Application of ICTs in Airspace Management and Collaborative Decision-Making—Analyzing the Risk Avoidance in the Condition of Risky Weather as an Example

The application of ICTs makes structural change of the development and effective utilization of airspace. Next generation air transportation system (NextGen) includes new automation concepts with automated information to support the traffic control decision-making. As a result, in the field of academia and industry, air traffic controllers integrate information automatically while making decisions to change the previous manually integrated and decided pattern. The safety ability of airspace is reduced and airspace system is endangered under risky weather conditions of airspace. So there is an urgent demand for new information and communication technologies. The paper is an overview of the information constitution and support of NextGen and provides the study of the development of technique of airspace collaborative decision-makings to confirm the new features based on ICTs. It contains basic application-the input of data and output of the routes of airspace management and collaborative decision-making, and general application-the choose of probability nets of avoiding risky weather, and special application-the affection in the management of the air routes, which are made up of position and direction. The research shows the accurate schedule characteristics of airspace management and collaborative decision-making based on ICTs, which made the space accurate by time accurate. Second, the visualization of airspace management and collaborative decision-making based on ICTs made the maps of flight path under mobile data quickly generated. This could make the fully development and utilization of national airspace, ensure safety, and reduce air traffic controllers’ workload and the costs in delaying and operating in risky weather.     

Unsupervised regionalization of the United States into landscape pattern types

We present a pattern-based regionalization of the conterminous US – a partitioning of the country into a number of mutually exclusive and exhaustive regions that maximizes the intra-region stationarity of land cover patterns and inter-region disparity between those patterns. The result is a discretization of the land surface into a number of landscape pattern types (LPTs) – spatial units each containing a unique quasi-stationary pattern of land cover classes. To achieve this goal, we use a recently developed method which utilizes machine vision techniques. First, the entire National Land Cover Dataset (NLCD) is partitioned into a grid of square-size blocks of cells, called motifels. The size of a motifel defines the spatial scale of a local landscape. The land cover classes of cells within a motifel form a local landscape pattern which is mathematically represented by a histogram of co-occurrence features. Using the Jensen–Shannon divergence as a dissimilarity function between patterns we group the motifels into several LPTs. The grouping procedure consists of two phases. First, the grid of motifels is partitioned spatially using a region-growing segmentation algorithm. Then, the resulting segments of this grid, each represented by its medoid, are clustered using a hierarchical algorithm with Ward’s linkage. The broad-extent maps of progressively more generalized LPTs resulting from this procedure are shown and discussed. Our delineated LPTs agree well with the perceptual patterns seen in the NLCD map.     

High-reliability zircon separation for hunting the oldest material on Earth: An automatic zircon separator with image-processing/microtweezers-manipulating system and double-step dating

Despite the recent development in radiometric dating of numerous zircons by LA-ICPMS, mineral separation still remains a major obstacle, particularly in the search for the oldest material on Earth. To improve the efficiency in zircon separation by an order of magnitude, we have designed/developed a new machine-an automatic zircon separator(AZS). This is designed particularly for automatic pick-up of100 μm-sized zircon grains out of a heavy mineral fraction after conventional separation procedures. The AZS operates in three modes:(1) image processing to choose targeted individual zircon grains out of all heavy minerals spread on a tray,(2) automatic capturing of the individual zircon grains with microtweezers, and(3) placing them one-by-one in a coordinated alignment on a receiving tray. The automatic capturing was designed/created for continuous mineral selecting without human presence for many hours. This software also enables the registration of each separated zircon grain for dating, by recording digital photo-image, optical(color) indices, and coordinates on a receiving tray. We developed two new approaches for the dating; i.e.(1) direct dating of zircons selected by LA-ICPMS without conventional resin-mounting/polishing,(2) high speed U-Pb dating, combined with conventional sample preparation procedures using the new equipment with multiple-ion counting detectors(LA-MIC-ICPMS).With the first approach, Pb-Pb ages obtained from the surface of a mineral were crosschecked with the interior of the same grain after resin-mounting/polishing. With the second approach, the amount of time required for dating one zircon grain is ca. 20 s, and a sample throughput of 150 grains per hour can be achieved with sufficient precision(ca. 0.5%).We tested the practical efficiency of the AZS, by analyzing an Archean Jack Hills conglomerate in Western Australia with the known oldest(4.3 Ga) zircon on Earth. Preliminary results are positive; we were able to obtain more than 194 zircons that are over 4.0 Ga out of ca. 3800 checked grains, and 9 grains were over 4300 Ma with the oldest at 4371 ± 7 Ma. This separation system by AZS, combined with the new approaches, guarantees much higher yield in the hunt for old zircons.     

