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The UK government provides a dataset on all UK postcodes under a modified UK OGL license. http://opendatacommunities.org/data/postcodes Some factors you may want to consider in your analysis: Distribution Reference: Population or Occupied Housing Units Variables: Land Use/Zoning Gross Domestic Product (GDP) per capita Government Subsidized Housing ...


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Well I can think of the following approach. I assume that you don't have access to the whole dataset of the entire postcodes. In general spatial distribution of postcodes will be similar to the population density or to the density of buildings. You can easily get most of the buildings of the UK from the OpenStreetMap. Converth them to points. Create a kernel ...


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Solution found! R.univar, despite the name, can actually calculate statistics on multiple raster at ones. My bad for not checking thoroughly. Thanks markusN for answering me..


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You were right, the r.series manual page was a bit lousy. I have hopefully improved it now. Comments certainly welcome. Concerning quantiles, if you want a single, i.e. a global map value, then check r.quantile or r.univar Example: Calculation of multiple elevation quantiles, results are printed and not stored as a new map: g.region rast=elevation -p ...


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From GWR by Roger Bivand: Geographically weighted regression (GWR) is an exploratory technique mainly intended to indicate where non-stationarity is taking place on the map, that is where locally weighted regression coefficients move away from their global values. Its basis is the concern that the fitted coefficient values of a global model, ...


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Much like jbsoq. 1) Convert the x,y data to a shapefile, here is the tutorial. 2) "Sample" or "Extract Multi Values to Points" to get the raster into the point shapefile. I prefer multi value. 3) Run Exploratory Regression on the data and his will give you most of what you want. 4) You now have the original values and the raster values in the attribute ...


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To add to msi_g's answer above: since you have multiple rasters you can use Extract Multi Values to Points then add a field to the attribute table of the point data and calculate whatever you want for all points individually, but you will have to type out the equation yourself. Also be cautious with multiple rasters that projections are the same and rasters ...


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This tool might be of benefit to you if you want to convert your rasters to vector. There is a OWA function and a WLC(weighted linear combination) there appears to be support for ArcGIS 10.1 and above. http://mcda4arcmap.codeplex.com/ and a paper http://www.ryerson.ca/~crinner/pubs/Pages12-13_from_Cartouche86_Winter-Spring2013.pdf


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In my education in GIS, I met some statistical methods, however I never encountered better, than AHP for weighting objectively. Unfortunately, there was only one software which provided built-in AHP support (surprisingly an entire wizard) for this purpose: IDRISI. There are some user scripts for ArcGIS, like AHP 1.1 or AHP-OWA 2.0, which has Ordered weighted ...


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Not entirely sure what you are after experimentally but you may want to investigate a Weights of Evidence approach.


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Thank you both for your very quick answers, which both solve my problem from a process point of view. Using OpenJump is much easier, but requires PC-power. ArcGIS requires licence money and a few more steps before getting there, but less hardware resources. PS. I dug even further into my long time favorite, GME, and found out that it actually has the ...


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using ArcGIS basic you can perform "intersect_analysis" (assuming your grid is made of polygons, otherwise you first need to convert to polygons), then compute the area of the new polygon, then use "summarize table" based on the grid index field (and the land use field as well, optionnally) that will be stored in your new feature class. the similar ...


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OpenJUMP does have a solution. You need the Plus version which includes the Aggregation plugin (Plugins - Analysis - Aggregation). EDIT I took execution time from a test where I used similarly sized datasets. I created a polygon layer with 1.2 million polygons and a polygon grid to present 26000 map sheet rectangles. Computing the parcel area per mapsheet ...



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