利用热图像和环境温度估算土壤湿度

IF 2.2 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Apra Gupta;S Janardhanan;Shaunak Sen
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引用次数: 0

摘要

准确的土壤水分估算对于农业、生态和水资源管理等各种应用至关重要。本研究提出了一种利用热成像和环境温度数据进行无创SM估计的新方法。采用低空热感相机,对控制湿度条件下冲积土表面温度变化进行了观测。分析显示,在恒定湿度水平下,热图像温度与环境温度之间存在很强的线性关系。至关重要的是,发现这种线性关系的截距与SM成正比,从而能够开发估计模型。为了提高精度,采用了两阶段的方法:首先,根据平均像素强度将热图像分类为“湿”或“干”;然后,根据“湿”类别定制的线性模型用于水分估计。该方法在一系列湿度条件下估计SM的准确度为83.6%,突出了热成像的潜力,并且该方法作为有效和非侵入性SM监测的有价值工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Soil Moisture Estimation Using Thermal Image and Ambient Temperature
Accurate soil moisture (SM) estimation is vital for various applications, including agriculture, ecology, and water resource management. This study presents a novel approach for noninvasive SM estimation using thermal imaging and ambient temperature data. A low-altitude thermal sensing camera was employed to capture alluvial soil surface temperature variations under controlled moisture conditions. Analysis revealed a strong linear relation between thermal image temperature and ambient temperature at constant moisture levels. Crucially, the intercept of this linear relationship was found to be directly proportional to SM, enabling the development of an estimation model. To enhance accuracy, a two-phased approach was implemented: first, thermal images were classified as “wet” or “dry,” based on mean pixel intensity; then, a linear model tailored to the “wet” category was applied for moisture estimation. This method demonstrated 83.6% accuracy in estimating SM across a range of moisture conditions, highlighting the potential of thermal imaging and the presented methodology as a valuable tool for efficient and noninvasive SM monitoring.
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来源期刊
IEEE Sensors Letters
IEEE Sensors Letters Engineering-Electrical and Electronic Engineering
CiteScore
3.50
自引率
7.10%
发文量
194
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