GEOGRAPHICALLY WEIGHTED REGRESSION Outline GWR 3.0 Software for GWR (Brief) Overview of ArcMap Displaying GWR results in ArcMap stewart.fotheringham@nuim.ie http://ncg.nuim.ie ncg.nuim.ie/gwr/ ArcGIS? ArcMap? I Understanding ArcMap ArcMap is part of ArcGIS ArcGIS is a Geographic Information System It is a Windows application for handling spatial data GIS & GWR We often use GIS software before modelling with GWR Creating the data Integrating different data Re-projecting We use it after modelling with GWR Mapping the parameter estimates Mapping diagnostics Find the ArcGIS 9.2 folder and the ArcMap program Click on ArcMap to start it ArcMap
The ArcMap Display On the left is the Table of Contents On the right is the Data Frame Data Layers Spatial data that we use in ArcMap are known as data layers. A data layer might be a set of boundaries with some attributes (counties with socio-economic data) A data layer might be the output from a single GWR run Attributes The spatial data are those which you see as boundaries or locations in the Data Frame they tell you where things are The attribute data describe the characteristics of the boundaries or locations they tell you what is there Data Types We need to distinguish between different types of spatial data Polygons are used to represent areas (counties, land classes ) Points are used to represent point objects (trees, pylons ) Adding Data Let s take a look at some data for the counties of the state of Georgia Shapefile of county boundaries DBF file of some socio-economic data Click on the Add Data icon The SampleData Folder In the SampleData folder there are several datasets we will use for this workshop We navigate to the Georgia subfolder and select g_utm.shp
ArcMap makes an entry in the Table of Contents and displays the polygons with a default fill color A single layer You can easily interrogate the data for Georgia Select the Identify icon from the ToolBar and click on any polygon Spatial Query There are several attributes (fields) listed FID SHAPE AREANAME AREAKEY LATITUDE LONGITUD Attributes Attributes The attribute data is in a separate table (in this case a DBF file). There is one line of data for each area, with several fields (items) The AREAKEY field is also present in this file This allows data to be linked Adding Further Attribute Data We click on the Add Data icon once more and select the file GeorgiaData.dbf This is a DBaseIV format file one of several types that ArcMap can deal with Linking tables Another frequent operation is linking tabular files using a common item GeorgiaData is a table of socio economic information extracted from the Census Each line in the GeorgiaData table has an AreaKey that corresponds to the appropriate polygon in the map data. 13001 for example is Appling County
We click on g_utm.shp in the layer list, and then right click. Select Joins and relates / Join Joining Tables The Join Dialog This is filled in as on the right Then click on [OK] Now, right click on g_utm.shp again and select Properties Click the Symbology tab Properties We will symbolise quantities using graduated colors PCTBACH is % of residents in each county with a Bachelor s degree Symbology Exploring It s now easy to select another attribute, say % of residents living below the poverty line (PctPov) and map its spatial variation
Classifying There are several different ways of creating the class intervals for the map The pattern you see can often be an artefact of this You can change this: Classification schemes A wide range of automatic schemes are available Try Quantile Notice how the spatial pattern changes Beware Beware of the assumptions that your software is making. II Working with GWR 3.0 Output Now on to GWR
Visualizing the results The parameter estimates are usually written to Comma-Separated- Variables (CSV) file. We can create a shapefile from this in ArcGIS for further analysis In the parameter estimate output file, the coordinates of the regression points are in the first two columns, named FITX and FITY Importing the CSV file Click on the Add Data icon, find the.csv file and Add it to the list of layers Right click on the layer name and select Display XY Data Change the entries in the X Field and Y Field boxes to FITX and FITY respectively You can add a coordinate system if necessary Display XY Data And ignore. The second stage is to convert this event layer to a shapefile
Creating the shapefile Select Yes to add the resulting shapefile as a data layer. Select Export Data The new shapefile in ArcMap When the shapefile has been added This looks a mess, so we ll tidy it We can use Graduated Symbols to show the distribution of the intercept term The polygons now have no fill as their symbology Point Symbols Joining points to polygons Instead of the circles, it would be helpful to have the polygons shaded Can we add the data from the new layer onto the attribute table of the old layer? Yes The points have been numbered sequentially by GWR so we can t just join the tables using the AreaKey Point attributes
Spatial join We can use the fact that each regression point lies inside a single county s boundary GIS are good at this sort of spatial manipulation The output is a layer that combines the county boundaries with the attributes of the spatially corresponding regression point We use a spatial join for this Select the g_utm.shp county layer Properties/Joins Joining the table Mappable results The new layer is added to the data frame You can now explore the spatial variation in the parameter estimates and the other diagnostics Workaround: failed to run Occasionally there is a minor problem in running a GWR model. This is a bug. Click OK and rerun the Model Journey s end This seems rather complex It s not it s just that this form of analysis can t be hurried However, patterns are revealed quite quickly, and you can explore, model, and explore the results as you wish. In fact, your journey has only just begun! (Nearly) over to you Later we will work through some GWR examples using Gaussian models to give you some experience in (a) running GWR (b) importing the results to ArcMap (c) interpreting and mapping the results
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