Abundance and Community Structure of Airborne Microorganisms over the Ocean and Their Influencing Mechanisms

Airborne microorganisms play an essential role in the microbial propagation and maintenance of the ecosystem diversity, and also significantly affect the climate by acting as effective Ice Nucleus (IN) and Cloud Condensation Nuclei (CCN). The ocean is a vital source and destination for airborne microbes. Nevertheless, little information has been obtained on the distribution of abundance and diversity of airborne microorganisms over the ocean. This paper systematically reviewed the abundance, size distribution, and community structure of airborne microorganisms over the ocean, as well as various environmental and meteorological factors that control the distribution of microbes in marine aerosols. The commonly used methods for detecting airborne microorganisms and their development prospects were also discussed. We pointed out that sampling and detection of extremely low concentration microorganisms in marine aerosols are key problems to be solved in this field, and future research directions include the increase of the cruising observation in open oceans and combination of advanced molecular techniques and other traditional methods. This paper provides extensive and crucial information for subsequently in-depth research on airborne microorganisms over the ocean, revealing their sources, activities, climate and ecological effects.     

机载激光雷达系统的应用与数据后处理技术

综述了机载激光雷达系统的组成、工作原理、应用和数据后处理技术,着重介绍机载激光雷达数据中的信息提取的有关算法,这些算法包括DEM、DTM提取、房屋提取与房屋几何模型的3D重建、道路网提取、森林参数的获取等。     

机载微波辐射计云中含水量的探测

通过对2003年4月18日在延安地区用单波长(0.95 cm)机载微波辐射计探测到的层状云云中液态水含量的分析,结果表明,层状云中的过冷水平均含量为0.0171 g.m-3。分析其变化,发现云中垂直向的液态水存在高值区,这一区有助于人工引晶催化增雨(雪)作业,有利于冰晶的增长,可提高人工催化作业的效果。与机载粒子测量系统(PMS)及地面711数字化雷达的探测结果进行比对,机载微波辐射计和PMS粒子测量系统的探测结果有较好的一致性;并且在垂直区域的探测上比PMS粒子测量系统更具有代表性;与711数字化雷达的探测结果也吻合。     

On the way to airborne gravelometry based on 3D spatial data derived from images

This paper presents basic tests to develop an airborne photogrammetric methodology that derives grain size characteristics of gravel bed rivers. The data acquisition was done using a lightweight action cam and a hand-held digital single lens reflex camera. Image processing comprised the structure from motion technique and multiview-stereo algorithms to obtain digital elevation models of non-cohesive gravel beds. Laboratory results indicate that the method accuracy is about four to six times lower than laser-scan data when based on action cam data. The accuracy of digital elevation models computed via photos taken by the reflex camera is almost of the same range as the laser data. Field experiments were done to test the performance of image based gravelometry against manual surface sampling. For this application the action cam was mounted to a low-cost quadrocopter, while the reflex camera was operated by hand. Results indicate that this combination has a high potential to generate data from which characteristic grain size parameters can be estimated.     

三维时间域航空电磁有理Krylov正演研究

常规的三维时间域航空电磁模拟通常采用隐式步长方法进行时间离散,需要几次矩阵分解和上百次右端源项回带,计算效率较低.为了提高正演计算效率,本文提出使用有理Krylov方法求解时间域电场扩散方程.首先使用非结构四面体网格进行空间离散,采用Nédélec矢量基函数近似四面体单元内的电场;然后基于有限元离散给出矩阵指数和矢量乘积表示的电场显式解;最后采用有理Arnoldi算法构造Krylov子空间内的正交基函数并进一步求解矩阵指数与矢量的乘积,直接得到任意时刻的电场解向量,避免步长离散过程.此外,本文还提出一种指数加权偏移参数优化方法,使得有理Arnoldi近似在瞬变衰减晚期具备更高的精度,从而降低Krylov子空间阶数并提高计算效率.通过和层状模型解析解的对比验证了有理Krylov方法的精度.针对三维异常体模型使用全局网格和局部网格剖分并和其他数值方法比较,进一步说明了有理Krylov方法的有效性.     

Feature selection for airborne LiDAR data filtering: a mutual information method with Parzon window optimization

ABSTRACT

Filtering is one of the key steps for Digital Elevation Model (DEM) generation from airborne Light Detection and Ranging (LiDAR) data. Machine-learning-based filters have emerged as a class of filtering algorithms in recent years. Most existing studies mainly focus on feature generation due to limited available features a point cloud possesses. More than 30 features have been described in the existing literature. But most generated features are based on geometric information of points. Several redundant and irrelevant features may not necessarily improve the filtering accuracy. Hence, this paper proposes a feature-selection method using minimal-Redundancy-Maximal-Relevance (mRMR) combined with Parzen window optimization to deal with both discrete and continuous features. An optimal/suboptimal feature subset is constructed for machine-learning filters in various landscapes. Experimental results based on AdaBoost show that height-related features, particularly height itself, are of the greatest significance in both urban and rural scenes. Moreover, different subsets can be selected from the datasets of the two landscapes by our feature-selection strategy, which increases the data relevance for describing each geographical landscape. This study provides guidelines for the selection of optimal/suboptimal features for point cloud filtering based on machine-learning algorithms.     

