A method to generalize stream flowlines in small-scale maps by a variable flow-based pruning threshold

The aim of this paper is to explore and describe a method of automated generalization designed to produce a map which strikes a balance between cartographic and hydrologic representations. Following a discussion of scholarly literature on generalization, we describe a novel method for automated generalization of hydrographic stream data, using the National Hydrography Data Set (NHDPlus) as an example.

Traditional hydrography shows a fairly uniform density of stream flowlines over space. While this is pleasing to the eye, traditional methods tend to under-represent rivers in humid areas and over-represent them in arid areas. We address this problem through a method in automated generalization to produce a high-quality presentation of hydrographic data, suitable for display as a wall map or in an atlas. Streams are pruned based on a variable flow threshold, derived from the local mean annual precipitation by a regression equation.

After running the model using different parameters, we produce a more satisfactory portrayal of stream networks in the United States that communicates the flow of water through rivers and reflects the regional climate. Specific advantages in generalizing with variable flow threshold include (1) the method allows for fine gradations in output scale; (2) the output maps tend to minimize density variations in the raw data; (3) the subjective criteria are easily derived; and (4) the method can be performed rapidly on large data sets, as long as the stream data has been enriched with reliable flow rates.     

数字沈阳基础地理信息空间框架数据组织方式

数字城市基础地理信息空间框架项目建设是沈阳市2012年重点工程项目。该项目建设的关键环节在于数字城市基础地理信息空间框架数据组织。数据组织要满足框架数据的约束条件,在严格符合规程要求的前提下针对各城市数据现状的特点确定数据的组织路线。先确定数据类别,再找出各类数据的各自组织方式。     

Aster DEM数据与1∶50000地面高程库数据的精度比较分析

ASTER DEM是利用高分辨率卫星成像设备ASTER获取的立体影像生成的DEM,其全球覆盖范围较广、数据获取快、质量稳定。但其数据精度和质量在我国区域内存在较多不确定性,本文选取具有高山峡谷等典型地貌特征的秦岭山区的ASTER DEM数据,以相应1∶50 000地面高程库数据作参照,从总体统计、检查点法以及剖面法几个方面对其精度进行了实验与分析。结果表明,与地面1∶50 000地面高程库相比,ASTER DEM误差值所对应的点数数据分布呈正态分布,RMSE为30.109 358 028 165 158 m;且其在山峰上的高程值会有所降低,在山谷中的高程值会有所增加。     

基于jitter采样和曲波变换的三维地震数据重建

传统的地震勘探数据采样必须遵循奈奎斯特采样定理,而野外数据采样可能由于地震道缺失或者勘探成本限制,不一定满足采样定理要求,因此存在数据重建问题.本文基于压缩感知理论,利用随机欠采样方法将传统规则欠采样所带来的互相干假频转化成较低幅度的不相干噪声,从而将数据重建问题转为更简单的去噪问题.在数据重建过程中引入凸集投影算法(POCS),提出采用e^-√x(0≤x≤1)衰减规律的阈值参数,构建基于曲波变换三维地震数据重建技术.同时针对随机采样的不足,引入jitter采样方式,在保持随机采样优点的同时控制采样间隔.数值试验表明,基于曲波变换的重建效果优于傅里叶变换,jitter欠采样的重建效果优于随机欠采样,最后将该技术应用于实际地震勘探资料,获得较好的应用效果.     

E) Organisations non Gouvernementales / Non Governmental Organizations

SUMMARY

The evaporation tank consists of a square pan with a flat base, 2 metres long and 0, 7 metre deep, set into the ground with the rim 0, 1 metre above, and connected to a well on which is installed a limnigraph. This limnigraph records continuously fluctuations of the free water surface.

The recordings show that a large amount of water can be evaporated during rainfall. This phenomenon is specific at every evaporation tank with a free water surface. It is only during the dry intervals that a strong correlation can be established between the evaporation measured in the tank and the potential evapotranspiration of the surrounding natural surfaces. In order to locate the dry intervals and to measure the evaporation only during these intervals, it is necessary to use an apparatus provided with a continuous recording mechanism     

运用策略路由技术保障新疆测震台网数据的稳定传输

为保证测震台网数据稳定可靠传输,提高本区域行业网络带宽利用率,分析了行业网络3条上行链路带宽占用情况及拥塞原因,运用策略路由技术,在网络边界设备上制定并应用规则改变了数据包的选路。通过对比分析前后获取的流量图,说明在设备上使用策略路由技术可以较好地均衡使用3条上行链路,保障测震数据畅通传输。     

