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Hongxiao Jin

Forskare

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Drone-based hyperspectral and thermal imagery for quantifying upland rice productivity and water use efficiency after biochar application

Författare

  • Hongxiao Jin
  • Christian Josef Köppl
  • Benjamin M.C. Fischer
  • Johanna Rojas-Conejo
  • Mark S. Johnson
  • Laura Morillas
  • Steve W. Lyon
  • Ana M. Durán-Quesada
  • Andrea Suárez-Serrano
  • Stefano Manzoni
  • Monica Garcia
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Summary, in English

Miniature hyperspectral and thermal cameras onboard lightweight unmanned aerial vehicles (UAV) bring new opportunities for monitoring land surface variables at unprecedented fine spatial resolution with acceptable accuracy. This research applies hyperspectral and thermal imagery from a drone to quantify upland rice productivity and water use efficiency (WUE) after biochar application in Costa Rica. The field flights were conducted over two experimental groups with bamboo biochar (BC1) and sugarcane biochar (BC2) amendments and one control (C) group without biochar application. Rice canopy biophysical variables were estimated by inverting a canopy radiative transfer model on hyperspectral reflectance. Variations in gross primary productivity (GPP) and WUE across treatments were estimated using light-use efficiency and WUE models respectively from the normalized difference vegetation index (NDVI), canopy chlorophyll content (CCC), and evapotranspiration rate. We found that GPP was increased by 41.9 ± 3.4% in BC1 and 17.5 ± 3.4% in BC2 versus C, which may be explained by higher soil moisture after biochar application, and consequently significantly higher WUEs by 40.8 ± 3.5% in BC1 and 13.4 ± 3.5% in BC2 compared to C. This study demonstrated the use of hyperspectral and thermal imagery from a drone to quantify biochar effects on dry cropland by integrating ground measurements and physical models.

Avdelning/ar

  • Institutionen för naturgeografi och ekosystemvetenskap

Publiceringsår

2021-05-02

Språk

Engelska

Publikation/Tidskrift/Serie

Remote Sensing

Volym

13

Issue

10

Dokumenttyp

Artikel i tidskrift

Förlag

MDPI AG

Ämne

  • Physical Geography
  • Remote Sensing

Nyckelord

  • Biochar
  • Gross primary productivity (GPP)
  • Hyperspectral and thermal imagery
  • Unmanned aerial vehicle (UAV)
  • Upland rice
  • Water use efficiency (WUE)

Status

Published

ISBN/ISSN/Övrigt

  • ISSN: 2072-4292