夏季中国降水型的年代际变化与大气内部动力过程及外强迫因子关系

根据中国160站月平均降水、NCEP/NCAR的再分析资料以及英国气象局哈德莱中心1900～1999年全球1°×1°格点月平均海表温度距平资料,利用物理量诊断、EOF分析等方法,探讨东亚季风区大气环流内部动力过程与大气外强迫因子（海温）年代际变化及对中国夏季降水型的影响。分析发现,中国东部地区、西北地区夏季降水型有各自不同的年代际变化趋势;中国东部夏季降水型及东亚夏季风环流年代际变化趋势与大气外强迫因子北太平洋中纬度海温年代际变化（PDO）关系密切;中国西北地区夏季降水年代际变化与大气内部动力过程中纬度西风带扰动动能年代际减弱有关。     

Understanding and modeling basin hydrology: interpreting the hydrogeological signature

Basin landscapes possess an identifiable spatial structure, fashioned by climate, geology and land use, that affects their hydrologic response. This structure defines a basin's hydrogeological signature and corresponding patterns of runoff and stream chemistry. Interpreting this signature expresses a fundamental understanding of basin hydrology in terms of the dominant hydrologic components: surface, interflow and groundwater runoff. Using spatial analysis techniques, spatially distributed watershed characteristics and measurements of rainfall and runoff, we present an approach for modelling basin hydrology that integrates hydrogeological interpretation and hydrologic response unit concepts, applicable to both new and existing rainfall‐runoff models. The benefits of our modelling approach are a clearly defined distribution of dominant runoff form and behaviour, which is useful for interpreting functions of runoff in the recruitment and transport of sediment and other contaminants, and limited over‐parameterization. Our methods are illustrated in a case study focused on four watersheds (24 to 50 km²) draining the southern coast of California for the period October 1988 though to September 2002. Based on our hydrogeological interpretation, we present a new rainfall‐runoff model developed to simulate both surface and subsurface runoff, where surface runoff is from either urban or rural surfaces and subsurface runoff is either interflow from steep shallow soils or groundwater from bedrock and coarse‐textured fan deposits. Our assertions and model results are supported using streamflow data from seven US Geological Survey stream gauges and measured stream silica concentrations from two Santa Barbara Channel–Long Term Ecological Research Project sampling sites. Copyright © 2004 John Wiley & Sons, Ltd.     

基于DMSP-OLS和珞珈一号夜光遥感影像的粤港澳大湾区城市空间格局演变

夜光遥感影像数据可有效反映城市空间格局变化。本文基于1992—2012年的DSMP-OLS夜光遥感影像和2018年的珞珈一号遥感影像,利用分层阈值法提取粤港澳大湾区内各城市建成区;通过计算平均灯光强度、平均灯光增长速率、城市建成区面积、城市建成区增长速率、城市重心、城市重心偏移距离等一系列指数,揭示区内各城市的空间格局演变过程。研究结果表明:①1992—2018年,粤港澳大湾区的城市规模大幅增长,沿珠江口两侧形成了以澳门、广州、深圳和香港为核心的倒“U”形城市群,并呈辐射状向周边扩张。②以珠江口为界,粤港澳大湾区东部各个城市的发展水平整体高于西部各个城市,广州、深圳、香港等核心城市发展水平明显高于江门、肇庆、惠州等外围城市。③1992—2018年,粤港澳大湾区建成区的增长速率由小变大,最后逐渐趋于稳定,2002—2007年是城市扩张最迅猛时期。④1992—2018年,粤港澳大湾区的各城市重心迁移方式表现为3种类型:持续向区域中心迁移;持续向相邻城市邻接区迁移;持续向海洋方向迁移。大部分城市的重心迁移方向呈“震荡”特征。     

无人机三维倾斜摄影测量助力自然资源调查——以不动产调查为例

随着第一次地理国情普查与监测、第三次全国土地调查等重大自然资源调查类项目的实施,以无人机作为搭载平台的遥感影像获取手段在不断发展并深入应用,特别是无人机航测技术和地理信息技术的结合应用越来越紧密.本文以不动产调查为例,重点论述结合无人机三维倾斜摄影测量技术在内的测绘地理信息新手段的作业原理及应用情况,并对其优缺点进行总...     

