A method for checking the quality of geographic metadata based on ISO 19157

With recent advances in remote sensing, location-based services and other related technologies, the production of geospatial information has exponentially increased in the last decades. Furthermore, to facilitate discovery and efficient access to such information, spatial data infrastructures were promoted and standardized, with a consideration that metadata are essential to describing data and services. Standardization bodies such as the International Organization for Standardization have defined well-known metadata models such as ISO 19115. However, current metadata assets exhibit heterogeneous quality levels because they are created by different producers with different perspectives. To address quality-related concerns, several initiatives attempted to define a common framework and test the suitability of metadata through automatic controls. Nevertheless, these controls are focused on interoperability by testing the format of metadata and a set of controlled elements. In this paper, we propose a methodology of testing the quality of metadata by considering aspects other than interoperability. The proposal adapts ISO 19157 to the metadata case and has been applied to a corpus of the Spanish Spatial Data Infrastructure. The results demonstrate that our quality check helps determine different types of errors for all metadata elements and can be almost completely automated to enhance the significance of metadata.     

Integration of nighttime light remote sensing images and taxi GPS tracking data for population surface enhancement

The population distribution grid at fine scales better reflects the distribution of residents and plays an important role in investigating urban systems. The recent years have witnessed a growing trend of applying the nighttime light data to the estimation of population at micro levels. However, using the nighttime light data alone to estimate population may cause the overestimation problem due to excessively high light radiance in specific types of areas such as commercial zones and transportation hubs. In dealing with this issue, this study used taxi trajectory data that delineate people’s movements, and explored the utility of integrating the nighttime light and taxi trajectory data in the estimation of population in Shanghai at the spatial resolution of 500 m. First, the initial population distribution grid was generated based on the NPP-VIIRS nighttime light data. Then, a calibration grid was created with taxi trajectory data, whereby the initial population grid was optimized. The accuracy of the resultant population grid was assessed by comparing it with the refined survey data. The result indicates that the final population distribution grid performed better than the initial population grid, which reflects the effectiveness of the proposed calibration process.     

Hierarchical community detection and functional area identification with OSM roads and complex graph theory

An in-depth analysis of the urban road network structure plays an essential role in understanding the distribution of urban functional area. To concentrate topologically densely connected road segments, communities of urban roads provide a new perspective to study the structure of the network. In this study, based on OpenStreetMap (OSM) roads and points-of-interest (POI) data, we employ the Infomap community detection algorithm to identify the hierarchical community in city roads and explore the shaping role roads play in urban space and their relation with the distribution of urban functional areas. The results demonstrate that the distribution of communities at different levels in Guangzhou, China reflects the urban spatial relation between the suburbs and urban centers and within urban centers. Moreover, the study explored the functional area characteristics at the community scale and identified the distribution of various functional areas. Owing to the structure information contained in the identification process, the detected community can be used as a basic unit in other urban studies. In general, with the community-based network, this study proposes a novel method of combining city roads with urban space and functional zones, providing necessary data support and academic guidance for government and urban planners.     

Analysis of Spatio-temporal Land Surface Temperature and Normalized Difference Vegetation Index Changes in the Andassa Watershed,Blue Nile Basin,Ethiopia

Analysis of the nexus between vegetation dynamics and climatic parameters like surface temperature is essential in environmental and ecological studies and for monitoring of the natural resources. This study explored the spatio-temporal distribution of land surface temperature (LST) and Normalized Difference Vegetation Index (NDVI) and the relationship between them in the Andassa watershed from 1986 to 2016 periods using Landsat data. Monthly average air temperature data of three meteorological sites were used for validating the results. The findings of the study showed that the LST of the Andassa watershed has increased during the study periods. Overall, average LST has been rising with an increasing rate of 0.081°C per year. Other results of this study also showed that there has been a dynamic change in vegetation cover of the watershed in all seasons. There was also a negative correlation between LST and NDVI in all the studied years. From this study we can understand that there has been degradation of vegetation and intensification of LST from 1986 to 2016.     

中国物理海洋学研究70年:发展历程、学术成就概览

本文概略评述新中国成立70年来物理海洋学各分支研究领域的发展历程和若干学术成就。中国物理海洋学研究起步于海浪、潮汐、近海环流与水团,以及以风暴潮为主的海洋气象灾害的研究。随着国力的增强,研究领域不断拓展,涌现了大量具有广泛影响力的研究成果,其中包括:提出了被国际广泛采用的“普遍风浪谱”和“涌浪谱”,发展了第三代海浪数值模式;提出了“准调和分析方法”和“潮汐潮流永久预报”等潮汐潮流的分析和预报方法;发现并命名了“棉兰老潜流”,揭示了东海黑潮的多核结构及其多尺度变异机理等,系统描述了太平洋西边界流系;提出了印度尼西亚贯穿流的南海分支(或称南海贯穿流);不断完善了中国近海陆架环流系统,在南海环流、黑潮及其分支、台湾暖流、闽浙沿岸流、黄海冷水团环流、黄海暖流、渤海环流,以及陆架波方面均取得了深刻的认识;从大气桥和海洋桥两个方面对太平洋–印度洋–大西洋洋际相互作用进行了系统的总结;发展了浅海水团的研究方法,基本摸清了中国近海水团的分布和消长特征与机制,在大洋和极地水团分布及运动研究方面也做出了重要贡献;阐明了南海中尺度涡的宏观特征和生成机制,揭示了中尺度涡的三维结构,定量评估了其全球物质与能量输运能力;基本摸清了中国近海海洋锋的空间分布和季节变化特征,提出了地形、正压不稳定和斜压不稳定等锋面动力学机制;构建了“南海内波潜标观测网”,实现了对内波生成–演变–消亡全过程机理的系统认识;发展了湍流的剪切不稳定理论,提出了海流“边缘不稳定”的概念,开发了海洋湍流模式,提出了湍流混合参数化的新方法等;在海洋内部混合机制和能量来源方面取得了新的认识,并阐述了混合对海洋深层环流、营养物质输运等过程的影响;研发了全球浪–潮–流耦合模式,推出一系列海洋与气候模式;发展了可同化主要海洋观测数据的海洋数据同化系统和用于ENSO预报的耦合同化系统;建立了达到国际水准的非地转(水槽/水池)和地转(旋转平台)物理模 型实验平台;发展了ENSO预报的误差分析方法,建立了海洋和气候系统年代际变化的理论体系,揭示了中深层海洋对全球气候变化的响应;初步建成了中国近海海洋观测网;持续开展南北极调查研究;建立了台风、风暴潮、巨浪和海啸的业务化预报系统,为中国气象减灾提供保障;突破了国外的海洋技术封锁,研发了万米水深的深水水听器和海洋光学特性系列测量仪器;建立了溢油、危险化学品漂移扩散等预测模型,为伴随海洋资源开发所带来的风险事故的应急处理和预警预报提供科学支撑。文中引用的大量学术成果文献(每位第一作者优选不超过3篇)显示,经过70年的发展,中国物理海洋学研究培养了一支实力雄厚的科研队伍,这是最宝贵的成果。这支队伍必将成为中国物理海洋学研究攀登新高峰的主力军。     

基于深度学习的钨钼找矿靶区预测方法研究

随着矿产勘查工作由浅部矿向深部隐伏矿、由易识别矿向难识别矿发展,找矿难度日益增大,地质专家越来越重视新理论、新方法、新技术的应用。深度学习作为人工智能的前沿领域/技术,对于实现矿产资源预测“智能化预测评价”具有得天独厚的优势。本文以陕西省镇安县西部钨钼矿集区单元素化探异常原始数据为基础,提出了基于深度学习的钨钼矿产评价方法。该方法以归一化地球化学数据作为模型训练数据,通过深度学习中深度自编码网络方法实现异常值提取进而识别重点成矿有利地段,实现矿产资源找矿远景区定性预测。研究结果表明,在对957条单元素化探异常原始数据分类且做好模型标签后,整个过程在计算机的“黑盒子”中自动完成学习和预测,相较于传统预测研究方法,本文方法具有自动化程度高和客观性强的特征。此外,本文利用已知矿点构建训练数据集,采用随机森林方法对预测区进行矿产资源找矿靶区预测圈定,为进一步缩小找矿靶区范围提供科学依据。     

