JoseWQ_TESE.pdf: 1778874 bytes, checksum: 7ff2c9f470b5b3873803d39a321ee362 (MD5) Previous issue date: 2009-10-05 / This work demonstrates the importance of using tools used in geographic information systems (GIS) and spatial data analysis (SDA) for the study of infectious diseases. Analysis methods were used to describe more fully the spatial distribution of a particular disease by incorporating the geographical element in the analysis. In Chapter 1, we report the historical evolution of these techniques in the field of human health and use Hansen s disease (leprosy) in Rio Grande do Norte as an example. In Chapter 2, we introduced a few basic theoretical concepts on the methodology and classified the types of spatial data commonly treated. Chapters 3 and 4 defined and demonstrated the use of the two most important techniques for analysis of health data, which are data point processes and data area. We modelled the case distribution of Hansen s disease in the city of Mossor? - RN. In the analysis, we used R scripts and made available routines and analitical procedures developed by the author. This approach can be easily used by researchers in several areas. As practical results, major risk areas in Mossor? leprosy were detected, and its association with the socioeconomic profile of the population at risk was found. Moreover, it is clearly shown that his approach could be of great help to be used continuously in data analysis and processing, allowing the development of new strategies to work might increase the use of such techniques in data analysis in health care / O presente trabalho demonstra a import?ncia do uso de ferramentas relacionadas ? sistemas de informa??o geogr?fica (SIG) e an?lise espacial de dados (AED) em estudos de doen?as infecciosas. M?todos de an?lise foram usados para descrever de forma mais abrangente a distribui??o espacial de doen?as a partir da incorpora??o do elemento geogr?fico na an?lise. No Cap?tulo 1 relata-se a evolu??o hist?rica da aplica??o destas t?cnicas no campo da sa?de humana e elege-se a hansen?ase no estado do Rio Grande do Norte como exemplo de aplica??o. No Cap?tulo 2 introduzem-se alguns conceitos te?ricos b?sicos sobre a metodologia e classificam-se os tipos de dados espaciais comumente tratados. Os Cap?tulos 3 e 4 definem e demonstram a utiliza??o das mais importantes t?cnicas de an?lise para os dois principais tipos de dados encontrados na sa?de, quais sejam dados de processos pontuais e dados de ?rea, focalizando como estudo de caso a hansen?ase na cidade de Mossor? RN. Na an?lise, ? priorizada a utiliza??o do sistema R, disponibilizando-se scripts de rotinas e procedimentos de an?lise desenvolvidos pelo autor que podem ser facilmente utilizados por pesquisadores de diversas ?reas. Como resultados pr?ticos, importantes ?reas de risco da hansen?ase em Mossor? foram detectadas e sua forte associa??o com o perfil socioecon?mico da popula??o sob risco foi constatada. Al?m disso, estima-se que este trabalho possa vir a incrementar a utiliza??o de tais t?cnicas na an?lise de dados na ?rea de sa?de