冰雷达探测数据处理方法研究——以南极冰盖Dome A地区的数据处理为例

提出了冰雷达数据处理的流程,详细论述了冰雷达数据处理中常规修正的关键技术：静态校正、增益控制、带通滤波以及偏移处理等。以中国第24次南极科学考察（CHINARE 24）所获取的Dome A 地区30 km×30 km范围冰雷达原始数据处理作为实例,提取得到了该区域冰盖内部等时层埋深以及冰盖的冰厚数据。通过插值展现了冰盖等时层以及冰岩界面的三维空间形态。结合该区域ICESat冰盖表面高程数据,构建出了Dome A地区涵盖冰盖表面、冰盖等时层以及冰岩界面形态特征的三维模型。     

The role of sub‐national government and the private sector in future spatial data infrastructures

A Spatial Data Infrastructure (SDI) facilitates and coordinates the exchange and sharing of spatial data between stakeholders in the spatial data community. With this objective in mind, countries throughout the world are developing SDIs to manage and utilize their spatial data assets more effectively. These countries are developing SDIs to assist in various kinds of decision‐making at different levels of government jurisdictions that have an important impact within their national boundaries. However, current research shows that SDI is understood and described differently by stakeholders from different disciplines and different jurisdictional levels. Therefore, in many cases, SDI initiatives remain very much an innovation, even among practitioners. There are still uncertainties regarding the benefits and identities of SDIs, particularly in connection with how they evolve over time to meet user needs. This paper reviews and assesses the development of SDIs throughout the world over the past 15 years and the leadership role of national governments in SDI creation. This assessment is based on the SDI activities of various jurisdictions including Asia‐Pacific, Australia, North America, and Europe, and research into the worldwide effects of spatial information clearing houses. This assessment includes a discussion on emerging trends in SDI development, with particular reference to the increasingly important role played by sub‐national governments and the private sector within the framework of SDI development. The paper concludes with a discussion of the implications for future SDI development, including the delivery of a virtual world that has a particular focus on facilitating decision‐making at a community level within a national context.     

A spatiotemporal data model for river basin‐scale hydrologic systems

Despite a long history of synergy, current techniques for integrating Geographic Information System (GIS) software with hydrologic simulation models do not fully utilize the potential of GIS for modeling hydrologic systems. Part of the reason for this is a lack of GIS data models appropriate for representing fluid flow in space and time. Here we address this challenge by proposing a spatiotemporal data model designed specifically for large‐scale river basin systems. The data model builds from core concepts in geographic information science and extends these concepts to accommodate mathematical representations of fluid flow at a regional scale. Space–time is abstracted into three basic objects relevant to hydrologic systems: a control volume, a flux and a flux coupler. A control volume is capable of storing mass, energy or momentum through time, a flux represents the movement of these quantities within space–time and a flux coupler insures conservation of the quantities within an overall system. To demonstrate the data model, a simple case study is presented to show how the data model could be applied to digitally represent a river basin system.     

Hydrological data assimilation with the Ensemble Square-Root-Filter: Use of streamflow observations to update model states for real-time flash flood forecasting

The objective of the study is to evaluate the potential of a data assimilation system for real-time flash flood forecasting over small watersheds by updating model states. To this end, the Ensemble Square-Root-Filter (EnSRF) based on the Ensemble Kalman Filter (EnKF) technique was coupled to a widely used conceptual rainfall-runoff model called HyMOD. Two small watersheds susceptible to flash flooding from America and China were selected in this study. The modeling and observational errors were considered in the framework of data assimilation, followed by an ensemble size sensitivity experiment. Once the appropriate model error and ensemble size was determined, a simulation study focused on the performance of a data assimilation system, based on the correlation between streamflow observation and model states, was conducted. The EnSRF method was implemented within HyMOD and results for flash flood forecasting were analyzed, where the calibrated streamflow simulation without state updating was treated as the benchmark or nature run. Results for twenty-four flash-flood events in total from the two watersheds indicated that the data assimilation approach effectively improved the predictions of peak flows and the hydrographs in general. This study demonstrated the benefit and efficiency of implementing data assimilation into a hydrological model to improve flash flood forecasting over small, instrumented basins with potential application to real-time alert systems.