IDEAS home Printed from
   My bibliography  Save this article

Predictive analytics for reducing human-animal conflict


  • Singh, Nitin
  • Islam, K M Baharul


Forest-adjoining areas are prone to human-animal conflict. In such areas, there is an urgent need to develop methods that prevent animal intrusion in human habitats while also ensuring that wild animals are not harmed. We have applied data science to track animal (in this case, the Indian panther) movement in forests and animal intrusion in villages adjoining the forest environment. The Indian panther (Panthera pardus fusca) is a panther subspecies distributed across the Indian subcontinent. We find that analytics on pugmark data can be effectively applied to simulate movement of the animal and thus undertake preventive measures.

Suggested Citation

  • Singh, Nitin & Islam, K M Baharul, 2017. "Predictive analytics for reducing human-animal conflict," International Journal of Development and Conflict, Gokhale Institute of Politics and Economics, vol. 7(2), pages 81-96.
  • Handle: RePEc:gok:ijdcv1:v:7:y:2017:i:2:p:81-96

    Download full text from publisher

    File URL:
    Download Restriction: no


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gok:ijdcv1:v:7:y:2017:i:2:p:81-96. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.