Hi,

Also, before sending this to spss, I would investigate if the statistics you 
plan to use are resistant to the effects autocorrelation.  If not, you will 
violate the fact that each sample need to be independent of each other.  I 
would look for spatial statistics.  You can look at GeoDa, R spatial 
packages...  

Nicolas Cadieux
https://gitlab.com/njacadieux

> Le 27 mars 2021 à 15:18, Christine <geo.gu...@web.de> a écrit :
> 
> Dear Milena,
> 
> have a look at the tool  'Sample raster values' in QGIS Geoprocessing: This
> algorithm creates a new vector layer with the same attributes of the input
> layer and the raster values corresponding on the point location.
> 
> If you sample the values of your raster layers for your given points (large
> airports or outbreak location points) you should get what you want. To
> complete the parameters for your regression analysis you should probably
> also perform a distance analysis, perhaps with the tool 'Distance to nearest
> hub (points)', but I never used this tool. 
> 
> I would try the sampling of the rasters and a distance analysis focusing
> both on the airports and the outbreak location points as well. I mean
> approach the regression from both sides. 
> 
> Regards, Christine
> 
> 
> 
> 
> Milena Muehler wrote
>> ... I have several raster layers (population density; livestock density;
>> mammal density; etc.) and two text layers (so I've imported two csv files
>> with longitudes and latitudes into QGIS and now I have points about the
>> location of large airports and location points where there was a zoonotic
>> infectious disease outbreak). 
>> 
>> My intention is to „combine“ all layers and to get all the values under
>> this specific point of an outbreak. So that I have the exact value of the
>> population density, livestock density ans so on where the outbreak
>> occurred. I guess I have to make the calculation within a certain vicinity
>> though. 
>> [...]
>> In the end I want to have a file as an output with values to make
>> regression analysis in SPSS. 
> 
> 
> 
> 
> 
> --
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