This paper introduces the “Saihanba comprehensive airborne remote sensing experiment of forest resources” (The carbon cycle airborne experiment), which is part of “The comprehensive experiment of carbon cycle, water cycle and energy balance”. This paper described the purpose, design scheme, flight mission execution, data processing and products of airborne remote sensing experiment of forest resources, respectively. The experiment focused on Saihanba Forest Farm, launched out with the monitoring of forest resources and energy balance of carbon-water cycle. 10 flights were flown from August 31 to September 20, 2018 using the Chinese Academy of Forestry’s LiDAR,CCD and Hyperspectral airborne observation system (CAF-LiCHy). The raw data volume was about 1568 GB. High-level remote sensing products were produced after further data processing. The POS position has a difference within 2 cm in both horizontal and vertical directions. The LiDAR point density is larger than 4 pts/m².
The horizontal and vertical differences of LiDAR point cloud data are within 0.2 m. The spatial resolution of digital elevation model product is 2 m. The spectral resolution of hyperspectral image is better than 10 nm with the spatial resolution of 1 m. The spatial resolution of CCD image is 0.2 m. The overall geolocation accuracy is about 1 m among these three type sensors. This study provided high-quality datasets for carbon-water cycle and forest resources monitoring, reflected the advantages of active and passive integrated observation system in collecting forest resources simultaneously.