Sagehen Creek UAS thermal sensing

Uncooled thermal infrared (TIR) imagers, commonly used on aircraft and small unmanned aircraft systems (UAS, “drones”), can provide high‐resolution surface temperature maps, but their accuracy is dependent on reliable calibration sources. A novel method for correcting surface temperature observations made by uncooled TIR imagers uses observations over melting snow, which provides a constant 0 °C reference temperature. This bias correction method is applied to remotely sensed surface
temperature observations of forests and snow over two mountain study sites: Laret, Davos, Switzerland (27 March 2017) in the Alps, and Sagehen Creek, California, USA (21 April 2017) in the Sierra Nevada. Surface temperature retrieval errors that arise from temperature‐induced instrument bias, differences in image resolution, retrieval of mixed pixels, and variable view angles were evaluated for these forest snow scenes. Applying the melting snow‐based bias correction decreased the root‐mean‐square error by about 1 °C for retrieving snow, water, and forest canopy temperatures from airborne TIR observations. The influence of mixed pixels on surface temperature retrievals over forest snow scenes was found to depend on
image resolution and the spatial distribution of forest stands. Airborne observations over the forests at Sagehen showed that near the edges of TIR images, at more than 20° from nadir, the snow surface within forest gaps smaller than 10 m was obscured by the surrounding trees. These off‐nadir views, with fewer mixed pixels, could allow more accurate airborne and satellite‐based observations of canopy surface temperatures.

RAW and processed data can be found here: https://nevada.app.box.com/folder/172808842498

非冷却型热红外成像仪（TIR），广泛用于飞机及小型无人机系统（UAS，俗称‘无人机’），能够提供高分辨率地表温度图，但其准确性依赖于可靠的校准源。一种新型的校正非冷却型热红外成像仪所测地表温度观测值的方法，通过熔化雪的观测实现，提供了恒定的0°C参考温度。此偏差校正方法应用于两个山地区域的遥感地表温度观测，分别为瑞士阿尔卑斯山脉的Laret、Davos（2017年3月27日）和加利福尼亚州Sagehen Creek（2017年4月21日）的Sierra Nevada山脉。对这些森林雪地场景，评估了由温度引起的仪器偏差、图像分辨率差异、混合像素的提取以及可变视角等因素引起的地表温度提取误差。应用基于熔化雪的偏差校正，在从空中TIR观测中提取雪、水和森林冠层温度时，将均方根误差降低了约1°C。研究发现，混合像素对森林雪地场景地表温度提取的影响取决于图像分辨率和森林立地的空间分布。在Sagehen的森林空中观测表明，在TIR图像的边缘，距离正下方的角度超过20°的地方，小于10米宽的森林间隙内的雪表面被周围树木所遮挡。这些非正下方的视角，由于混合像素较少，可能允许更精确的空中和基于卫星的地表温度观测。

原始和经过处理的数据可在此处找到：https://nevada.app.box.com/folder/172808842498