Discovering forest height changes based on spaceborne lidar data of ICESat-1 in 2005 and ICESat-2 in 2019:a case study in the Beijing-Tianjin-Hebei region of China

Background:The assessment of change in forest ecosystems,especially the change of canopy heights,is essential for improving global carbon estimates and understanding effects of climate change.Spaceborne lidar systems provide a unique opportunity to monitor changes in the vertical structure of forests.NASA’s Ice,Cloud and Land Elevation Satellites,ICESat-1 for the period 2003 to 2009,and ICESat-2(available since 2018),have collected elevation data over the Earth’s surface with a time interval of 10 years.In this study,we tried to discover forest canopy changes by utilizing the global forest canopy height map of 2005(complete global coverage with 1 km resolution)derived from ICESat-1 data and the ATL08 land and vegetation products of 2019(sampling footprints with 17 m diameter)from ICESat-2.Results:Our study revealed a significant increase in forest canopy heights of China’s Beijing-Tianjin-Hebei region.Evaluations of unchanging areas for data consistency of two products show that the bias values decreased significantly from line-transect-level(−8.0 to 6.2 m)to site-level(^(−1).5 to 1.1 m),while RMSE values are still relatively high(6.1 to 15.2 m,10.2 to 12.0 m).Additionally,58%of ATL08 data are located in‘0m’pixels with an average height of 7.9 m,which are likely to reflect the ambitious tree planting programs in China.Conclusions:Our study shows that it is possible,with proper calibrations,to use ICESat-1 and-2 products to detect forest canopy height changes in a regional context.We expect that the approach presented in this study is potentially suitable to derive a fine-scale map of global forest change.

A 3D approach to reconstruct continuous optical images using lidar and MODIS

Background: Monitoring forest health and biomass for changes over time in the global environment requires the provision of continuous satellite images. However, optical images of land surfaces are generally contaminated when clouds are present or rain occurs.Methods: To estimate the actual reflectance of land surfaces masked by clouds and potential rain, 3D simulations by the RAPID radiative transfer model were proposed and conducted on a forest farm dominated by birch and larch in Genhe City, Da Xing’An Ling Mountain in Inner Mongolia, China. The canopy height model(CHM) from lidar data were used to extract individual tree structures(location, height, crown width). Field measurements related tree height to diameter of breast height(DBH), lowest branch height and leaf area index(LAI). Series of Landsat images were used to classify tree species and land cover. MODIS LAI products were used to estimate the LAI of individual trees. Combining all these input variables to drive RAPID, high-resolution optical remote sensing images were simulated and validated with available satellite images.Results: Evaluations on spatial texture, spectral values and directional reflectance were conducted to show comparable results.Conclusions: The study provides a proof-of-concept approach to link lidar and MODIS data in the parameterization of RAPID models for high temporal and spatial resolutions of image reconstruction in forest dominated areas.

Identification of African swine fever virus MGF505-2R as a potent inhibitor of innate immunity in vitro

African swine fever(ASF)is etiologically an acute,highly contagious and hemorrhagic disease caused by African swine fever virus(ASFV).Due to its genetic variation and phenotypic diversity,until now,no efficient commercial vaccines or therapeutic options are available.The ASFV genome contains a conserved middle region and two flexible ends that code for five multigene families(MGFs),while the biological functions of the MGFs are not fully characterized.Here,ASFV MGF505-2R-deficient mutant ASFV-Δ2R was constructed based on a highly virulent genotype II field isolate ASFV CN/GS/2018 currently circulating in China.Transcriptomic profiling demonstrated that ASFV-Δ2R was capable of inducing a larger number of differentially expressed genes(DEGs)compared with ASFV CN/GS/2018.Hierarchical clustering of up-regulated DEGs revealed that ASFV-Δ2R induced the most dramatic expression of interferon-related genes and inflammatory and innate immune genes,as further validated by RT-qPCR.The GO and KEGG pathway analysis identified significantly enriched pathways involved in pathogen recognition and innate antiviral immunity.Conversely,pharmacological activation of those antiviral immune responses by exogenous cytokines,including type I/II IFNs,TNF-αand IL-1β,exerted combinatory effects and synergized in antiviral capacity against ASFV replication.Collectively,MGF505-2R is a newly identified inhibitor of innate immunity potentially implicated in immune evasion.

