distancegeometrypythonshapely
Let's say we have the following point and polygon:
poly = Polygon([(0, 0), (2,8), (14, 10), (6,1)])
point = Point(4,4)
Because point lies within poly, the distance from the first to the latter will be zero (poly.distance(point) will return 0.0).
Is there a way to instead calculate the distance to the nearest edge?
Note: Effectively the same question as this, but desire a solution in Python, ideally with Shapely.
Integration is done by summing the values and multiplying the common cell area (equal to the square of the cellsize).
Here is an example region to illustrate.
Create the Euclidean distance grid to the complement of the polygons. To do this, convert the polygons to raster format. This will place NoData values at all cells outside the polygons. Use IsNull and SetNull to place NoData only at cells inside the polygons. The compute the Euclidean distance grid of that. When hillshaded it should look something like this, with peaks inside each polygon and "ridges" extending along their "skeletons":
Use math operations, such as those offered in the Raster Calculator, to compute the values of N. In the formula, "x" is the Euclidean distance grid and A..D are constants. Here is a picture of the resulting grid, in pseudo 3D perspective:
Using the original polygon grid as the zone grid, compute the zonal sum of the result of (2). It will be a table with one number for each grid. Multiply those numbers by the square of the zone grid's cell size: those are the desired values.
I have figured this one out.
I ended up using the NeighborFinder as I initially suspected. The trick is to store all candidate details in a list (I called it NeighbourList).
I then connected that to a ListExploder to create features from all elements in the list. Then I used a tester to filter out the features with a distance of zero. Finally, I used a VertexCreator to add a vertex at the candidate location to make a line.
The results are:
There is still some work needed to get rid of non-perpendicular lines at the bends of the black lines. But generally, the results are good.
Note the gap is where the lines are greater than 10km apart.
Best Answer
Compare the point to the polygon's exterior ring: