Thermal imagery acquired from an Uncrewed Aerial System (UAS) and hydroacoustic measurements of flow velocity collected along the Sacramento River, California, November, 2023

A reach of the Sacramento River near Glenn, California, was selected as a field site to test a sensor payload developed by the U.S. Geological Survey and the National Aeronautics and Space Administration for estimating surface flow velocities in rivers. The payload, called the River Observing System (RiOS), can be deployed from an uncrewed aircraft system (UAS). RiOS includes visible and thermal cameras, a laser range finder, an inertial navigation system, an embedded computer for storing and processing data, and a wireless link for transmitting data to a ground station. This data release includes thermal imagery acquired by RiOS and stored in Robot Operating System (ROS) *.bag files. The bag files are organized into two separate zip archives, one for each date of data collection. Foxglove Studio, an open-source data visualization tool, can be used to view the thermal images contained within the bag files (see link in Related External Sources). Once the thermal bag file is loaded in Foxglove Studio, open the settings and set the color mode to gradient and the minimum and maximum values to 12,000 and 15,000, respectively (see Foxglove.jpg in Attached files). The minimum and maximum values can be adjusted from these default values to enhance image contrast. The thermal images were used as input to an image velocimetry algorithm to estimate the surface flow velocities along the river. To assess the accuracy of these image-derived velocity estimates, field measurements of flow velocity were obtained using a SonTek M9 acoustic Doppler current profiler (ADCP) using the RiverSurveyor Live software package. ADCP measurements were collected along multiple pre-planned cross section lines oriented perpendicular to the primary downstream flow direction. At each transect, multiple ADCP passes were made and the data was then processed using the Velocity Mapping Toolbox (VMT) to produce mean cross sections (Parsons et al., 2013). The output from VMT consisted of a single comma delimited text file with the following seven column headers: 1) xs: the river transect stationing in meters; 2) x_meters: easting (x) spatial coordinate in meters; 3) y_meters: northing (y) spatial coordinate in meters; 4) depth_meters: depth in meters; 5) vmag_meters_per_second: the depth-averaged velocity magnitude in meters per second; 6) u_meters_per_second: east (u) component of the depth-averaged velocity vector in meters per second; and 7) v_meters_per_second: northing (v) component of the depth-averaged velocity vector in meters per second. The spatial coordinates are projected in Universal Transverse Mercator (UTM) Zone 10, World Geodetic System 1984 (WGS-84) datum.

加利福尼亚州格伦附近的萨克拉门托河河段被选为野外试验站点，用于测试由美国地质调查局（U.S. Geological Survey）与美国国家航空航天局（National Aeronautics and Space Administration）联合研发的传感器载荷，该载荷旨在估算河流表面流速。该载荷名为河流观测系统（River Observing System，RiOS），可通过无人飞行器系统（UAS，Uncrewed Aircraft System）部署。RiOS集成了可见光与热红外相机、激光测距仪、惯性导航系统、用于数据存储与处理的嵌入式计算机，以及用于向地面站传输数据的无线链路。本次数据发布包含RiOS采集的热红外影像，存储于机器人操作系统（ROS，Robot Operating System）格式的*.bag文件中。这些bag文件被打包为两个独立的压缩归档包，分别对应两次数据采集日期。可使用开源数据可视化工具Foxglove Studio查看bag文件中的热红外影像（相关外部资源中提供了操作指引链接）。将热红外bag文件加载至Foxglove Studio后，在设置界面中将色彩模式调整为渐变，并将最小、最大取值分别设为12000与15000（详见附件中的Foxglove.jpg）。用户可根据需求调整该默认取值范围以增强图像对比度。上述热红外影像被作为输入送入图像测速算法，以估算沿河区域的表面流速。为评估该图像衍生流速估算结果的准确性，研究人员借助搭载RiverSurveyor Live软件套件的SonTek M9型声学多普勒流速剖面仪（ADCP，Acoustic Doppler Current Profiler）开展了实地流速测量。ADCP测量沿多条预先规划的、与主下游流向垂直的横断面航线开展。在每个断面上完成多次ADCP走航测量后，使用流速映射工具箱（VMT，Velocity Mapping Toolbox）对数据进行处理，以生成平均横断面流速数据（Parsons等人，2013）。VMT的输出结果为单个逗号分隔文本文件，包含以下7列表头：1）xs：河流断面测站位置，单位为米；2）x_meters：东向（x）空间坐标，单位为米；3）y_meters：北向（y）空间坐标，单位为米；4）depth_meters：水深，单位为米；5）vmag_meters_per_second：垂线平均流速幅值，单位为米每秒；6）u_meters_per_second：垂线平均流速矢量的东向（u）分量，单位为米每秒；7）v_meters_per_second：垂线平均流速矢量的北向（v）分量，单位为米每秒。空间坐标采用通用横轴墨卡托（UTM，Universal Transverse Mercator）10区、世界大地测量系统1984（WGS-84，World Geodetic System 1984）基准面进行投影。