Applied Spatial Statistics

Professor
Peter Alexander Whigham
Eduardo de Rezende Francisco (Assistente)
 
Ementa
Applied Spatial Analysis considers methods for the description, representation, visualization and modelling of spatial (geographic) data. Spatial concepts are broadly divided into two areas: discrete representations as points, lines and polygons (Vector analysis) and continuous representations (Raster Analysis). These two models of spatial data are integrated in a Geographic Information System that allows cartographic models of spatial concepts to be incorporated into the modification and exploration of spatial data relationships. The concept of scale and spatial representation, meta-data and the appropriate integration of datasets, is key to interpreting spatial data and it’s fitness for use. The development of simple spatial models include the selection of space based on properties (classification), combining spatial data (overlay) and the use of models of diffusion for constraint-based modelling and resource selection. Spatial clustering concepts involve point/line/polygon objects and their distribution in space. Clustering may be used for problems such as detecting cancer clustering due to contamination or determining hot spots for crime or road accident analysis. In addition, concepts such as spatial non-stationarity, the use of spatial regression models and Monte-Carlo simulations are also fundamental concepts in spatial analysis.
 
Pré-requisito: Students who deal with patterns and relationships best represented as geographic data will benefit from a course in Spatial Analysis. They may be students with a background in fields as diverse as Geography, Computer Science, Public Health, Zoology, Botany or Marketing (to name a few) are likely to find this course valuable within their discipline. Students would be assumed to have some background in the use of computing systems for modelling (or a background in programming), preferable with at least one year of mathematics or statistics. No previous knowledge of Geographic Information Systems would be assumed.
 

Obs.: Esta disciplina valerá como eletiva de Administração, Análise e Tecnologia da Informação; Estratégias de Marketing; e Transformações do Estado e Políticas Públicas para os alunos das referidas Linhas de Pesquisa do CMCD AE e APG da FGV-EAESP.

Público-alvo: Destina-se a alunos dos Programas de Mestrado (acadêmico e profissional) e Doutorado da FGV-EAESP e de outras Instituições e professores interessados

Informações Importantes.

Créditos Aulas Datas Horário Sala Idioma
 2  30  from 4 to 8 July, 2016 (from monday to friday)  from 9 a.m. till 12 p.m. and from 2 p.m. till 5 p.m.  502  Inglês

Programa completo, clique aqui 

Voltar às Disciplinas                               Ir para página de inscrição

Portal FGVENG

Escolas FGV

Acompanhe na rede