Developing Standards for a National Spatial Data Infrastructure

The concept of a framework for data and information linkages among producers and users, known as a National Spatial Data Infrastructure (NSDI), is built upon four corners: data, technology, institutions, and standards. Standards are paramount to increase the efficiency and effectiveness of the NSDI. Historically, data standards and specifications have been developed with a very limited scope — they were parochial, and even competitive in nature, and promoted the sharing of data and information within only a small community at the expense of more open sharing across many communities. Today, an approach is needed to grow and evolve standards to support open systems and provide consistency and uniformity among data producers. There are several significant ongoing activities in geospatial data standards: transfer or exchange, metadata, and data content. In addition, standards in other areas are under discussion, including data quality, data models, and data collection.     

The Spatial Data Transfer Standard (FIPS 173): A Management Perspective

The Spatial Data Transfer Standard (SDTS) was approved by the Department of Commerce as Federal Information Processing Standard (FIPS) 173 on July 29, 1992. As a FIPS, the SDTS will serve as the national spatial data transfer mechanism for all federal agencies and will be available for use by state and local governments, the private sector, and research organizations. FIPS 173 will transfer digital spatial data sets between different computer systems, making data sharing practicable. This standard is of significant interest to users and producers of digital spatial data because of the potential for increased access to and sharing of spatial data, the reduction of information loss in data exchange, the elimination of the duplication of data acquisition, and the increase in the quality and integrity of spatial data. The success of FIPS 173 will depend on its acceptance by users of spatial data and by vendors of spatial information systems. Comprehensive workshops are being conducted, and the tools and procedures necessary to support FIPS 173 implementations are being developed. The U.S. Geological Survey, as the FIPS 173 maintenance authority, is committed to involving the spatial data community in various activities to promote acceptance of FIPS 173 and to providing case examples of prototype FIPS 173 implementations. Only by participating in these activities will the members of the spatial data community understand the role and impact of this standard.     

Developing a Raster Profile for the Spatial Data Transfer Standard

The Spatial Data Transfer Standard (SDTS) was designed to transfer both vector and raster data sets. In the early development of the SDTS, the designers recognized that there was a need to transfer raster data in addition to the more challenging vector data. As a result, the SDTS includes a “raster module” that accommodates a variety of raster data structures and formats. A raster profile is being developed that will exercise a selected subset of SDTS capabilities in order to provide a simple-to-use transfer of complete raster data sets.     

An Overview of FIPS 173, The Spatial Data Transfer Standard

The Spatial Data Transfer Standard (SDTS), after nine years of development, was approved on July 29, 1992, as FIPS Publication 173. The SDTS consists of three distinct parts. Part 1 is concerned with logical specifications required for spatial data transfer and has three major components: a conceptual model of spatial data, data quality report specifications, and detailed logical transfer format specifications for SDTS data sets. Part 2 provides a model for the definition of real-world spatial features, attributes, and attribute values and includes a standard but working and expandable list with definitions. Part 3 specifies the byte-level format implementation of the logical specifications in SDTS Part 1 using ISO/ANSI 8211 (FIPS 123), a general data exchange standard.     

Implementation of the Spatial Data Transfer Standard in the Commonwealth of Virginia

Present efforts to implement the Spatial Data Transfer Standard (SDTS) within the Commonwealth of Virginia are centered in Virginia's Council on Information Management (CIM). Since 1992, mapping, surveying and land information systems activities have been identified as a responsibility of the Council "The promotion of access to federal and other digital data banks through standards" is an area of CIM interest specified in the Code of Virginia. Prior to adoption of the SDTS by Virginia in November 1994, a Technical Advisory on the SDTS was issued and a SDTS Training and Education Plan was adopted. The Council on Information Management has worked with the USGS SDTS Task Force in developing this plan.     

Conformance Testing for the Spatial Data Transfer Standard

The Spatial Oata Transfer Standard (SOTS) was approved as Federal Information Processing Standard (FIPS) 173, effective February 1993. Federal agencies and geographic information system vendors currently are developing SOTS encoding and decoding capabilities. A program is being developed to test encoders and decoders for conformance to the requirements of SOTS profiles. A series of test points will specify SOTS requirements that can be tested by software or by nonautomated methods. By certifying SOTS products, the conformance testing program will benefit both vendors and users of the SOTS.     

Opportunities for Use of the Spatial Data Transfer Standard at the State and Local Level

Dramatic changes in the way that spatial data have been collected and processed over that last 20 years is leading to a rethinking and restructuring on the most efficient ways to handle geographical information. These changes are taking place at the federal, state, and local governmental levels with great potential for the private sector as well. The formal adoption of the Spatial Data Transfer Standard (SDTS) as the federal database transfer standard for spatial databases signals a new era in this long chain of developments. It offers more flexible and efficient database transfers than earlier tools, and will become the workhorse for implementing the new National Spatial Data Infrastructure. It offers organizations a standard that will make possible and practical a much wider sharing of databases than is currently being done today. Use of the SDTS presents an opportunity to many organizations to share data more easily and reduce the duplication of expensive spatial database resources.     

