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.
Highlights
This study examined ET’s estimation using very-high-resolution (VHR) multispectral and thermal imagery derived from unmanned aerial vehicle (UAV) sensing
The energy balance components were estimated based on the high-resolution mapping of evapotranspiration (HRMET) surface energy balance model
Tree-by-tree analytic maps were produced by the systematic feature segmentation method based on pure canopy extraction and statistical analysis of the distribution of surface temperatures and leaf area index (LAI)
Summary
Water scarcity has long been an important issue in Australia, and has resulted in declined production in irrigated agriculture at a national scale [1]. Efficient water use in agriculture requires improved irrigation management informed by accurate monitoring of crop water requirements. In the case of high-value horticultural crops, e.g., pear, peach, grape, and olive, various studies have investigated the effect of deficit irrigation, including regulated deficit irrigation (RDI) [2,3], to increase fruit quality while maintaining yield [4,5]. Optimal irrigation water volume and understanding crop water uptake and loss. Crop ET estimations inform farmers of water consumption and plant available water in the soil, which are key inputs for irrigation management and scheduling
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