Javascript är avstängt eller blockerat i din webbläsare. Detta kan leda till att vissa delar av vår webbplats inte fungerar som de ska. Sätt på javascript för optimal funktionalitet och utseende.

Webbläsaren som du använder stöds inte av denna webbplats. Alla versioner av Internet Explorer stöds inte längre, av oss eller Microsoft (läs mer här: * https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Var god och använd en modern webbläsare för att ta del av denna webbplats, som t.ex. nyaste versioner av Edge, Chrome, Firefox eller Safari osv.

Ola Hall, photo.

Ola Hall

Universitetslektor, prefekt

Ola Hall, photo.

Remote sensing of yields : Application of UAV imagery-derived ndvi for estimating maize vigor and yields in complex farming systems in Sub-Saharan Africa

Författare

  • Ibrahim Wahab
  • Ola Hall
  • Magnus Jirström

Summary, in English

The application of remote sensing methods to assess crop vigor and yields has had limited applications in Sub-Saharan Africa (SSA) due largely to limitations associated with satellite images. The increasing use of unmanned aerial vehicles in recent times opens up new possibilities for remotely sensing crop status and yields even on complex smallholder farms. This study demonstrates the applicability of a vegetation index derived from UAV imagery to assess maize (Zea mays L.) crop vigor and yields at various stages of crop growth. The study employs a quadcopter flown at 100 m over farm plots and equipped with two consumer-grade cameras, one of which is modified to capture images in the near infrared. We find that UAV-derived GNDVI is a better indicator of crop vigor and a better estimator of yields—r = 0.372 and r = 0.393 for mean and maximum GNDVI respectively at about five weeks after planting compared to in-field methods like SPAD readings at the same stage (r = 0.259). Our study therefore demonstrates that GNDVI derived from UAV imagery is a reliable and timeous predictor of crop vigor and yields and that this is applicable even in complex smallholder farms in SSA.

Avdelning/ar

  • Institutionen för kulturgeografi och ekonomisk geografi

Publiceringsår

2018

Språk

Engelska

Publikation/Tidskrift/Serie

Drones

Volym

2

Issue

3

Dokumenttyp

Artikel i tidskrift

Förlag

MDPI AG

Ämne

  • Human Geography
  • Agricultural Science, Forestry and Fisheries

Nyckelord

  • Green normalized difference vegetation index
  • Maize yields
  • Near infrared
  • Remote sensing
  • Unmanned aerial vehicles

Status

Published

ISBN/ISSN/Övrigt

  • ISSN: 2504-446X