A comparative estimation of maize leaf water content using machine learning techniques and unmanned aerial vehicle (uav)-based proximal and remotely sensed data

HIGHLIGHTS

• who: Helen S. Ndlovu and collaborators from the University of KwaZulu-Natal, Scottsville, Pietermaritzburg, South Africa have published the research: A Comparative Estimation of Maize Leaf Water Content Using Machine Learning Techniques and Unmanned Aerial Vehicle (UAV)-Based Proximal and Remotely Sensed Data, in the Journal: (JOURNAL) of 11/02/2021
• what: This study evaluated the utility of UAV-derived multispectral imagery and machine learning techniques in estimating maize leaf water indicators: equivalent water thickness (EWT) fuel moisture content (FMC) and specific leaf area (SLA). The aims of this study were to conduct a comparative . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

  If you don't have an account, you can create one here.