I have a set of (~200k) polygons showing deforestation in the Amazon. Each polygon is associated with a date when the deforestation happened.
Some of them are intersecting with each other, ie. one location is covered by multiple polygons. This is an error of the dataset - one place cannot be deforested twice (within a few years' time).
Since it is not feasible to manually check and resolve each of these situations, I want to get rid of these areas. So, for every polygon of the dataset. I want to remove/cut all of its parts where it intersects with other datasets.
Example:
On the picture, the purple and yellow rectangles represent two polygons that overlap. I'd like to cut out this overlapping part from both of the polygons.
I am preferably looking for a solution in Python. I have tried but failed to come up with a reasonable solution. Since this seems like a common spatial problem I imagine there should be some alternate solutions available.
.symmetric_difference()
in theshapely
package? Please, be aware that your question can be closed, because it does not contain any code and you used the python tag.