城市空间智能计算平台研究

该文提出了空间智能平台的概念,阐述了其研究意义和内容,明确了空间智能计算平台核心计算模型的建模对象和目标。在此基础上,分析了宏观数学模型、群体行为模型两种用来构建空间活动模型的建模方法以及适用于空间活动分析的物理环境建模技术。从融合多尺度行为模型、构建城市日常生活模型、验证和校验核心模型以及平衡效率和效果4方面探讨了构建空间智能计算平台的关键技术。从实际功能看,城市空间智能平台是联系宏观复杂问题和微观机制的桥梁,是分析城市问题的工程化实验平台,具有广阔的应用前景。     

Satellite-observed trends in the Arctic sea ice concentration for the period 1979–2016

Arctic sea ice cover has decreased dramatically over the last three decades. This study quanti?es the sea ice concentration(SIC) trends in the Arctic Ocean over the period of 1979–2016 and analyzes their spatial and temporal variations. During each month the SIC trends are negative over the Arctic Ocean, wherein the largest(smallest) rate of decline found in September(March) is-0.48%/a(-0.10%/a).The summer(-0.42%/a) and autumn(-0.31%/a) seasons show faster decrease rates than those of winter(-0.12%/a) and spring(-0.20%/a) seasons. Regional variability is large in the annual SIC trend. The largest SIC trends are observed for the Kara(-0.60%/a) and Barents Seas(-0.54%/a), followed by the Chukchi Sea(-0.48%/a), East Siberian Sea(-0.43%/a), Laptev Sea(-0.38%/a), and Beaufort Sea(-0.36%/a). The annual SIC trend for the whole Arctic Ocean is-0.26%/a over the same period. Furthermore, the in?uences and feedbacks between the SIC and three climate indexes and three climatic parameters, including the Arctic Oscillation(AO), North Atlantic Oscillation(NAO), Dipole anomaly(DA), sea surface temperature(SST), surface air temperature(SAT), and surface wind(SW), are investigated. Statistically, sea ice provides memory for the Arctic climate system so that changes in SIC driven by the climate indices(AO, NAO and DA) can be felt during the ensuing seasons. Positive SST trends can cause greater SIC reductions, which is observed in the Greenland and Barents Seas during the autumn and winter. In contrast, the removal of sea ice(i.e., loss of the insulating layer) likely contributes to a colder sea surface(i.e., decreased SST), as is observed in northern Barents Sea. Decreasing SIC trends can lead to an in-phase enhancement of SAT, while SAT variations seem to have a lagged in?uence on SIC trends. SW plays an important role in the modulating SIC trends in two ways: by transporting moist and warm air that melts sea ice in peripheral seas(typically evident inthe Barents Sea) and by exporting sea ice out of the Arctic Ocean via passages into the Greenland and Barents Seas, including the Fram Strait, the passage between Svalbard and Franz Josef Land(S-FJL),and the passage between Franz Josef Land and Severnaya Zemlya(FJL-SZ).     

渤海AVHRR多通道海冰密集度反演算法试验研究

为了得到更精确的渤海海冰密集度反演参数,采用辽东湾不同类型海冰ASD实测数据,在分析光谱特征的基础上,针对NOAA/AVHRR数据确定出合适海冰密集度反演算法阈值。继而,基于线性光谱混合模型的多通道反演算法进行了一系列算法试验。同时实现了基于LandSat5-TM数据的渤海海冰密集度场反演,并利用该结果与AVHRR单通道和多通道算法得到的海冰密集度反演结果进行比对分析。定量误差分析结果表明,当单通道算法或组合算法中包含1通道时,与Landsat5-TM反演结果的平均误差为正值,包含2通道且不包含1通道时,平均误差为负值;同时使用这两个通道较只包含其一的各种组合算法的平均误差明显偏小;在各种组合算法中,1245四个通道组合反演的海冰密集度结果误差最小,可应用于渤海AVHRR数据海冰密集度反演。     

地学G4I系统的开发研究

G4I系统基于数据集成、发掘与信息融合这一构想,设计开发了一种以地质学、地理学、地球化学、地球物理学等地学数据信息集成分析为内核,提供矿产资源预测服务为目标的计算机系统,是服务于地壳下位空间信息机理与模型分析体系的数字化地学信息平台。本文介绍了地学G4I系统的设计原理与过程,以及应用到“河北地勘局多源地学信息系统”中。     

两种自适应串行干扰消除器的比较

多用户检测中的串行干扰检测器,因其结构简单、计算复杂度低而倍受关注,但由于其自身结构特点,容易引起误差传播.在串行干扰检测器中加入自适应滤波算法,使自适应消除器的权重很好地跟踪信道变化.通过计算机仿真可知,采用递归最小二乘的自适应串行干扰消除器比最小均方自适应串行干扰消除器在抗多址和抗远近效应方面性能要更胜一筹.     

中分辨率成像光谱仪的海冰密集度遥感反演

海冰信息在船舶运输、天气预报和全球气候预测等领域都起着重要作用.一直以来微波遥感是卫星监测海冰密集度的主要手段,目前基于可见光遥感的中分辨率海冰密集度产品还较少,其中只有NOAA发布了相关业务化产品,但其所采用的算法对低密集度海冰反演准确性仍存在提升空间.本文在Liu提出的算法基础上进行改进,提出了最邻近像素法确定纯冰...     

