Spatiotemporal water use mapping of a commercial apple orchard using UAS based spectral imagery

A. Chandel, L. Khot, C. Stöckle, R. Peters, Steve Mantle
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Abstract

Crop water use estimation at high geospatial resolution is critical for site-specific irrigation management of perennial specialty crops. This study aims to map actual evapotranspiration (ETa) of a commercial apple orchard using unmanned aerial system (UAS) based thermal and multispectral imagery and a widely adopted METRIC (Mapping Evapotranspiration at High Resolution with Internalized calibration) energy balance model (UASM). Four imaging campaigns were conducted during the 2020 growth season and weather data for pertinent days was downloaded from the nearest WSU-AgWeatherNet network station. 24-h ETa was also calculated from the soil water balance (SWB) approach that used soil moisture data from sensors installed at three locations and down to depth of 111 cm. A high linear correlation (r) of 0.84 and non-significant difference (p = 0.5) was observed between UASM derived ETa (5.05 ± 0.8 [Mean ± Std. Dev.] mm day-1) and SWB calculated ETa (5.44 ± 1.81 mm day-1). Notable differences in spatiotemporal water use and crop-coefficients were observed within the orchard. A moderately strong correlation was also observed between the UASM derived crop-coefficients and multispectral imagery derived Normalized Difference Vegetation Index (r = 0.69) that may also be used for estimating actual crop water use. Overall, approach presented in this study may help identify under or over-irrigated areas within the orchard. It may also assist in developing site-specific irrigation prescription maps and schedules.
利用基于UAS的光谱图像绘制商业苹果园的时空水资源利用图
高地理空间分辨率作物水分利用估算对多年生特色作物的定点灌溉管理至关重要。本研究旨在利用基于无人机系统(UAS)的热成像和多光谱图像以及广泛采用的METRIC (Mapping evapotranspiration at High Resolution with Internalized calibration)能量平衡模型(UASM)绘制商业苹果园的实际蒸散发(ETa)。在2020年生长季节进行了四次成像活动,并从最近的wsu agweathernet网络站点下载了相关日期的天气数据。24小时ETa也通过土壤水分平衡(SWB)方法计算,该方法使用安装在三个位置的土壤水分数据,深度为111 cm。UASM计算的ETa(5.05±0.8 [Mean±Std. Dev.] mm day-1)与SWB计算的ETa(5.44±1.81 mm day-1)之间存在高度线性相关(r = 0.84),差异无统计学意义(p = 0.5)。果园内水分利用和作物系数的时空差异显著。UASM导出的作物系数与多光谱图像导出的归一化差异植被指数(r = 0.69)之间也存在中等强度的相关性,该指数也可用于估算实际作物用水量。总的来说,本研究提出的方法可能有助于确定果园内灌溉不足或过度的地区。它还可以协助制定特定地点的灌溉处方地图和时间表。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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