%0 Conference Proceedings
%4 sid.inpe.br/mtc-m16d/2019/
%2 sid.inpe.br/mtc-m16d/2019/
%@issn 2179-4847
%A Felgueiras, Carlos Alberto,
%A Ortiz, Jussara de Oliveira,
%A Camargo, Eduardo Celso Gerbi,
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@electronicmailaddress carlos.felgueiras@inpe.br
%@electronicmailaddress jussara.ortiz@inpe.br
%@electronicmailaddress eduardo.camargo@inpe.br
%T PyESSDA - An User-friendly Python Application for Exploratory and Structural Spatial Dependence Analysis for Sample Points of Spatial Attributes
%B Simpósio Brasileiro de Geoinformática (GEOINFO)
%D 2019
%E Lisboa Filho, Jugurta,
%E Monteiro, Antonio Miguel Vieira,
%S Anais do 20º Simpósio Brasileiro de Geoinformática
%8 11 -13 nov. 2019
%J São José dos Campos
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%C São José dos Campos
%K geoinformatica.
%X This article describes the functionalities, for demonstration purposes, of the PyESSDA, an easy to use Python application, that allows for performing exploratory and structural spatial dependence analysis on a set of sample points representing geographic attributes. The PyESSDA exploratory analysis makes it possible to view the sample set in 2D and 3D projections, to report its univariate statistics and to generate its histogram. A semivariogram map can be generated to evaluate the isotropic or anisotropic spatial behavior of the investigated attribute. The analyzes of spatial dependencies, for determining the attribute spatial correlation structures, comprise the interactive creation of experimental and mathematical, or conceptual, semivariograms.
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%@language pt
%3 307-309.pdf