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KG2204 Exercise 2: Point to Polygon (and more)

Point to Polygon

Copy the folder T\:KG2204\Exercise 2 to your computer.

Open ArcMap and add the following files:

  • Point data with ancient monuments (fastighetskartanVektor_FS_1302_epsg3006_point.shp)
  • Election districts in Sweden (alla_valdistrikt.shp)
  • Excel file with the population 18 years old or older for each election district (population.xls)
  • Water (fastighetskartanVektor_MV_1302_epsg3006_polygon.shp)
  • Rectangle marking the study area (Study_Area.shp)

1. The intensity of monuments and spatial autocorrelation

Create (20 rows x 20 columns) rectangular polygons covering the study area with the tool:

ArcToolbox » Data Management Tools » Feature Class » Create Fishnet

If not open; click Show Help » and read through the information about the functions in the tool. The fishnet should have the same extent as the study area, and consist of 20 rows and columns. You want the results to be polygons.

Give the rectangular polygons values for the number of ancient monuments inside them by right clicking on the layer name of the rectangular polygons in the Table of Contents. Choose:

Joins and Relates » Join…

Do: Join data from another layer based on spatial location

Join your rectangular polygons with the ancient monuments.

All the rectangles have the same area and therefore you don’t need to normalize the number of monuments with the area to get the intensity of monuments.

Visualize the intensity of ancient monuments: Right click on the name of the joined layer and choose Properties…

Go to the tab Symbology and choose:

Quantities » Graduated colors

The value we want to visualize is Count_ Are there any patterns? Do neighboring polygons tend to be more similar than a random polygon? Check if that is the case by calculating the Moran’s I.

ArcToolbox » Spatial Statistics Tools » Analyzing Patterns » Spatial Autocorrelation (Morans I)

You could use CONTIGUITY_EDGES_ONLY as conceptualization of spatial relationships. The result of the analysis is found here:

:Geoprocessing » Results

Index is the value of Moran’s I (positive if there is spatial autocorrelation and not more than 1). The p value indicate if the result is significant.

2. Test the stability of where people live

Now we ask the data if people tend to live in the same areas today as they did during ancient times.

For that we use the election districts. Some of the election districts include a lot of water. Erase those parts from the election districts using the tool:

ArcToolbox » Analysis Tools » Overlay » Erase

Give the election districts values for the population by joining them with the Excel file. Right click on the layer name of the election district polygons with lakes erased. Choose:

Joins and Relates » Join…

Do: Join attributes from a table using the fields: election_d and election_district_id

Now we have the population for each district. We want to calculate the density and therefore also need the area.

Open the attribute table for the election districts layer you have joined with the population. Add a new field for area of the type Float in Table Options (the icon in the upper left corner at the attribute tables).

Right click on the name of the area column and click on Calculate Geometry to calculate the area in km2.

Add a new column for the population density (type: Float). Right click on the name of this new column and open the Field Calculator. Calculate the population divided with the area.

Count the number of points inside of each polygon in the same way as previous with the rectangular polygons (This can take a while).

Create a new column and calculate the density of the monuments. Export the table as a .dbf file using Table Options.

Open Microsoft Excel and open the dbf file (instead of All Excel Files, choose dBase Files). Copy or erase columns in a way that the population density column is to the right of the monument density column. Mark the both columns (include the headers) and choose:

Insert » (Charts) » Scatter » Scatter with only Markers

3. Test of monuments are close to water

If we instead ask the data if ancient monuments tend to be close to water or not, we can start with reusing the previous rectangular polygons with the count of monuments. We also want to create a raster file with the distance to water using the tool Euclidean Distance:

ArcToolbox » Spatial Analyst Tools » Distance » Euclidean Distance

Calculate the mean distance to water for each rectangular area using the tool:

ArcToolbox » Spatial Analyst Tools » Zonal » Zonal Statistics as Table

Join this new table to the rectangular polygons and export the joined attribute table and open it in Microsoft Excel. Make a scatter plot for how the count of monuments relates to the mean distance for each rectangle.

Observe that we this time ignored the proportion of the rectangle that consist of water.

The End

Put your intensity map and the two scatter plots in a Microsoft Word document and export the document as a PDF. Send in the PDF file on Mondo.

If you have time you can also practice map design using this application.

lab_point_to_polygon_and_point_to_raster.txt · Last modified: 2016/04/12 12:33 by ene