• DocumentCode
    720482
  • Title

    A detailed field study of direct correlations between ground truth crop water stress and normalized difference vegetation index (NDVI) from small unmanned aerial system (sUAS)

  • Author

    Tiebiao Zhao ; Stark, Brandon ; Yangquan Chen ; Ray, Andrew L. ; Doll, David

  • Author_Institution
    Embedded Syst. & Autom. Lab., Univ. of California, Merced, Merced, CA, USA
  • fYear
    2015
  • fDate
    9-12 June 2015
  • Firstpage
    520
  • Lastpage
    525
  • Abstract
    Aerial images with high spatial resolution and high temporal resolution were used to detect water stress based on canopy level normalized difference vegetation index (NDVI). We attempted to determine the correlation between stem water potential (SWP) and canopy NDVI with and without shade. Results indicated that removing the shade from the canopy improved the correlation between the NDVI of canopy and SWP with coefficient of determination (R2) from 0.001 to 0.0052. We further compared SWP and the NDVI of the canopy without shade over a period of one week to four weeks. The correlation between NDVI with SWP was highest in the time range of three weeks. However, both cases show that there is no obvious relationship between NDVI of canopy and SWP. Therefore, canopy level NDVI does not indicate water stress. Further research is needed beyond pretty pictures.
  • Keywords
    autonomous aerial vehicles; crops; image resolution; industrial robots; SWP; aerial images; canopy NDVI; canopy level normalized difference vegetation index; ground truth crop water stress; sUAS; small unmanned aerial system; spatial resolution; stem water potential; temporal resolution; water stress detection; Cameras; Correlation; Irrigation; Stress; Vegetation; Water resources; NDVI (normalized difference vegetation index); SWP (stem water potential); crop canopy; crop water stress;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Unmanned Aircraft Systems (ICUAS), 2015 International Conference on
  • Conference_Location
    Denver, CO
  • Print_ISBN
    978-1-4799-6009-5
  • Type

    conf

  • DOI
    10.1109/ICUAS.2015.7152331
  • Filename
    7152331