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Automated land cover classification for conservation and habitat monitoring

Posted by Mark Williams on May 8, 2015 at 4:25am

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I posted the results of my research into using a small UAV for land cover classification for habitat monitoring a couple of months ago.

I've created a short video as part of my research presentation that details the workflow used to analyse the image data and thought it may be of interest to the community. I'm more than happy to have a conversation about the project in the comments :)

Tags: apm, conservation, drones, habitat, monitoring, ndvi, nir
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Comments

  • Mark Williams May 11, 2015 at 7:09am
    *times
  • Mark Williams May 11, 2015 at 7:08am
    Martin, I'd agree. The UI can be awkward at tikes but you kind of get used to it.
  • Mark Williams May 10, 2015 at 1:50am
    Hey Adam. That's my understanding of it as well though in perhaps less florid terms. I'm still in the learning stage with a lot of these classification techniques but they're very interesting and finding the right technique and its use for the toolset is the challenge.
  • Adam Erickson May 9, 2015 at 11:59am

    These papers loosely describes eCognition's nearest neighbor supervised classification algorithm with fuzzy rules (link and link). It is based on the feauture space of the sample objects. eCognition provides a rich toolset for nearest neighbor classification that includes spatial autocorrelation and other contextual descriptors. In other words, it is principally object-based. There are an infinite number of ways one could mathematically describe what a nearest neighbor is, but here it refers to distance in the sense of multivariate space and either Euclidean or Mahalanobis distance, in what is likely a variation on the commonly used k-nearest neighbors (knn) algorithm.

    http://www.ecognition.com/sites/default/files/270_igarsswei.pdf
  • Martin May 9, 2015 at 6:05am

    Thanks Mark, the person in that particular video does not seem too fond of the user interface though.

  • Mark Williams May 9, 2015 at 2:10am
    Hi Martin, there's lots of YouTube videos about nearest neighbour classification in recognition. This one is on version 8 but should give you a good idea of how it works. https://youtu.be/vVQBiWWIAuM
  • Martin May 9, 2015 at 1:57am

    Hi Mark,

    Could you go into some more detail on how you're using eCognition? Maybe some screenshots or a video.

  • Mark Williams May 8, 2015 at 7:22am
    Hi Martin, you're right, generating the NDVI image in the GIS software is better and that is what I'm doing now.

    I'm using nearest neighbour classification in eCognition which is a learning algorithm of sorts.
  • Moderator
    Gary Mortimer May 8, 2015 at 6:48am

    Nice, very nice

  • Martin May 8, 2015 at 6:10am

    I read your previous post and you said you used imageJ for the falsecolor image. I think it's a much better idea to use GIS software like QGIS for the purpose. All the georeference data is preserved that way.

    Could you talk about the automation part of your work. Are you using a learning algorithm for classification?

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