• DocumentCode
    143705
  • Title

    Topsoil moisture estimation for precision agriculture using unmmaned aerial vehicle multispectral imagery

  • Author

    Hassan-Esfahani, Leila ; Torres-Rua, Alfonso ; Ticlavilca, Andres M. ; Jensen, Austin ; McKee, Mac

  • Author_Institution
    Utah Water Res. Lab., Utah State Univ., Logan, UT, USA
  • fYear
    2014
  • fDate
    13-18 July 2014
  • Firstpage
    3263
  • Lastpage
    3266
  • Abstract
    There is an increasing trend in crop production management decisions in precision agriculture based on observation of high resolution aerial images from unmanned aerial vehicles (UAV). Nevertheless, there are still limitations in terms of relating the spectral imagery information to the agricultural targets. AggieAir™ is a small, autonomous unmanned aircraft which carries multispectral cameras to capture aerial imagery during pre-programmed flights. AggieAir enables users to gather imagery at greater spatial and temporal resolution than most manned aircraft and satellite sources. The platform has been successfully used in support of a wide variety of water and natural resources management areas. This paper presents results of an on-going research in the application of the imagery from AggieAir in the remote sensing of top soil moisture estimations for a large field served by a center pivot sprinkler irrigation system.
  • Keywords
    autonomous aerial vehicles; crops; moisture measurement; remote sensing; soil; AggieAir; crop production management decision; precision agriculture; spatial resolution; spectral imagery information; temporal resolution; topsoil moisture estimation; unmmaned aerial vehicle multispectral imagery; Agriculture; Estimation; Image resolution; Moisture; Remote sensing; Soil moisture; Unmanned aerial vehicles; AggieAir; High Resolution Imaging; Learning Machines; Remote Sensing; Soil Moisture;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
  • Conference_Location
    Quebec City, QC
  • Type

    conf

  • DOI
    10.1109/IGARSS.2014.6947175
  • Filename
    6947175