Thank you all for your input. As I mentioned in the original post, one of my goals in launching this project is to create a space for both citizen scientists and Peruvian taxonomists to view and identify a much narrower subset of iNaturalist observations, specifically, those occurring above 4,500 m. These expert-curated observations can then contribute to downstream biodiversity analyses.
I will try the approach described by @rupertclayton, breaking the original KML into simplified regional polygons. If that proves unworkable, I will instead simplify the polygon overall and accept that it will include some observations below my intended elevation threshold.
Thank you as well for the discussion around the inaccuracy of elevation data, particularly in steep terrain. I am aware of these limitations; similar errors also affect specimen data, which underpin many biodiversity studies.
I am geolocating my pictures with a GPS that gives me the altitude and loads it on the picture. Or my cellphone gives me altitude info as well on the picture. As I was âthereâ the gradient shouldnât play any role, whereas if I add the altitude from a map (GE) I will have that uncertainty.
There is the question of accuracy in all directions if a GPS gives a 3d or 2d position on a cliff. I assume that there are not all that many observers which optically triangulate their position
As others have pointed out, GPS locations for a camera or phone are satellite-based. Elevation is the least accurate variable of the x, y, and z coordinates in GPS. The accuracy depends on how many satellites your device was getting a signal from and that will change from minute to minute and also depends also on terrain, canopy cover, etc. If you are capturing data in a deep canyon or under a heavy forest canopy, satellite access will be limited. The dataâif accessible at allâwill be better than nothing and possibly better than consulting a map but just keep in mind that it may not be perfect. I havenât researched this in detail with modern phones and satellites, but Iâm sure somebody has done quantitative examination of such questions.
This is obviously correct, but how is altitude for any observation determined otherwise.
My GPS is calculating it from atmospheric pressure, which will be pretty accurate if you calibrated the GPS at a known point within the day of the obs.
You want to collect all observations in the Peruvian Andes above 4500m. What options do you have?
Select them by coordinates and compare against a .kml:
The coordinates are relatively accurate unless you are in a gorge without GPS satellite visibility.
They could as well be relatively accurate but on a slope that introduces insecurity.
The .kml is cumbersome and introduces further insecurity
The map projection introduces even more insecurity.
Triangulation: would be very accurate, but hellish cumbersome
Measured altitude with a calibrated altimeter (based on atmospheric pressure):
A GPS will do that and transfer the data into your meta data of your picture if you use a program like Geosetter. So, this is to my mind of thinking the best method of selecting the observations but requires the iNat application to make that data available. Most geolocated pictures will have this data available.
Itâs a pity the iNaturalist infrastructure canât automatically (based on a good enough global DEM) fill the missing altitude info for those observations that lack it.
This could benefit such a project, while making the dataset more versatile.
what i would do is create a collection project âPossible High Andean Flora of Peruâ using a simplified polygon, and then I would use a separate traditional project âHigh Andean Flora of Peruâ to collect observations that i could actually verify as having been collected above 4500m.
I reached out to @marceloamores, who has made similar projects using complex geometry for the PĂĄramos Ecuador project. He walked me through his workflow in Google Earth Engine and exported the elevation polygons for me, which were much smoother using his method.
@rupertclayton and anyone else interested in the alpine flora of Peru, it would be a pleasure to have you join the project! Thank you for your help.
Nicely done! And a fascinating ecoregion. I notice a few similar plants from my Aug 2025 visit to the PĂĄramo of the central Andes in Colombia like Plantago rigida.
I assume that there are not all that many observers which optically triangulate their position 