I am looking for some constructive advice on how to successfully nominate the entrances to a local urban forest in my town (“Bosco di Via Carrer”).
The Context:
This is a well-known public urban woodland used daily by the community for jogging, walking, and cycling. It perfectly fits the Exercise and Exploration criteria.
The Problem:
Unfortunately, this park lacks official signs or nameboards at the specific access points. The entrances are only defined by wooden bollards/posts or wooden fencing that physically separate the paved road from the internal gravel paths.
The Rejections:
I have tried nominating these entrances focusing on the wooden infrastructure, but I keep receiving immediate automatic rejections (AI). I suspect the ML model sees “trees + ground” and immediately flags it as a “Natural Feature,” failing to recognize the wooden markers as a man-made entrance.
My Question:
Since there are no signs available to photograph, do you have any tips on how to frame the photo or write the description/supporting info to prove these are valid Access Points?
Has anyone had success getting “unmarked” trail/park entrances approved by highlighting the physical barriers/posts?
I have attached the photos of the candidates below.
The photos you have included seem good for the supplemental.
I would also make sure to tell reviewers in supplemental to look for the marked trail on Google maps. The submission may not get to human reviewers, but appeal reviewers can read that statement.
Can I ask you one last thing? What do you think about these? They are old stone markers from the local aqueduct connected to the land reclamation as here everything was a swamp.
I can’t make a judgment just from photos. I wpuld need more explanation about how these meet the criteria. I’d also want really good proof of what they are.
For example, the web submit allows you to upload multiple supplemental photos. Maybe one of those could be a rubbing of the stone to show what the writing says since it is too worn to read by sight now. And then google this project or these marker to get more information about them.
I like finding old boundary markers. It can sometimes be a challenge finding what they were for, but the more information you have the better. I’m surprised they were rejected by the ML system.