利用众源地理数据快速测制大比例尺军事地形图

针对特战实训演练中大比例尺军事地形图数据不足、现势性较差的问题,从特战用图需求出发,基于众源地理数据提出了一种快速、高效、经济、准确的大比例尺军事地形图测制方法。首先,介绍了众源地理数据的概念和特点,研究了众源地理数据的来源和获取方法。然后,在顾及军事地形图与民用地形图之间制图表达的差异后,设计了利用众源地理数据绘制大比例尺军事地形图的工艺流程。最后,基于ArcMap,绘制了某地1∶1万军事地形图并进行实验验证和精度分析。实验结果表明,该方法既可有效提高作业效率,又能满足成图精度要求,可为军事教学训练、指挥员用图决策提供重要参考。     

黑龙江省耕地非农化的空间格局与重心曲线分析

为了揭示耕地非农化的空间格局与重心曲线,为耕地资源保护和利用政策制定提供决策支撑,该文以黑龙江省1980、1990、2000、2010、2015年土地利用数据为基础,运用GIS空间分析方法,引入重心模型分析黑龙江省耕地非农化的空间格局及重心曲线。研究结果表明:1980—2015年黑龙江省耕地非农化发展不平衡,4个时期耕地非农化面积呈波动增长的趋势;耕地非农化等级空间分布特征明显,等级较高的城市集中分布在西部地区;耕地非农化速度等级的重心曲线在空间分布上,具有从中心向边缘延伸的特点;耕地非农化围绕中心地区进行,其空间扩散路径在图形上呈现出一个回旋状。     

The Austrian node of the natural resources satellite remote sensing cloud service platform:examples of Sino-Austrian cooperation

The Austrian node of the Natural Resources Satellite Remote Sensing Cloud Service Platform was established in 2016 through a cooperation agreement between the Land Satellite Remote Sensing Application Center(LASAC),Ministry of Natural Resources of the Peoples Republic of China and the University of Vienna,Austria.Under this agreement panchromatic and multi-spectral data of the Chinese ZY-3 satellite are pushed to the server at the University of Vienna for use in education and research.So far,nearly 500 GB of data have been uploaded to the server.This technical note briefly introduces the ZY-3 system and illustrates the implementation of the agreement by the first China-Sat Workshop and several case studies.Some of them are already completed,others are still ongoing.They include a geometric accuracy validation of ZY-3 data,an animated visualization of image quick views on a spherical display to demonstrate the time series of the image coverage for Austria and Laos,and the use of ZY-3 data to study the spread of bark beetle in the province of Lower Austria.An accuracy study of DTMs from ZY-3 stereo data,as well as a land cover analysis and comparison of Austria with ZY-3 and other sensors are still ongoing.     

空间层次聚类显著性判别的重排检验方法

同时顾及空间邻近与专题属性相似的空间层次聚类是挖掘空间分布模式的一种有效手段。空间层次聚类方法虽然可以获得多层次的聚集结构,但聚类结果显著性的统计判别依然是一个尚未解决的难题。为此,本文提出了一种空间层次聚类结果显著性的统计判别方法,用于确定空间层次聚类的停止准则,减少聚类过程对参数设置的依赖。通过试验分析与比较发现,该方法能够有效判别空间层次聚类结果的显著性和确定层次聚类合并过程的停止条件,同时具有很好的抗噪性,避免随机结构的干扰。     

大连市地理信息共享平台建设内容探讨

以大连市为例,对城市地理信息系统共享平台的建设内容进行探讨,明确了建设目标,将系统的总体建设内容分为数据中心工程、标准规范工程、数据建设工程、运维管理工程、应用接口工程、应用系统工程6个部分,并对各部分进行详细地介绍。     

Grid pattern recognition in road networks using the C4.5 algorithm

Pattern recognition in road networks can be used for different applications, including spatiotemporal data mining, automated map generalization, data matching of different levels of detail, and other important research topics. Grid patterns are a common pattern type. This paper proposes and implements a method for grid pattern recognition based on the idea of mesh classification through a supervised learning process. To train the classifier, training datasets are selected from worldwide city samples with different cultural, historical, and geographical environments. Meshes are subsequently labeled as composing or noncomposing grids by participants in an experiment, and the mesh measures are defined while accounting for the mesh’s individual characteristics and spatial context. The classifier is generated using the C4.5 algorithm. The accuracy of the classifier is evaluated using Kappa statistics and the overall rate of correctness. The average Kappa value is approximately 0.74, which corresponds to a total accuracy of 87.5%. Additionally, the rationality of the classifier is evaluated in an interpretation step. Two other existing grid pattern recognition methods were also tested on the datasets, and comparison results indicate that our approach is effective in identifying grid patterns in road networks.