Design of a Spatial Data Transfer Processor

A processor to support the Spatial Data Transfer Standard (NIST 1992) is being designed. The Spatial Data Transfer Processor will support both encoding and decoding operations. The system will have five components: transfer manager, content encoder, format encoder, content decoder, and format decoder. No component will have expertise in more than one area. The system design should be used as a guide when developing software for the SDTS. NOTE: Readers should be familiar with mapping concepts described in the article “An Implementation Strategy for SDTS Encoding,” located elsewhere in this issue.     

Profile Development for the Spatial Data Transfer Standard

The Spatial Data Transfer Standard (SDTS), or Federal Information Processing Standard (FIPS) 173, is designed to support all types of spatial data. Implementing all of the standard's options at one time is impractical. Therefore, implementation of the SDTS is being accomplished through the use of profiles. Profiles are clearly defined, limited subsets of the SDTS created for use with a specific type or model of data and designed with as few options as possible. When a profile is proposed, specific choices are made for encoding possibilities that were not addressed, left optional, or left with numerous choices within the SDTS. Profile development is coordinated by the U.S. Geological SUIVey's SDTS Task Force. When completed, profiles are submitted to the National Institute of Standards and Technology (NIST) for approval as official amendments to the SDTS. The first profile, the Topological Vector Profile (TVP), has been completed. A Raster Profile has been tested and is being finalized for submission to the NIST. Other vector profiles, such as those for network and nontopological data, are also being considered as future implementation options for the SDTS.     

The Search for Boundaries on Maps: Color Processing and Map Pattern Effects

This paper presents a model which combines three of the parameters of the "Swiss manner" of relief representation with the Yoeli method of analytical hill-shading.

The model consists of various computational and graphic procedures that are intended to imitate by computer the complex hand-shading process. The first two procedures adjust the light source vertically and horizontally to the local relief forms. The adjustments avoid the disappearance of edges in unfavorable positions and exaggeration of others, and they utilize digitized data of the network of ridges and ravines. A third algorithm deals with "atmospheric perspective," the phenomenon of diminished value contrast in low lands and enhanced contrast in upper areas. This procedure also allows a general change in tonal value as a function of altitude. Other procedures deal with multicolor relief shading techniques, small-scale generalization, and selected reproduction problems.

Graphic output has been performed on a modified printer (IBM 1443) and a CRT raster recorder.     

Variable-scale Topological Data Structures Suitable for Progressive Data Transfer: The GAP-face Tree and GAP-edge Forest

This paper presents the first data structure for a variable scale representation of an area partitioning without redundancy of geometry. At the highest level of detail, the areas are represented using a topological structure based on faces and edges; there is no redundancy of geometry in this structure as the shared boundaries (edges) between neighbor areas are stored only once. Each edge is represented by a Binary Line Generalization (BLG)-tree, which enables selection of the proper representation for a given scale. Further, there is also no geometry redundancy between the different levels of detail. An edge at a higher importance level (less detail) does not contain copies of the lower-level edges or coordinates (more detail), but it is represented by efficiently combining their corresponding BLG trees. Which edges have to be combined follows from the generalization computation, and this is stored in a data structure. This data structure turns out to be a set of trees, which will be called the (Generalized Area Partitioning) GAP-edge forest. With regard to faces, the generalization result can be captured in a single tree structure for the parent-child relationships—the GAP face-tree. At the client side there are no geometric computations necessary to compute the polygon representations of the faces, merely following the topological references is sufficient. Finally, the presented data structure is also suitable for progressive transfer of vector maps, assuming that the client maintains a local copy of the GAP-face tree and the GAP-edge forest.     

A New Construction Method for Circle Cartograms

An area cartogram is a transformed map on which areas of regions are proportional to statistical data values; it is considered to be a powerful tool for the visual representation of statistical data. A circle cartogram is a type of area cartograms, on which regions are represented by circles. Its first construction algorithm is proposed by Dorling in 1996, based on the following requirements to construct visually elegant cartograms: 1) maintain the similarity of configurations between circles and regions, 2) express the contiguity of regions on cartograms if possible, and 3) avoid overlap of circles. The algorithm is widely used for its easiness to use and its ability to express a spatial distribution of data; however, the relative positions of circles on cartograms sometimes greatly differ from the geographical maps, since the algorithm does not consider the first requirements explicitly. In this paper, it is first pointed out that the construction problem of circle cartograms resembles that of distance cartograms, and the only difference is the existence of third requirement. Then a new construction method for circle cartograms is proposed based on the distance cartogram construction method; the proposed method is formulated as non-linear minimization with inequality constraint conditions. Finally its applicability is confirmed using dataset, including the comparison with the result of previous algorithm.     

