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I have a dataset that contains several hundred telemetry points for my focal species around twilight hours. data Attached to these points are mean values that represent how active the animal was 10 minutes before and after the GPS point was taken. That is, when the animal is inactive, the cooresponding point will have a value of 0, whereas if the animal is incredibly active (such as running), the value goes up to 175. As this data deals with wildlife, you can imagine that it is zero -inflated (animals rest a lot) and likewise, there will be some overlapping areas with high and low values histogram.

Is there a way to spatially interpolate this data as a means to visually assess areas where the animals are generally more active or inactive in ArcGIS?

EDIT: Here is the closest example that I can find from the literature (Mosser et al. 2014; while the questions are still somewhat different, the basic concept is similar. Unfortunately, It did not describe exactly what she method she utilised for visualization. example

  • I was about to suggest you to select only values that somewhat implies an activity, say greater than 0.18 as in your histogram and use kernel density tool of spatial analysis but not sure if this is what you want. Can you add a picture showing what you want to do say from a similar study? – fatih_dur May 21 '17 at 2:01
  • Thank you so much for your response, I edited it with an example, however, unfortunately, the authors didn't mention exactly what they utilised. Well, inactivity is still somewhat useful (as it shows where the animals aren't doing anything) however, maybe using 0.18 would work as it still probably represents no activity (all activity data represents the total mean activity within 10 minutes before and after a telemetry fix since the activity data is collected every 2 minutes whereas fixes are every 3 hours and 20 minutes). Thank you! – Redskies421 May 21 '17 at 9:57

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