Mapping very-high-resolution evapotranspiration from unmanned aerial vehicle (UAV) imagery

Suyoung Park, Dongryeol Ryu, Sigfredo Fuentes, Hoam Chung, Mark O’Connell, Junchul Kim

Research output: Contribution to journalArticleResearchpeer-review

Abstract

There is a growing concern about water scarcity and the associated decline in Australia’s agricultural production. Efficient water use as a natural resource requires more precise and adequate monitoring of crop water use and irrigation scheduling. Therefore, accurate estimations of evapotranspiration (ET) at proper spatial-temporal scales are critical to understand the crop water demand and uptake and to enable optimal irrigation scheduling. Remote sensing (RS)-based ET estimation has been adopted as a method for large-scale applications when the detailed spatial representation of ET is required. This research aimed to estimate instantaneous ET using very-high-resolution (VHR) multispectral and thermal imagery (GSD < 8 cm) collected using a single flight of a UAV over a high-density peach orchard with a discontinuous canopy. The energy balance component estimation was based on the high-resolution mapping of evapotranspiration (HRMET) model. A tree-by-tree ET map was produced using the canopy surface temperature and the leaf area index (LAI) resampled at the corresponding scale via a systematic feature segmentation method based on pure canopy extraction. Results showed a strong linear relationship between the estimated ET and the leaf transpiration (n = 42) measured using a gas exchange sensor, with a coefficient of determination (R2) of 0.89. Daily ET (5.5 mm d-1) derived from the instantaneous ET map was comparable with daily crop ET (6.4 mm d-1) determined by the meteorological approach over the study site. The proposed approach has important implications for mapping tree-by-tree ET over horticultural fields using VHR imagery.

Original languageEnglish
Article number211
Number of pages15
JournalISPRS International Journal of Geo-Information
Volume10
Issue number4
DOIs
Publication statusPublished - 1 Apr 2021

Keywords

  • High-resolution mapping of evapotranspiration (HRMET)
  • Multispectral (MS) imagery
  • Surface energy balance model (SEBM)
  • Thermal infrared (TIR) imagery
  • Water use

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