Influence of voxel size on forest canopy height estimates using full-waveform airborne LiDAR data

Background: Forest canopy height is a key forest structure parameter. Precisely estimating forest canopy height is vital to improve forest management and ecological modelling. Compared with discrete-return LiDAR(Light Detection and Ranging), small-footprint full-waveform airborne LiDAR(FWL) techniques have the capability to acquire precise forest structural information. This research mainly focused on the influence of voxel size on forest canopy height estimates.Methods: A range of voxel sizes(from 10.0 m to 40.0 m interval of 2 m) were tested to obtain estimation accuracies of forest canopy height with different voxel sizes. In this study, all the waveforms within a voxel size were aggregated into a voxel-based LiDAR waveform, and a range of waveform metrics were calculated using the voxelbased LiDAR waveforms. Then, we established estimation model of forest canopy height using the voxel-based waveform metrics through Random Forest(RF) regression method.Results and conclusions: The results showed the voxel-based method could reliably estimate forest canopy height using FWL data. In addition, the voxel sizes had an important influence on the estimation accuracies(R2 ranged from 0.625 to 0.832) of forest canopy height. However, the R2 values did not monotonically increase or decrease with the increase of voxel size in this study. The best estimation accuracy produced when the voxel size was 18 m(R2= 0.832, RMSE = 2.57 m, RMSE% = 20.6%). Compared with the lowest estimation accuracy, the R2 value had a significant improvement(33.1%) when using the optimal voxel size. Finally, through the optimal voxel size, we produced the forest canopy height distribution map for this study area using RF regression model. Our findings demonstrate that the optimal voxel size need to be determined for improving estimation accuracy of forest parameter using small-footprint FWL data.

A new denoising method for photon-counting LiDAR data with different surface types and observation conditions

Spaceborne photon-counting LiDAR is significantly affected by noise,and existing denoising algorithms cannot be universally adapted to different surface types and topographies under all observation conditions.Accordingly,a new denoising method is presented to extract signal photons adaptively.The method includes two steps.First,the local neighborhood radius is calculated according to photons’density,then thefirst-step denoising process is completed via photons’curvature feature based on KNN search and covariance matrix.Second,the local photonfiltering direction and threshold are obtained based on thefirst-step denoising results by RANSAC and elevation frequency histogram,and the local dense noise photons that thefirst-step cannot be identified are further eliminated.The following results are drawn:(1)experimental results on MATLAS with different topographies indicate that the average accuracy of second-step denoising exceeds 0.94,and the accuracy is effectively improves with the number of denoising times;(2)experiments on ICESat-2 under different observation conditions demonstrate that the algorithm can accurately identify signal photons in different surface types and topographies.Overall,the proposed algorithm has good adaptability and robustness for adaptive denoising of large-scale photons,and the denoising results can provide more reasonable and reliable data for sustainable urban development.

Segmentation of the communication tower and its accessory equipment based on geometrical shape context from 3D point cloud

Communication tower(CT)and its accessory equipment(AE)such as radio frequency equipment(RFE)and antenna,are essential in providing highspeed and stable mobile network services.It is necessary to routinely monitor the security and stability of CT and AE for seamless communication.There is limited research on fine segmentation of communication base station objects.This paper proposes a method for accurately segmenting the point cloud of the CT and AE from Terrestrial Laser Scanning(TLS)data.At first,the CT point cloud is accurately segmented based on region growing and Random Sample Consensus(RANSAC).Then,the point cloud of pole-shaped apart is extended to a certain distance to obtain the buffer point cloud containing AE.Normal Differential(ND)clustering is employed to obtain several groups of clusters containing planes,and calculate each plane's filling rate and size.Finally,the cluster type(such as antenna,RFE,or other)is distinguished.The experimental results demonstrate that the point-based average F1-score of CTs is 98.70%,the point-based and object-based average F1-scores of antennas are 96.09%and 97.93%,and the corresponding values for the RFE are 89.89%and 90.00%,respectively,indicating the optimal performance of the proposed method.

UAV Laser scanning technology:a potential cost-effective tool for micro-topography detection over wooded areas for archaeological prospection

Airborne laser scanning(ALS)has recently been identified as a potential tool in topographic mapping for archaeological prospection.However,most existing applications in this field refers to manned ALS systems,for which the high operation and maintenance costs limits its application in small-scale archaeological investigation.In this paper,we conducted an exploratory study on the application of the unmanned aerial vehicle(UAV)laser scanning(ULS)system in ancient micro-topography detection over wooded areas.Compared with manned ALS technology,we analyzed the advantages and potentials of ULS technology for archaeological applications.Then we outlined existing mainstream survey-grade UAV-based laser scanners,data processing and visualization approaches.Furthermore,we performed case studies in three cultural heritage sites in Zhejiang Province,China using two representative mainstream survey-grade ULS systems.Results were then verified by an in-site investigation.Finally,the correct selection of ULS devices,the planning of data acquisition missions and the use of appropriate data processing methods specifically for archaeological prospection were discussed.This paper provides a cost-effective and flexible solution for micro-topography detection in wooded areas.ULS technology,as demonstrated here,can be an important supplement to existing archaeological investigation methods,particularly for small-scale areas,and has promising prospects in archaeological applications.

