Archive for category: Spatial analysis

Is Moran’s I robust?

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 […]

R: Compute NDVI from Landsat images

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

R: Comparing two marked point patterns

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

R: K-function

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.

R: Analysis of precipitation trends in the US

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.

R: Classification breaks in R

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:

R: Kriging

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

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

R: Using matrix algebra to compute a Kriged value

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.