## Archive for category: Spatial analysis

4 May, 2012 (12:15) | R, Spatial analysis | By: Manuel Gimond

Moran’s I (both global and local) is a measure of spatial autocorrelation. One form of its equation looks like this: Note the residual and spread terms. As such, Moran’s I can be sensitive to outliers. The following example demonstrates this point: You can map the simulated data as follows: The p-values from the Monte Carlo […]

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18 February, 2012 (23:44) | R, Remote Sensing, Spatial analysis | By: Manuel Gimond

Tags: Remote Sensing | No comments

31 January, 2012 (14:56) | R, Spatial analysis | By: Manuel Gimond

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2 November, 2011 (14:32) | R, Spatial analysis | By: Manuel Gimond

The following example assumes a stationary point process. This example does NOT assume a stationary process.

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5 November, 2010 (15:23) | R, Spatial analysis | By: Manuel Gimond

Data files used with the following script were downloaded from: ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/. The following figure shows the standardized regression coefficients from a Universal Kriging analysis of the Precip_total_coef_all_z.csv file (the values are in fact correlation coefficients). The time period spans 1975 – 2009.

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19 October, 2010 (08:57) | R, Spatial analysis | By: Manuel Gimond

Data for this exercise can be downloaded from Maine_pop. The resulting plots are shown side-by-side To display all the color palettes available from Brewer type:

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15 October, 2010 (16:00) | R, Spatial analysis | By: Manuel Gimond

!! Data for this exercise can be downloaded from here !!

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15 October, 2010 (14:04) | R, Spatial analysis | By: Manuel Gimond

The following example was created in R and was inspired from O’Sullivan and Unwin’s Geographic Information Analysis (1st edition) Data for this exercise can be downloaded here.

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