Hello,
I am trying to calculate a viewshed which shows different classes of visibility depending on its distance from a point (turbine). The outcome should be a shapefile which catagorizes the visibility of wind power stations into different visibility classes. To do so I tried different approaches, which appear to be long-winded and complicated. Right now I'm working with rather small data sets to get a better understanding of the processes. Later on I will have to find a way to automatize these processes in order to work with the real data.
So here is what I have so far.
Approach 1:
1 testturbine in a pointshape (turbine.shp)
1 dem
1)Calculate 4 serperate viewsheds with Radius2 of 1000m , 5000m, 7.500m and 15.000m from turbine.shp
2)convert all 4 rasters into polygons
3)dissolve all 4 rasters (dissolve field : gridcode)
4)manually remove the dissolved polygon with gridcode 0
5)create rings by erasing polgon3 (10.000m radius) from polygon4(15.000m radius) --> the same with polygon3-polygon2 & polygon2 - polygon1
6)add a field with a textvalue into each new polygon(-ring)
7)union all four polygons
Now I have a polygon which looks something like the picture I attached
Approach 2:
1 turbine in a pointshape (turbine.shp)
1 dem
1) Calculate 4 rings by using the multiple ring buffer tool
2) assign a specific text value to each ring to be able to use the split tool to create seperate shapes of rings
3) calculate the viewshed with the radius2 of 15.000m
4) convert raster to polygon
5) dissolve with field gridcode
6) intersect each ring with the 15.000m viewshed
7) union all four new polygons
Again I (after adding unique values) I have whats shown on the attached picture
I know that these approaches are probably way too complicated for achieving what I want. Which is why I signed up here to ask for help.
As I said before the methods I used work fine for small datasets, but later I will have like 800-1000 turbines and therefore wont be able to do the steps manually. I researched some python scripts which until now do the job with bigger datasets, but I guess there is a (much) easier way.
Again what I want to do is I want to modify the viewshed of a wind turbine, so that its visibility is catagorized by distance (radius) from the origin
Later on this has to be done to at least 800 other wind turbines, creating 800 more catagorized viewsheds which then will be "unioned" to one final polygone. In its attribute table will then be enough data to classify each polygon in viewing range of the turbine with a "level of visual disturbance".
I really hope you understand what I want to do here and can give me some helpfull advice. I have to apologize for my bad english, it's clearly not my native language.