Nanoparticles targeting at methylases with high correlation to N^(6)-methyladenosine-related lncRNA signatures as potential therapy of kidney clear cell carcinoma

Clear cell renal cell carcinoma(ccRCC)is a heterogeneous malignancy with poor prognosis.Methylation of the N^(6) position of adenosine(m^(6)A),the most common epigenetic modification in both messenger RNAs and noncoding RNAs,has been reported to regulate the initiation and progression of ccRCC.However,whether and how m^(6)A-related long noncoding RNAs(m^(6)ArlncRNAs)signify the progression of ccRCC remain unclear.We found m^(6)ArlncRNAs are effective signatures illustrating immune landscape and risk stratification in ccRCC.We identified two differently expressed m^(6)ArlncRNAs(DEm^(6)ArlncRNAs),AC008870.2 and EMX2OS,as independent risk factors for overall survival of ccRCC patients,by applying stringent variable selection procedure to data from the Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma project.The risk score generated from the DEm^(6)ArlncRNA expression categorizes patients into either high or low-risk groups,between which,enrichment analysis indicated an enrichment in immune-related pathways.Under different DEm^(6)ArlncRNA transcription pattern,the two risk groups differ in immune cell population composition and expression levels of therapy targeting genes.Nanoparticle is satisfactory strategy to delivering therapeutic drugs.For further clinical translation,we designed a novel nanoparticle delivery system packaged STM2457(STM@8P4 NPs),which selectively inhibits AC008870.2-correlated m^(6)A writer.STM@8P4 NPs loaded drug successfully with uniform particle size,long-term stability and high release efficiency.STM@8P4 NPs can easily enter ccRCC cells and showed a highly efficient ccRCC killing activity in vitro.Our results therefore indicate that m^(6)ArlncRNAs expression can depict tumor microenvironment,predict prognosis for ccRCC patient and give hint to therapeutic strategies in ccRCC.

Dynamics of neutralizing antibody responses to SARS-CoV-2 in patients with COVID-19: an observational study

Our understanding of the protective immunity,particularly the long-term dynamics of neutralizing antibody(NAbs)response to SARS-CoV-2,is currently limited.We enrolled a cohort of 545 COVID-19 patients from Hubei,China,who were followed up up to 7 months,and determined the dynamics of NAbs to SARS-CoV-2 by using a surrogate virus neutralization test(sVNT).In our validation study,sVNT IC50 titers and the neutralization rate measured at a single dilution(1:20)were well correlated with FRNT titers(r=0.85 and 0.84,respectively).The median time to seroconversion of NAbs was 5.5 days post onset of symptoms.The rate of positive sVNT was 52% in the first week,reached 100% in the third week,and remained above 97% till 6 months post onset.Quantitatively,NAbs peaked in the fourth week and only a quarter of patients had an estimated peak titer of>1000.NAbs declined with a half-time of 61 days(95%CI:49-80 days)within the first two months,and the decay deaccelerated to a half-time of 104 days(95%CI:86-130 days)afterward.The peak levels of NAbs were positively associated with severity of COVID-19 and age,while negatively associated with serum albumin levels.The observation that the low-moderate peak neutralizing activity and fast decay of NAbs in most naturally infected individuals called for caution in evaluating the feasibility of antibody-based therapy and vaccine durability.NAbs response positively correlated with disease severity,warning for the possibility of repeat infection in patients with mild COVID-19.

Personnel protection strategy for healthcare workers in Wuhan during the COVID-19 epidemic

Objective:To identify the effectiveness of a personnel protection strategy in protection of healthcare workers from SARS-CoV-2 infection.Design:During the COVID-19 pandemic,943 healthcare staff sent from Guangzhou to Wuhan to care for patients with suspected/confirmed COVID-19 received infection precaution training before their mission and were equipped with Level 2/3 personal protective equipment(PPE),in accordance with guidelines from the National Health Commission of China.We conducted a serological survey on the cumulative attack rate of SARS-CoV-2 among the healthcare workers sent to Wuhan and compared the seropositive rate to that in local healthcare workers from Wuhan and Jingzhou.Results:Serial tests for SARS-CoV-2 RNA and tests for SARS-CoV-2 immunoglobulin M and G after the 6-8 week mission revealed a zero cumulative attack rate.Among the local healthcare workers inWuhan and Jingzhou of Hubei Province,2.5%(113 out of 4495)and 0.32%(10 out of 3091)had RT-PCR confirmed COVID-19,respectively.The seropositivity for SARS-CoV-2 antibodies(IgG,IgM,or both IgG/IgM positive)was 3.4%(53 out of 1571)in local healthcare workers from Wuhan with Level 2/3 PPE working in isolation areas and 5.4%(126 out of 2336)in healthcare staff with Level 1 PPE working in non-isolation medical areas,respectively.Conclusions and relevance:Our study confirmed that adequate training/PPE can protect medical personnel against SARS-CoV-2.

Single-cell transcriptomics reveals the ameliorative effect of rosmarinic acid on diabetic nephropathy-induced kidney injury by modulating oxidative stress and inflammation

Diabetic nephropathy(DN)is a severe complication of diabetes,characterized by changes in kidney structure and function.The natural product rosmarinic acid(RA)has demonstrated therapeutic effects,including anti-inflammation and anti-oxidative-stress,in renal damage or dysfunction.In this study,we characterized the heterogeneity of the cellular response in kidneys to DN-induced injury and RA treatment at single cell levels.Our results demonstrated that RA significantly alleviated renal tubular epithelial injury,particularly in the proximal tubular S1 segment and on glomerular epithelial cells known as podocytes,while attenuating the inflammatory response of macrophages,oxidative stress,and cytotox-icity of natural killer cells.These findings provide a comprehensive understanding of the mechanisms by which RA alleviates kidney damage,oxidative stress,and inflammation,offering valuable guidance for the clinical application of RA in the treatment of DN.