北斗三号组网卫星数据质量分析及单系统定轨精度初步评估

选取2018-01-23起10 d内16个iGMAS测站观测数据,对北斗三号卫星的观测数据质量及BDS单系统精密定轨精度进行评估。初步结果表明,老信号B1I、B3I北斗三号卫星的信噪比略强于二号卫星,噪声与多路径基本相当,均在0.1 m量级,新卫星不存在星内多路径偏差。新信号B1C/L1/E1频点GPS信噪比最强,Galileo和BDS卫星相当,B2a/L5/E5a和B2b/E5b各系统基本相当;噪声及多路径方面,B1C/L1/E1频点GPS优于BDS、Galileo卫星0.1 m量级,B2a/L5/E5a和B2b/E5b各系统基本相当,均在0.1 m量级,新信号中北斗三号卫星星内多路径偏差基本消失。单系统精密定轨试验中,分别进行有/无GEO卫星策略、太阳光压模型ECOM 五/九参数策略的比较,并使用卫星激光测距数据进行独立检核。初步结果表明,有GEO卫星、ECOM五参数光压模型的定轨精度最好,C19号卫星7个重叠弧段的平均定轨精度在沿迹向、法向、径向的精度分别为32 cm、16 cm、8 cm,与试验卫星的定轨精度基本相当。     

基于夜间灯光和土地利用数据的云南沿边地区GDP空间差异性分析

云南沿边地区包括8个地州,共56个县,其中有25个县市与老挝、缅甸和越南直接毗邻,具有重要的地缘位置。本研究利用土地利用数据和夜间灯光数据在实现云南沿边地区GDP空间化的基础上,对GDP的空间分布格局进行深入探讨,这对缩小区域经济差异及促进地区共同发展具有一定的指导意义。采用土地利用数据对国内生产总值（Gross Domestic Product, GDP）数据的第一产业进行空间化拟合,采用DMSP/OLS夜间灯光数据对GDP的第二、三产业进行拟合,将第一产业和第二、三产业空间化拟合的结果相加,实现云南沿边地区1992-2013年的GDP的空间化拟合。在此基础上对云南沿边地区GDP空间分布差异进行分析。结果表明：① 土地利用数据对第一产业建模的效果较好,拟合的多期数据的相对误差均低于1.12%,采用夜间灯光数据,基于“分类回归”方法对第二、三产业拟合相对误差最大仅为6.404%,最终二者之和拟合的GDP拟合精度都较好,相对误差最大仅为4.241%;② 22期GDP数据在空间分布上均呈现正的相关性,且均为显著集聚;③ GDP空间分布局部集聚的高值-高值区域集中在开远、蒙自等县域,低值-低值地区集中在绿春、西蒙等地区;④ 云南沿边地区县域之间的经济差异在1992-1996年逐渐增强,1996年之后,经济差异波动缩小,空间关联效应呈现波动式的增强和减弱;⑤ 云南沿边地区的三维插值结果均呈现出西北至东南一线的“洼地-丘陵-平地-高峰”地势变化格局,沿边地区的东南角地区即红河州的建水、个旧和开远等县市的GDP最高,“丘陵”地势主要集中在腾冲、保山市以及最南部的景洪地区,“洼地-平地”地势主要分布在沿边地区西北角的贡山和福贡等县域、西南角的西蒙和孟连等县及中部区域的绿春和江城县等地区。     

北京市居民地铁出行出发时间弹性时空分布特征研究

伴随城市转型进程的加快,交通需求不断膨胀,导致大城市交通拥堵日趋严重,以调节出行者的选择行为为核心要素的交通需求管理理念成为相关政策的重要理论基础,但现有研究也表明,交通需求管理对出行弹性较高的出行具有显著调节作用,而对出行弹性较低的出行调节作用并不明显。因此,加强出行弹性等居民出行行为研究日益迫切,而公交刷卡数据等新的时空数据为居民复杂出行行为的挖掘提供了新的契机。本文利用北京市2014年3月地铁刷卡数据,以出行者出发时刻的可变性来测度出发时间选择的可改变程度,对居民地铁出行出发时间选择弹性进行测度,并结合GIS空间分析技术对其时空分布特征进行分析。研究表明：① 北京市地铁出行的居民出行弹性平均值为0.521,出发时间选择弹性整体上较大,表明北京居民出发时间选择相对较为灵活;② 北京市居民地铁出行弹性存在时空差异,居民个体休息日出行弹性高于工作日,一天中高峰时段出行弹性高于非高峰时段;③ 居民出行弹性存在空间自相关,倾向于在空间上发生集聚,存在明显的冷热点区域;内城居民的出行弹性明显高于城市外围居民。