A Dataset of Thermal Infrared (TIR) and RGB Images of Lettuces, soil moisture data, and Pseudo-coloring RGB Images of the Lettuce’s Stressed Areas
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This dataset supports the article entitled "Integrating Thermal Infrared and RGB Imaging for Early Detection of Water Stress in Lettuces with Comparative Analysis of IoT Sensors". This dataset consists of Thermal Infrared (TIR) images with embedded visible-spectrum (RGB) images of two lettuces (Lactuca sativa var. capitata L), which were captured by a handheld dual Thermal Infrared and RGB camera two times per day for six days. The experiment took place in a lab for two lettuces, where one was irrigated normally, and the other was non-irrigated to have severe water stress. The RGB and TIR images are used initially for the lettuce canopy isolation from the background, the detection of the stressed areas over the lettuce’s leaves according to stomatal closure, and considering temperature value differences. The stressed areas in the lettuce canopy are annotated with pseudo-coloring on a newly generated RGB image. In addition, two capacitive soil moisture sensors log the soil moisture values per hour for six days for each lettuce. The dataset contains 26 raw TIR images with embedded RGB images, 26 RGB images with pseudo-coloring where plants’ stressed areas exist, aligned, and cropped based on the TIR images’ Field of View (FOV), and a file in CSV format with soil moisture values per hour for each lettuce.
本数据集用于支撑题为《结合热红外与RGB成像早期检测生菜水分胁迫并对比物联网（Internet of Things, IoT）传感器分析》的学术论文。该数据集包含内嵌可见光谱RGB（Red-Green-Blue）图像的热红外（Thermal Infrared, TIR）图像，拍摄对象为两株结球生菜（*Lactuca sativa* var. *capitata* L），由手持式热红外与RGB双摄相机每日拍摄两次，持续六天。实验在实验室环境下开展，两株生菜分别采用正常灌溉与非灌溉处理，其中非灌溉组会出现严重水分胁迫。最初使用RGB与TIR图像完成三项任务：从背景中分离生菜冠层、根据气孔闭合情况检测生菜叶片上的胁迫区域，并结合温度值差异开展分析。生菜冠层中的胁迫区域会在新生成的RGB图像上通过伪彩色进行标注。此外，两台电容式土壤湿度传感器每小时记录一次两株生菜的土壤湿度值，记录时长为六天。本数据集包含26张内嵌RGB图像的原始TIR图像、26张带有植物胁迫区域伪彩色标注的RGB图像，这些图像已根据TIR图像的视场（Field of View, FOV）完成对齐与裁剪，此外还包含一份以CSV格式存储的、每小时记录的两株生菜土壤湿度值文件。
