Estimation of Evaporation and Drought Stress of Pistachio Plant Using UAV Multispectral Images and a Surface Energy Balance Approach

IF 3.1 3区 农林科学 Q1 HORTICULTURE Horticulturae Pub Date : 2024-05-16 DOI:10.3390/horticulturae10050515
Hadi Zare Khormizi, Hamid Reza Ghafarian Malamiri, Carla Sofia Santos Ferreira
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Abstract

Water scarcity is a critical abiotic stress factor for plants in arid and semi-arid regions, impacting crop development and production yield and quality. Monitoring water stress at finer scales (e.g., farm and plant), requires multispectral imagery with thermal capabilities at centimeter resolution. This study investigates drought stress in pistachio trees in a farm located in Yazd province, Iran, by using Unmanned Aerial Vehicle (UAV) images to quantify evapotranspiration and assess drought stress in individual trees. Images were captured on 10 July 2022, using a Matrix 300 UAV with a MicaSense Altum multispectral sensor. By employing the Surface Energy Balance Algorithm for Land (SEBAL), actual field evapotranspiration was accurately calculated (10 cm spatial resolution). Maps of the optimum crop coefficient (Kc) were developed from the Normalized Difference Vegetation Index (NDVI) based on standard evapotranspiration using the Food and Agriculture Organization (FAO) 56 methodology. The comparison between actual and standard evapotranspiration allowed us to identify drought-stressed trees. Results showed an average and maximum daily evaporation of 4.3 and 8.0 mm/day, respectively, in pistachio trees. The real crop coefficient (Kc) for pistachio was 0.66, contrasting with the FAO 56 standard of 1.17 due to the stress factor (Ks). A significant correlation was found between Kc and NDVI (R2 = 0.67, p < 0.01). The regression model produced a crop coefficient map, valuable to support precise irrigation management and drought prevention, considering the heterogeneity at the farm scale.
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利用无人机多光谱图像和地表能量平衡法估算开心果植物的蒸发量和干旱压力
对于干旱和半干旱地区的植物来说,缺水是一个关键的非生物压力因素,影响着作物的生长发育、产量和质量。要在更精细的尺度(如农场和植物)上监测水分胁迫,需要具有热功能的厘米级分辨率的多光谱图像。本研究利用无人飞行器 (UAV) 图像量化蒸散量并评估单棵树木的干旱压力,从而调查伊朗亚兹德省一个农场中开心果树的干旱压力。图像拍摄于 2022 年 7 月 10 日,使用的是配备 MicaSense Altum 多光谱传感器的 Matrix 300 无人机。通过采用土地表面能量平衡算法(SEBAL),准确计算出了实际的田间蒸散量(空间分辨率为 10 厘米)。根据归一化差异植被指数 (NDVI),在标准蒸散量的基础上,采用联合国粮农组织 (FAO) 56 方法绘制了最佳作物系数 (Kc) 图。通过比较实际蒸散量和标准蒸散量,我们可以确定受旱树木。结果显示,开心果树的日平均蒸发量为 4.3 毫米,日最大蒸发量为 8.0 毫米。开心果的实际作物系数(Kc)为 0.66,与联合国粮农组织(FAO)56 项标准中由于压力因子(Ks)而得出的 1.17 形成鲜明对比。Kc 与 NDVI 之间存在明显的相关性(R2 = 0.67,p < 0.01)。考虑到农场尺度上的异质性,回归模型生成了作物系数图,这对支持精确灌溉管理和干旱预防非常有价值。
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来源期刊
Horticulturae
Horticulturae HORTICULTURE-
CiteScore
3.50
自引率
19.40%
发文量
998
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