Positional Accuracy of Spatial Data: Non-Normal Distributions and a Critique of the National Standard for Spatial Data Accuracy

Spatial data quality is a paramount concern in all GIS applications. Existing spatial data accuracy standards, including the National Standard for Spatial Data Accuracy (NSSDA) used in the United States, commonly assume the positional error of spatial data is normally distributed. This research has characterized the distribution of the positional error in four types of spatial data: GPS locations, street geocoding, TIGER roads, and LIDAR elevation data. The positional error in GPS locations can be approximated with a Rayleigh distribution, the positional error in street geocoding and TIGER roads can be approximated with a log‐normal distribution, and the positional error in LIDAR elevation data can be approximated with a normal distribution of the original vertical error values after removal of a small number of outliers. For all four data types considered, however, these solutions are only approximations, and some evidence of non‐stationary behavior resulting in lack of normality was observed in all four datasets. Monte‐Carlo simulation of the robustness of accuracy statistics revealed that the conventional 100% Root Mean Square Error (RMSE) statistic is not reliable for non‐normal distributions. Some degree of data trimming is recommended through the use of 90% and 95% RMSE statistics. Percentiles, however, are not very robust as single positional accuracy statistics. The non‐normal distribution of positional errors in spatial data has implications for spatial data accuracy standards and error propagation modeling. Specific recommendations are formulated for revisions of the NSSDA.     

DEM产品质量检查标准研究与实现

随着测绘技术的发展进步,测绘产品质量特点也发生了质的变化。本文从生产实际出发,深入分析了测绘成果质量评定标准,探讨了DEM产品质量检查与评价,基于C#.Net平台设计并实现了"DEM质量检查与评价系统"。实践证明,该系统能够大幅度提高DEM质量检查效率,实现对DEM质量的良好控制,对测绘生产单位具有重要意义。     

城市空间数据生产的技术框架探讨

城市空间数据是城市GIS、数字城市乃至数字中国的核心要素之一。我国城市空间数据生产取得了巨大成就，但尚不能满足城市发展的需求。“快、准、全、廉”地生产与提供城市空间数据应该成为未来的奋斗目标。为此，需要面向应用建立一个统一的包括数据形式、内容、尺度、质量与标准等在内的技术框架。     

煤矿地理信息系统空间数据引擎的设计

在煤矿地理信息系统中,现有的文件存储方式无法实现空间数据和属性数据的统一存储,难以保持数据一致性,不支持多用户并发处理,空间数据管理的效率有待提高。另外,由于煤矿空间数据的复杂性和特殊性,普通空间数据引擎难以应用。为此,本文提出了一种煤矿地理信息系统空间数据引擎,以解决煤矿空间数据的管理和存储问题。最后,结合试验验证了该引擎的可行性与有效性。     

WaterNet: A GIS Application for the Analysis of Hydrologic Networks Using Vector Spatial Data

Traditionally, stream and sub‐watershed characterization in GIS has been accom‐ plished using a DEM‐based terrain analysis approach; however, there is a large amount of existing vector hydrographic data difficult to accurately reproduce using DEMs. WaterNet is a GIS/hydrologic application for the integration and analysis of stream and sub‐watershed networks in vector format. Even with vector data, hydrologic inconsistencies between streams and sub‐watersheds do exist, and are revealed in the form of streams crossing drainage divides and sub‐watersheds with more than one outlet. WaterNet rectifies these inconsistencies and couples the two datasets. Most algorithms involving traces of dendritic networks employ a form of tree traversal which requires topologic information to be organized into specialized data structures. On the contrary, WaterNet develops topologic relationships from GIS attribute tables, which, in combination with sorting and querying algorithms, make the calculation process efficient and easy to implement. With the topologic relationships of the streams and sub‐watersheds, WaterNet can perform traces to calculate cumulative network parameters, such as flow lengths and drainage areas. WaterNet was applied to the catchment of the Texas Gulf coast for a total of 100 cataloging units (411,603 km²) and 60,145 stream lines (183,228 km).     

Exhibiting the Exhibitors: Spatial Visualization for Heterogeneous Cinema Venue Data

Abstract

Cinema data is characteristically complex, heterogeneous and interlinked. Rather than relying on simple information retrieval techniques, researchers are increasingly turning to the creative exploration and reapplication of data in order to more fully explore the meaning of newly available and diverse data sets. In this context, the cinema historian becomes the creator of visual texts which can be assessed for both their interpretive insight and their aesthetic qualities. This paper presents four research projects that use different spatio-temporal visualization techniques to understand the industrial dynamics of post-war film exhibition and distribution in Australia. The research integrates work by a group of inter-disciplinary investigators into the effectiveness of techniques such as dendritic mapping, Circos circular visualizations, animation, cartogram mapping, and multivariate visualization for the study of cinema circuits and operations at a number of scales.     

基于触发器自动配置的土地利用变化数据捕获技术

研究了业务驱动的土地利用变化发现机制的基本思路及其实现方法,提出了基于数据库触发器机制完成土地利用变化数据捕获的技术方案,涵盖触发器自动配置和变化数据缓存、传输、管理。结合试点应用,完整地实现了这套技术方案。试点应用表明,该研究成果能够及时地发现土地利用变化信息并进行有效的管理和应用。