基于SIC的伪卫星系统抗远近效应捕获算法研究

地基伪卫星系统中由于远近效应的影响,近场伪卫星信号可能对远场伪卫星信号形成压制干扰,导致远场伪卫星信号无法被捕获. 针对该系统中使用的跳时直接序列扩频(TH-DSSS)信号的捕获问题,引入串行干扰消除(SIC)技术,缓解伪卫星系统中的远近效应问题,通过本地重构强信号和干扰对消降低强信号对弱信号捕获的影响,并从理论和仿真两方面对其性能进行了分析. 仿真结果表明,相比传统未采用干扰消除的捕获算法而言,基于SIC的信号捕获方法在不改变伪卫星基站结构和接收机框架的基础上,可有效降低远近效应的影响,提高弱信号捕获概率,扩大系统工作范围,从而为接收机在强远近效应场景下的捕获、跟踪和定位解算提供有效保障.      

长时间序列北极海冰密集度遥感数据的比较评估

基于空间分辨率和精度更高的BLM海冰密集度数据集, 评估了两种时间跨度较长、 应用广泛的25 km分辨率海冰密集度遥感数据集——NSIDC数据集和SICCI数据集。两种数据集与BLM数据集的海冰面积变化趋势相同, 但均低于基于BLM数据集得到的海冰面积, 其中基于SICCI数据集得到的海冰面积更接近BLM数据集。相比于NSIDC数据集, SICCI数据集的年、 月平均和日海冰面积偏差分别低81.88%、 80.90%、 81.44%, 且其海冰密集度平均偏差为-3.28%, 低于NSIDC数据的4.36%, 因此在进行北极地区整体海冰面积及海冰密集度分析时应选用SICCI数据集。按纬度、 海冰密集度值分情况对两种数据进行比较, 发现NSIDC数据集对开阔水域和浮冰区的区分效果较差, 其在低纬度和低密集度区域的平均偏差分别为10.11%和13.13%, 而SICCI数据集的平均偏差达到0.05%和0.44%, 是研究低纬度和中低海冰密集度区域的首选数据。与之相对, NSIDC数据集对中高纬度高海冰密集区域, 特别是近北极点区域的反映能力优于SICCI数据集, 平均偏差为1.08%, 均方根偏差为7.76%, 因此进行中高纬度高海冰密集度区域分析时首选NSIDC数据集。对两类数据集在北极东北航道上的分段评估结果发现, 低纬度海冰边缘地带或中低海冰密集度区域占比较高的航段区, SICCI数据集更接近BLM数据集, 这些航段应使用SICCI数据集进行分析; 而在中高纬度高海冰密集度区域占比较高的航段区, NSIDC数据集更加贴合, 应为首选数据集。     

对加拿大萨德伯里撞击构造的考察及其启示

简介了近年来萨德伯里撞击构造及超大型铜镍硫化物矿床的研究现状和作者现场考察所得的认识。记述了萨德伯里的撞击构造、陨石撞击事件及其构造效应、岩浆杂岩（SIC）和有关成因争论；叙述了该大陨石坑的变形和邻近格林威尔造山作用导致的NW－SE向缩短和剪切作用；还介绍了萨德伯里铜镍硫化物矿床撞击成矿假说；最后，特别提出在从事地球动力学和成矿作用动力学研究时，应十分注意类似萨德伯里陨石撞击灾变事件及损击成矿作用的研究。     

Comparison on soil carbon stocks between urban and suburban topsoil in Beijing,China

The urban population and urbanized land in China have both increased markedly since the 1980s. Urban and suburban developments have grown at unprecedented rates with unknown consequences for ecosystem functions. In particular, the effect of rapid urbanization on the storage of soil carbon has not been studied extensively. In this study, we compared the soil carbon stocks of different land use types in Beijing Municipality. We collected 490 top-soil samples （top 20 cm） from urban and suburban sites within the Sixth Ring Road of Beijing, which cover approximately 2400 km2, and the densities of soil organic carbon （SOC）, soil inorganic carbon （SIC）, and total carbon （TC） were analyzed to determine the spatial distribution of urban and suburban soil carbon characteristics across seven land use types. The results revealed significant differences in soil carbon densities among land use types. Additionally, urban soil had significantly higher SOC and SIC densities than suburban soil did, and suburban shelterbelts and productive plantations had lower SIC densities than the other land use types. The comparison of coefficients of variance （CVs） showed that carbon content of urban topsoil had a lower variability than that of suburban topsoil. Further findings revealed that soil carbon storage increased with built-up age. Ur- ban soil built up for more than 20 years had higher densities of SOC, SIC and TC than both urban soil with less than 10 years and sub- urban soil. Correlation analyses indicated the existence of a significantly negative correlation between the SOC, SIC, and TC densities of urban soil and the distance to the urban core, and the distance variable alone explained 23.3% of the variation of SIC density and 13.8% of the variation of TC density. These results indicate that SOC and SIC accumulate in the urban topsoil under green space as a result of the conversion of agricultural land to urban land due to the urbanization in Beijing.