GeoDa 1.8 介绍
GeoDa是由 Luc Anselin 博士和其团队开发的. 该程序提供了友好的用户界面以及丰富的用于探索性空间数据分析(ESDA)的方法，比如空间自相关统计(spatial autocorrelation statistics)和基本的空间回归分析(spatial regression analysis)。
从2003年2月GeoDa发布第一个版本以来， GeoDa的用户数量 成倍的增长。截止2016年4月，GeoDa的用户数量已经超过了15万。 包括哈佛，麻省理工、康奈尔等著名大学都在实验室中安装并使用GeoDa软件。GeoDa软件得到了用户和媒体广泛的好评，被称之为“一个非常重要的分析工具”，“一款制作精良的软件”，有着“激动人心的进展”。
GeoDa最新发布的版本是1.8。其包含了很多新的功能，比如：支持更多的空间数据格式，支持时空（space-time)数据，支持包括Nokia和CartoDB提供的底图(Basemap)显示，均值比较图表(averages charts)，散点图矩阵(scatter plot matrices)，非参数的空间自相关图(nonparametric spatial autocorrelation--correlogram)，以及灵活的数据分类方法(flexible data categorization)。
跨平台：GeoDa可以运行在Windows， MacOSX 和 Linux (Ubuntu) 系统上。
GeoDa now supports a larger variety of vector data in different formats: You can work with shapefiles, geodatabases, GeoJSON, MapInfo, GML, KML, and other vector data formats supported by the GDAL library. The program also converts coordinates in table format (.csv, .dbf, .xls, .ods) to one of these spatial data formats and converts data between different file formats (such as .csv to .dbf or shapefile to GeoJSON). Selecting a subset and exporting it as a new file is now also possible.
Connect to CartoDB from Within GeoDa
You can now load data from CartoDB into GeoDa and save results back to the CartoDB table. See how this works.
In contrast to programs that visualize raw data in maps, GeoDa focuses on exploring the results of statistical tests and models through linked maps and charts.
You can now group the same variable across time periods in the new Time Editor to explore statistical patterns across space and time. Then explore results as views change over time with the Time Player.
If your spatial data are projected (.prj file), you can now add a basemap to any map view, including cluster maps, for better orientation and for ground-truthing results.
A new Averages Chart compares values that are averaged over time and/or space and tests if the differences in these means are significant. For instance, first select if you want to compare means of selected vs. unselected observations in the same time period or compare all observations for different time periods. A basic pre-post/impact-control test then indicates if your results changed over time and space (using an F-test and difference-in-difference test).
A scatter plot matrix allows you to explore multiple bivariate correlations at once. In this example, the regression slopes for selected, unselected and all police precincts in San Francisco are shown to explore relationships between four types of crime.
Use a global or local Differential Moran?s I test to find out if a variable?s change over time in a given location is statistically related to that of its neighbors. For instance, this local (LISA) cluster map shows hotspots in New York with larger changes in the share of kids between 2002 and 2008 (and coldspots with smaller changes).
A nonparametric spatial autocorrelation test (correlogram) is now available to determine distance thresholds when the values of neighboring pairs are no longer correlated.
With the new category editor, you can explore how sensitive your results are to changes in the thresholds that categorize your data. In this example the thresholds in the conditional map (right) are based on the categories that can be adjusted in the category editor (left).
GeoDa is released under a GPL license. It builds on several open source libraries and source-code files. Below is the list of the key projects that we would like to acknowledge.
GDAL Libraries, version 1.10 License: X/MIT style Open Source license Authors: many Links: http://www.gdal.org/
Boost Libraries, version 1.53 License: Boost Software License - Version 1.0 Authors: many Links: http://www.boost.org/ http://www.boost.org/LICENSE_1_0.txt
Boost.Polygon Voronoi Library, Boost version 1.53 License: Boost Software License - Version 1.0 Author: Andrii Sydorchuk Links: http://www.boost.org/ http://www.boost.org/LICENSE_1_0.txt
wxWidgets Cross-Platform GUI Library, version 2.9.4 License: The wxWindows Library Licence Authors: Julian Smart, Robert Roebling, and others Links: http://www.wxwidgets.org/ http://www.opensource.org/licenses/wxwindows.php
CLAPACK Linear Algebra Libraries, version 3.2.1 Authors: many License: Custom by University of Tennessee Links: http://www.netlib.org/clapack/ http://www.netlib.org/lapack/lapack-3.2/LICENSE
Approximate Nearest Neighbor Library, version 0.1 Note: Full source of 0.1 release included in kNN directory Authors: Sunil Arya and David Mount License: See kNN/AHH.h in included source files Links: http://www.cs.umd.edu/~mount/ANN/
FastArea.c++ source code Note: We have based the source for functions findArea and ComputeArea2D in our file GenGeomAlgs.h from FastArea.c++ in Journal of Graphics Tools, 7(2):9-13, 2002 Author: Daniel Sunday License: unknown Links: http://jgt.akpeters.com/papers/Sunday02/FastArea.html
logger.h source code Author: Seweryn Habdank-Wojewodzki Note: We have copied the source for logger.h and modified it slightly to work with wxString. License: Boost Software License - Version 1.0 Links: http://accu.org/index.php/journals/1304
nullstream.h source code Author: Maciej Sobczak License: See logger.h in included source files Links: http://www.msobczak.com/
The development of GeoDa has most recently been supported by the National Science Foundation, the National Institutes of Health, the National Institute of Justice, and the Agency for Healthcare Research and Quality.
We are currently updating the documentation to reflect the new features in GeoDa 1.8. The Openspace listserv supports technical questions about GeoDa.
GeoDa uses a GPL License (General Public License).