I am working on filter for biogeographical data. It is based on citizen science principle. People put new point data to database and I want add information about "reliability" or probability (maybe expressed by score) of added point. Please look on the picture for better understanding.

I need predict probability or score that green point is placed good based on old data

In the picture it is visualize like zones with score, but it is only one way how to get something like this. Other maybe should be use distance between points. I don't know what I should find and where I should start finding.

What should I search on the internet and books when I need explore more ways how predict probability (or some type of score) to express new added point is placed good (It can be placed there)?

I need handle it in python but for a start it is probably good idea try it in QGIS or ArcGIS, or other software.


So I tried something like this:

enter image description here

It looks it works but, what do you think. Is it good approach with appropriate formula?

Then I thought about Mean of Inverse distance. What do you think about this approach?

Should I define some buffer or distance where I will take points into account for RMSE?

  • Look into the Root Mean Squared Error (RMSE) which is a de facto standard in this type of assessment. May 7, 2016 at 17:48
  • Hi, thanks for you reply and sorry for my late answer. I was too busy and forgot for this my question. What do you think about edited question please? You can rewrite your comment to answer and I will mark it as good.
    – Bulva
    Jul 21, 2016 at 17:35