Temperature annotated 3D Point Cloud of sweet cherry trees in climate chamber

Measurements were carried out at Leibniz Universität Hannover, using terrestrial orchard monitoring measurement yaw (TOMMY) developed by Leibniz-Institut für Agrartechnik und Bioökonomie e.V. (ATB), in 2023. Seven sweet cherry (Prunus avium) trees were allowed to acclimate to ambient temperature and then placed in cold conditions. Tree temperature was measured with a handheld IR thermometer and analysis based on fused data from terrestrial mobile 2D LiDAR sensor analysis and thermal camera to gain tree point clouds with temperature labels. Tree temperature acclimation data are provided here as an preliminary example file showing forced wetness appearance on the fruit surface, capturing fruit temperature and wetness reference data as well as T-annotated point clouds. Sensor Specifications LiDAR sensor (LRS4000, Sick AG, Waldkirch, Germany) Wavelength: 905 nm, angular resolution: 0.02°, scanning frequency: 25 Hz, scanning angle: 180°, laser aperture: 13.6 mm Thermal camera (A655sc, FLIR Systems Inc., MA, USA) with lens (T198065, FLIR Systems Inc., MA, USA) spatial resolution: 640 × 480 pixels at 50 Hz, spectral range: 7.5 – 14.0 μm, focal length: 6.5 mm, detects thermal differences < 30 mK IR-Thermometer (Microscanner D501, Exergen, Watertown, USA) Operational temperature: 0 - 50 °C, resolution: 0.1 °C, rms error: +/- 1 %, repeatability: 0.01 °C Files: *.xlsx file contain several clusters of fruit or single fruit during acclimation, representing geometric x, y, z data; return signal strength intensity, temperature remaining point clouds reference readings capturing manual temperature and wetness ground truth as well as temperature estimated by TOMMY Python code to read files. A total of 549 RGB images of cherry fruit used as reference for wetness classes are available on request.本数据集的测量工作于2023年在汉诺威莱布尼茨大学（Leibniz Universität Hannover）开展，采用由莱布尼茨农业技术与生物经济研究所（Leibniz-Institut für Agrartechnik und Bioökonomie e.V.，简称ATB）研发的地面果园监测偏航系统（Terrestrial Orchard Monitoring Measurement Yaw，简称TOMMY）完成。 共选取7株甜樱桃（Prunus avium）植株，先使其适应环境温度，随后转移至低温环境中。采用手持式红外测温仪记录树体温度，并基于地面移动二维激光雷达（LiDAR）传感器与热成像相机的融合数据开展分析，以获取带有温度标签的树体点云。本次提供的树体温度适应数据为初步示例文件，可呈现果实表面的强制湿润状态，同时包含果实温度与湿润度参考数据，以及带有温度标注的点云数据。 ### 传感器规格 1. 激光雷达传感器（LiDAR sensor，型号LRS4000，西克集团（Sick AG），德国瓦尔德基尔希）：波长905 nm，角分辨率0.02°，扫描频率25 Hz，扫描角度180°，激光孔径13.6 mm。 2. 热成像相机（Thermal camera，型号A655sc，FLIR系统公司，美国马萨诸塞州），搭配镜头（型号T198065，FLIR系统公司，美国马萨诸塞州）：空间分辨率为50 Hz下640×480像素，光谱范围7.5–14.0 μm，焦距6.5 mm，可检测小于30 mK的温差。 3. 红外测温仪（IR-Thermometer，型号Microscanner D501，Exergen公司，美国沃特敦）：工作温度范围0–50 °C，分辨率0.1 °C，均方根误差±1%，重复性0.01 °C。 ### 数据文件 1. *.xlsx文件：包含适应过程中多簇果实或单颗果实的几何坐标（x、y、z）数据、回波信号强度与温度信息；其余点云数据，以及手动记录的温度与湿润度真值参考数据，同时包含TOMMY系统估算的温度数据。 2. 附带读取该数据文件的Python代码。 3. 另有共计549张樱桃果实RGB图像，可作为湿润度分类的参考样本，需另行申请获取。