A method for vertical adjustment of digital aerial photogrammetry data by using a high-quality digital terrain model

The accuracy of vertical position information can be degraded by various sources of error in digital aerial photogrammetry (DAP) based point clouds. To address this issue, we propose a relatively straightforward method for automated correction of such point clouds. This method can be used in conjunction with any 3D reconstruction method in which a point cloud is generated from a pair of aerial images. The crux of the method involves separately co-registering each DAP point cloud (formed by the overlap of two or more images) to a common airborne laser scanning (ALS) based digital terrain model. The proposed method has the following essential steps: (1) Ground surface patches are identified in the normalized DAP point clouds by selecting areas in which standard deviation of vertical height is low, (2) height differences between the DAP and ALS point clouds are calculated at these patches, and (3) a correction surface is interpolated from these height differences and is then used to rectify the entire DAP point cloud. The performance of the proposed method is verified using plot data (n = 250) from a forested study area in Eastern Finland. We observed that DAP data from the area corrected using our proposed method resulted in significant increases in prediction accuracy of key forest variables. Specifically, the root mean squared error (RMSE) values for dominant height predictions decreased by up to 23.2%, while the associated model R² values increased by 16.9%. As for stem volume, RMSEs dropped by 20.6%, while the model R² improved by 14.6%, respectively. Hence, prediction accuracies were almost as good as with ALS data. The results suggest that vertically misaligned DAP data, if rectified using an algorithm such as the one presented here, could deliver near ALS data quality at a fraction of the cost.     

Mapping individual trees with airborne laser scanning data in an European lowland forest using a self-calibration algorithm

Traditional field-based forest inventories tend to be expensive, time-consuming, and cover only a limited area of a forested region. Remote sensing (RS), especially airborne laser scanning (ALS) has opened new possibilities for operational forest inventories, particularly at the single-tree level, and in the prediction of single-tree characteristics. Throughout the world, forests have varying characteristics that necessitate the development of modern, effective, and versatile tools for ALS data processing. To address this need, we aimed to develop a tool for individual tree detection (ITD) utilising a self-calibrating algorithm procedure and to verify its accuracy using the complicated forest structure of near natural forests in the temperate zone.This study was carried out in the Polish part of the Białowieża Forest (BF). The airborne laser scanner (ALS) and color-infrared (CIR) datasets were acquired for more than 60 000 ha. Field-based measurements were performed to provide reference data at the single tree level. We introduced a novel ITD method that is self-calibrated and uses a hierarchical analyses of the canopy height model.There were more than 20 000 000 of trees in first layer in BF above 7 m height. Trees visible from above were divided into coniferous, deciduous and mixed trees that were then matched with an accuracy of 85 %, 85 % and 75 %, respectively. Compared to existing methods, the proposed method is more flexible and achieves better results, especially for deciduous species. Before application of the presented method to other regions, the calibration based on the developed optimisation procedure is needed.     

Helicopter-Borne Flux Measurements in the Nocturnal Boundary Layer Over Land – a Case Study

This case study introduces measurements of turbulent fluxes in a nocturnal boundary layer in North Germany with the new helicopter-borne turbulence measurement system HELIPOD, a detailed data analysis and examination in regard of systematic errors of the instrument, and some comparison with local similarity theory and experiments of the past, in order to confirm the occurrence of small vertical turbulent fluxes. The examined nocturnal boundary layer offered excellent conditions to analyse the quality of the measurement system. In this connection, a detailed look at a strong ground-based inversion disclosed small turbulent fluxes with a spectral maximum at ten metres wavelength or less, embedded in intermittent turbulence. For verification of these fluxes, the measurements were compared with well established results from past experiments. Local similarity theory was applied to calculate dimensionless variances of the turbulent quantities, which were found in good agreement with other observations. Since shear and stratification varied significantly on the horizontal flight legs due to global intermittency, a method was developed to determine vertical gradients on a horizontal flight pattern, by use of small fluctuations of the measurement height. With these locally determined gradients, gradient transport theory became applicable and the turbulent diffusivities for heat and momentum, the Richardson number, and the flux Richardson number were estimated within isolated strong turbulent outbursts. Within these outbursts the flux Richardson number was found between 0.1 and 0.2. The functional relationship between the gradient Richardson number and the turbulent Prandtl number agreed well with observations in past experiments and large eddy simulation. The impact of the stratification on the vertical turbulent exchange, as already described for the surface layer using Monin–Obukhov similarity, was analogously observed in the very stably stratified bulk flow when local scaling was applied.     

利用空中平均重力异常确定区域大地水准面

提出了直接利用空中平均重力异常计算区域大地水准面的方法。模拟计算的结果表明, 该方法与传统的利用地面平均空间重力异常确定的大地水准面精度相当, 但其显著优点是勿需空中重力异常的向下解析延拓, 从而可以避免延拓误差对大地水准面精化的影响。