Enhanced Branch Simulation to Improve RAPID in Optical Region Using RAMI Scenes

To improve the simulation accuracy of vegetation canopy reflectance in optical bands,the Radiosity Applicable to Porous IndiviDual objects(RAPID)model has been upgraded to better deal with branches in the latest RAPID4.Previous versions of RAPID(RAPID1 and RAPID3)neglected branches in porous objects in optical bands,while RAPID2 emphasized them in microwave bands.This inconsistency needed to be addressed to establish a unified radiosity-based simulation framework.By incorporating branches in RAPID4,we have improved several aspects of the model,including the random dynamic projection process,the equivalent reflectance or transmittance,the single scattering estimation,the multiple scattering solution,and the bidirectional reflectance factor(BRF)calculation.Three-dimensional trees from the fifth RAdiation transfer Model Intercomparison(RAMI-V)have been used to test the contribution of branches on BRF.Comparisons with a ray-tracing-based LESS model(the LargE-Scale remote sensing data and image Simulation framework)on RAMI-V scenes show a general agreement on BRF(R^(2)≥0.96 and root mean square error ranging from 0.014 to 0.054).The major biases occur in a realistic scene(i.e.,HET51_WWO_TLS)created from terrestrial laser scanning data.Sensitivity analysis has been conducted to show the branch contribution on BRF in optical domain.Without considering dense branches,the BRF error can exceed 0.1.

Fast and Accurate Simulation of Canopy Reflectance under Wavelength-Dependent Optical Properties Using a Semi-Empirical 3D Radiative Transfer Model

Generating canopy-reflectance datasets using radiative transfer models under various leaf and optical property combinations is important for remote sensing retrieval of vegetation parameters.Onedimensional radiative transfer models have been frequently used.However,three-dimensional(3D)models usually require detailed 3D information that is difficult to obtain and long model execution time,limiting their use in remote sensing applications.This study aims to address these limitations for practical use of 3D models,proposing a semi-empirical speed-up method for canopy-reflectance simulation based on a LargE-Scale remote sensing data and image Simulation model(LESS),called Semi-LESS.The speed-up method is coupled with 3D LESS to describe the dependency of canopy reflectance on the wavelength,leaf,soil,and branch optical properties for a scene with fixed 3D structures and observation/illumination configurations,allowing fast generating accurate reflectance images under various wavelength-dependent optical parameters.The precomputed dataset stores simulated multispectral coefficient images under few predefined soil,branch,and leaf optical properties for each RAdiation transfer Model Intercomparison-V scene,which can then be used alone to compute reflectance images on the fly without the participation of LESS.Semi-LESS has been validated with full 3D radiative-transfer-simulated images,showing very high accuracy(root mean square error<0.0003).The generation of images using Semi-LESS is much more efficient than full LESS simulations with an acceleration of more than 320 times.This study is a step further to promote 3D radiative transfer models in practical remote sensing applications such as vegetation parameter inversions.

A commentary of “Using satellites to map trees”: 10 remarkable discoveries from 2020 in Nature

Brandt et al.reported the results of their analysis from high-resolution satellite images,covering more than 1.3 million square kilometers of the Western Sahara and Sahel in West Africa.They mapped the locations and sizes of approximately 1.8 billion trees.Prior to this,scientists had never made such a detailed map of trees in such a large area.Commercial satellites have begun to collect data and can detect small ground objects that are 1 square meter or less in size.Therefore,the field of terrestrial remote sensing may have a significant advance from mainly a comprehensive landscape-scale measurement to mapping the position and canopy size of each tree at a regional or even global scale.This progress will revolutionize how we think,monitor,simulate,and manage the global terrestrial ecosystem.

Fine-Scale Quantification of Absorbed Photosynthetically Active Radiation(APAR)in Plantation Forests with 3D Radiative Transfer Modeling and LiDAR Data

Quantifying the relationship between light and stands or individual trees is of great significance in understanding tree competition,improving forest productivity,and comprehending ecological processes.However,accurately depicting the spatiotemporal variability of light under complex forest structural conditions poses a challenge,especially for precise forest management decisions that require a quantitative study of the relationship between fine-scale individual tree structure and light.3D RTMs(3-dimensional radiative transfer models),which accurately characterize the interaction between solar radiation and detailed forest scenes,provide a reliable means for depicting such relationships.