Fine scale optical remote sensing experiment of mixed stand over complex terrain(FOREST)in the Genhe Reserve Area:objective,observation and a case study

Optical remote sensing allows to efficiently monitor forest ecosystems at regional and global scales.However,most of the widely used optical forward models and backward estimation methods are only suitable for forest canopies in flat areas.To evaluate the recent progress in forest remote sensing over complex terrain,a satellite-airborne-ground synchronous Fine scale Optical Remote sensing Experiment of mixed Stand over complex Terrain(FOREST)was conducted over a 1 km×1 km key experiment area(KEA)located in the Genhe Reserve Areain 2016.Twenty 30 m×30 m elementary sampling units(ESUs)were established to represent the spatiotemporal variations of the KEA.Structural and spectral parameters were simultaneously measured for each ESU.As a case study,we first built two 3D scenes of the KEA with individual-tree and voxel-based approaches,and then simulated the canopy reflectance using the LargE-Scale remote sensing data and image Simulation framework over heterogeneous 3D scenes(LESS).The correlation coefficient between the LESS-simulated reflectance and the airborne-measured reflectance reaches 0.68-0.73 in the red band and 0.56-0.59 in the near-infrared band,indicating a good quality of the experiment dataset.More validation studies of the related forward models and retrieval methods will be done.

Clear-sky land surface upward longwave radiation dataset derived from the ABI onboard the GOES-16 satellite

Surface upward longwave radiation(SULR)is one of the four components of the surface radiation budget,which is defined as the total surface upward radiative flux in the spectral domain of 4-100μm.The SULR is an indicator of surface thermal conditions and greatly impacts weather,climate,and phenology.Big Earth data derived from satellite remote sensing have been an important tool for studying earth science.The Advanced Baseline Imager(ABI)onboard the Geostationary Operational Environmental Satellite(GOES-16)has greatly improved temporal and spectral resolution compared to the imager sensor of the previous GOES series and is a good data source for the generation of high spatiotemporal resolution SULR.In this study,based on the hybrid SULR estimation method and an upper hemisphere correction method for the SULR dataset,we developed a regional clear-sky land SULR dataset for GOES-16 with a half-hourly resolution for the period from 1st January 2018 to 30th June 2020.The dataset was validated against surface measurements collected at 65 Ameriflux radiation network sites.Compared with the SULR dataset of the Global LAnd Surface Satellite(GLASS)longwave radiation product that is generated from the Moderate Resolution Imaging Spectroradiometer(MODIS)onboard the polar-orbiting Terra and Aqua satellites,the ABI/GOES-16 SULR dataset has commensurate accuracy(an RMSE of 15.9 W/m2 vs 19.02 W/m2 and an MBE of−4.4 W/m2 vs−2.57 W/m2),coarser spatial resolution(2 km at nadir vs 1 km resolution),less spatial coverage(most of the Americas vs global),fewer weather conditions(clear-sky vs all-weather conditions)and a greatly improved temporal resolution(48 vs 4 observations a day).The published data are available at http://www.dx.doi.org/10.11922/sciencedb.j00076.00062.