基于岩石图像深度学习的岩性自动识别与分类方法

岩石岩性的识别与分类对于地质分析极为重要,采用机器学习的方法建立识别模型进行自动分类是一条新的途径。基于Inception-v3深度卷积神经网络模型,建立了岩石图像集分析的深度学习迁移模型,运用迁移学习方法实现了岩石岩性的自动识别与分类。采用此方法对所采集的173张花岗岩图像、152张千枚岩图像和246张角砾岩图像进行了学习和识别分类研究,通过训练学习建立岩石图像深度学习迁移模型,并分别采用训练集和测试集中的岩石图像对模型进行了检验分析。对于训练集中的岩石图像,每组岩石分别用3张图像测试,三种岩石的岩性分类均正确,且分类概率值均达到90%以上,显示了模型良好的鲁棒性;对于测试集中的岩石图像,每组岩石分别采用9张图像进行识别分析,三种岩石的岩性分类均正确,并且千枚岩组图像分类概率均高于90%,但是花岗岩组2张图像和角砾岩组的1张图像分类概率值不足70%,概率值较其他岩石图像低,推测其原因是训练集中相同模式的岩石图像较少,导致模型的泛化能力减小。为了提高识别精确度,对准确率较低的岩石图像进行截取,分别取其中的3张图像加入训练集进行再训练,增加与测试图像具有相同模式的训练样本;在新的模型中,对3张图像进行二次检验,测试概率值均达到85%以上,说明在数据足够的状况下模型具有良好的学习能力。与传统的机器学习方法相比,所提出的岩石图像深度学习方法具有以下优点:第一,模型通过搜索图像像素点提取物体特征,不需要手动提取待分类物体特征;第二,对于图像像素大小,成像距离及光照要求低;第三,采用适当的训练集可获得较好的识别分类效果,并具有良好鲁棒性和泛化能力。     

A Study of the Extended-range Forecast for the Low Frequency Temperature and High Temperature Weather over the Lower Reaches of Yangtze River Valley in Summer

Based on the observational data, the variations of Intraseasonal Oscillation (ISO) of the daily temperatures and its relationships to the high temperature in summer over the lower reaches of the Yangtze River Valley (LYRV) were studied for the period of 1979-2011. It is found that the daily temperatures over LYRV in May-August was mainly of periodic oscillations of 1525, 3060 and 6070 days, and the interannual variation of the intensity of its 3060-day oscillation had a strongly positive correlation with the number of days with daily highest temperature over 35 ℃ in July-August. Low frequency components of daily temperature in the LYRV, and the principal components of the Eastern Asian 850 hPa low frequency temperature, over a time period ranging from 1979 to 2000, were used to establish the Extended Complex Autoregressive model (ECAR) on an extended-range forecast of the 3060-day low frequency temperature over the LYRV. A 11-year independent real-time extended-range forecast was conducted on the extended-range forecast of low frequency component of the temperature over the LYRV in May-August, for the period ranging from 2001 to 2011. These experimental results show that this ECAR model, which is based on a data-driven model, has a good forecast skill at the lead time of approximately 23 days, with a forecast ability superior to the traditional autoregressive (AR) model. Hence, the development and variation of the leading 3060-day modes for the Eastern Asian 850 hPa low frequency temperatures and temporal evolutions of their relationships to low frequency components of the temperature over the LYRV in summer are very helpful in predicting the persistent high temperature over the LYRV at a 20 to 25 days lead.     

微波辐射计在对流天气预报中的应用

选取2016—2018年每年4—9月份RPG-HATPRO型42通道微波辐射计观测的不稳定指数参数(K、SI、CAPE、LI)及水汽参数(IWV、LWP),研究得出各参数触发雷雨大风、短时强降水的阈值条件为K>37℃、SI<-1℃、IWV>60 kg/m~2、LWP>400 g/m~2,而LI、CAPE无法对3种天气类型进行区分。利用费舍判别分析方法,将不稳定指数参数及水汽参数作为预报因子,建立预报方程并进行检验,结果表明:二级判别方程预测对流天气的准确率为76%,可以作为预报对流天气的辅助工具;多级判别方程不能很好地区分3种天气类型,但将其作为修正后的二级判别方程使用,能提高对流天气的测中概率。     

Novel fusion approach on automatic object extraction from spatial data: case study Worldview-2 and TOPO5000

The automatic extraction of information content from remotely sensed data is always challenging. We suggest a novel fusion approach to improve the extraction of this information from mono-satellite images. A Worldview-2 (WV-2) pan-sharpened image and a 1/5000-scaled topographic vector map (TOPO5000) were used as the sample data. Firstly, the buildings and roads were manually extracted from WV-2 to point out the maximum extractable information content. Subsequently, object-based automatic extractions were performed. After achieving two-dimensional results, a normalized digital surface model (nDSM) was generated from the underlying digital aerial photos of TOPO5000, and the automatic extraction was repeated by fusion with the nDSM to include individual object heights as an additional band for classification. The contribution was tested by precision, completeness and overall quality. Novel fusion technique increased the success of automatic extraction by 7% for the number of buildings and by 23% for the length of roads.     

区域自动气象站蓄电池异常状态判别方法

针对天津市一种常见的CAWS600型区域自动气象站对其供电及功耗进行了详细分析,利用对电池放电特性曲线的归一化处理,得到了针对12V38AH铅酸蓄电池的剩余容量估算方法,同时利用该站蓄电池工作电压的统计规律,提出了针对蓄电池工作电压的极值判定、时间/空间一致性质量控制方法,并对2017年逐10min观测数据进行检验。检验结果显示,文章提出的质量控制方法可以有效识别出蓄电池异常站点,针对2017年个站蓄电池持续放电情况可提前10d定位。     

安全射界技术在人工影响天气对空作业中的应用

本文根据人工影响天气(以下简称人影)作业安全射界管理需求,讨论分析了影响人影作业安全射界因素包括装备性能、弹药稳定性、高空气流、站点海拔和人员操作水平等,提出一种人影作业安全射界精细化绘制思路和方法,设计开发了基于高分辨率卫星影像数据和数字高程模型数据(以下简称DEM数据)人工标识技术的人影安全射界绘制系统。经实践应用,该系统输出的人影作业安全射界图,可解决传统射界图安全标记要素不全、绘制分辨率不高、信息化程度低等问题,对提升作业效益和安全管理水平具有一定的实用价值,可以向开展人影作业的各级单位推广使用。