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.     

Cartography/Geographic Information Systems at Southwest Texas State University

Australia and New Zealand are adopting the Spatial Data Transfer Standard (SDTS) as their transfer standard for geographic data. The standard requires a number of modifications to suit Australia/New Zealand requirements. These modifications primarily involve coordinate reference systems for each country, references to those standards applicable to each country and new spatial feature dictionaries. For other countries adopting SDTS, future revisions to the standard should emphasize a framework for required modifications. Australia/New Zealand have established a support body to ensure the smooth introduction of the standard within these countries. This commercial venture has been successful in promoting the standard, in providing training and in related consulting work. The US Geological Survey has been the maintenance authority for the standard. It is essential that this function continues to be provided through this body to guarantee a single interpretation of the standard.     

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.     

The SDTS Topological Vector Profile

Because the Spatial Data Transfer Standard (SDTS), also Federal Information Processing Standard 173, is designed to support any type of spatial data, implementing all of its options at one time is impossible. Instead, the SDTS is implemented through the use of profiles, which are limited subsets of the SDTS. The first profile developed is the Topological Vector Profile. This profile supports geographic vector data with geometry and topology. It does not support raster data, graphic representation modules, and geometry-only vector data. This profile was tested in 1992 in order to validate it. It will be submitted to the National Institute of Standards and Technology as an amendment to the SDTS.     

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.     

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.     

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: A Catalyst for Change

The Spatial Data Transfer Standard (SOTS), as a standard, is somewhat of a paradox. Standards help to establish order and promote stability. As such, SDTS serves both as a standard and a catalyst for change. Beyond being the first major geographic information systems(GIS) standard, SOTS has invoked—and continues to invoke—significant changes throughout federal organizations and other' organizations that interact with them. The changes inspired by SDTS focus attention on the importance of GIS standards. This importance, in turn, is the underlying force in creating a GIS standards infrastructure. The infrastructure provides a mechanism/process for developing, approving, and coordinating GIS standards in the federal, national, and international communities.     

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.     

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.     

Volunteered Geographic Information: A Bicycling Enthusiast Perspective

Mapping technologies have made considerable strides in recent decades. Global positioning systems (GPS), remote sensing satellites, Web-based mapping services, and geographic information systems (GIS) have facilitated the collection, distribution, analysis, and ultimately interaction with geospatial information. In particular, portable GPS have altered how individuals participate in mapping. Individuals can use GPS to collect tracings of their personal interactions with the environment. These interactions can then be uploaded to one of many available Web-based mapping services. Once uploaded, the geospatial data can be mapped and shared among the broader community of users. Such volunteered geographic information (VGI) exemplifies the conceptualization of an individual collecting, mapping, and sharing personal geographic information. This paper focuses on challenges surrounding VGI. To help place these challenges in a broader context, specialized Web services and GPS technologies developed for the bicycling community will serve as examples of the current status and future prospects of VGI.     

Mapping Population Distribution in the Urban Environment: The Cadastral-based Expert Dasymetric System (CEDS)

This paper discusses the importance of determining an accurate depiction of total population and specific sub-population distribution for urban areas in order to develop an improved "denominator," which would enable the calculation of more correct rates in GIS analyses involving public health, crime, and urban environmental planning. Rather than using data aggregated by arbitrary administrative boundaries such as census tracts, we use dasymetric mapping, an areal interpolation method using ancillary information to delineate areas of homogeneous values. We review previous dasymetric mapping techniques (which often use remotely sensed land-cover data) and contrast them with our technique, Cadastral-based Expert Dasymetric System (CEDS), which is particularly suitable for urban areas. The CEDS method uses specific cadastral data, land-use filters, modeling by expert system routines, and validation against various census enumeration units and other data. The CEDS dasymetric mapping technique is presented through a case study of asthma hospitalizations in the Bronx, New York City, in relation to proximity buffers constructed around major sources of air pollution. The case study shows the impact that a more accurate estimation of population distribution has on a current environmental justice and health disparities research project, and the potential of CEDS for other GIS applications.     

The TIGER System: Yesterday,Today, and Tomorrow

The TIGER System is many things to many people. At this juncture, the TIGER System has fulfilled the precensus geographic support functions for which the Geography Division designed it. During the next 18 months, the TIGER System will support a number of functions needed to complete the tabulation of the collected data and make those data useful to the numerous constituencies that carry out the myriad tasks that define our lives. Simultaneously with the use of the TIGER System to support the data tabulation and dissemination missions of the Census Bureau, work will be under way to define a framework for the future of this bold new product – and this future looks bright. If the TIGER System is to be judged truly useful outside the Census Bureau, similar planning will need to be going on in offices and institutions across America. This is true especially in the context of geographic information system (GIS) applications involving the digital products of the TIGER System and the demographic data products of the 1990 census.     

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 Network Perspective on Spatial Data Infrastructures: Application to the Sub-national SDI of Flanders (Belgium)

In order to provide a basis for quantitative and qualitative assessment of SDI-performance, a clear definition and a theoretical framework for SDI are needed. From the various definitions and frameworks of SDI available in the literature, the productional and the geographic information process perspective were selected, combined and extended. From the productional perspective, SDI-development is a dynamic process in which suppliers and users of spatial data interact to add value to the data by using them in applications and processes. The geographic information process perspective incorporates the "information acquisition – delivery – usage" chain. The extension proposed in this article leads to a network perspective on SDI. The nature of this perspective is described for the Flemish SDI. Its applicability to characterise and underpin the assessment of SDI is tested using a Social Network Analysis (SNA) focusing on the network structure parameters "density", "distance" and "centrality". The SNA confirms the applicability, usability and extensibility of the network perspective to characterize the SDI, to describe the data flows between stakeholders and to analyse the behaviour of the different (types) of stakeholders within the network. We conclude that SNA should likely be complemented by an impact analysis of different SDI setups on business processes which will provide a good basis for a holistic SDI-performance assessment.     

Bringing GEOSS Services into Practice: A Capacity Building Resource on Spatial Data Infrastructures (SDI)

Data discoverability, accessibility, and integration are frequent barriers for scientists and a major obstacle for favorable results on environmental research. To tackle this issue, the Group on Earth Observations (GEO) is leading the development of the Global Earth Observation System of Systems (GEOSS), a voluntary effort that connects Earth Observation resources world‐wide, acting as a gateway between producers and users of environmental data. GEO recognizes the importance of capacity building and education to reach large adoption, acceptance and commitment on data sharing principles to increase the capacity to access and use Earth Observations data. This article presents “Bringing GEOSS services into practice” (BGSIP), an integrated set of teaching material and software to facilitate the publication and use of environmental data through standardized discovery, view, download, and processing services, further facilitating the registration of data into GEOSS. So far, 520 participants in 10 countries have been trained using this material, leading to numerous Spatial Data Infrastructure implementations and 1,000 tutorial downloads. This workshop lowers the entry barriers for both data providers and users, facilitates the development of technical skills, and empowers people.     

The GIS/SA interface for substantive research(ers): A critical need

This paper is concerned with the intersection of GIS and spatial analysis, its accessibility for scientists who may be less methodologically oriented than others, and its use in substantive research driven by theoretical, conceptual, and empirical issues central to one's discipline. GIS/SA use in this manner has lagged considerably. The case is documented, that there may be shifts in this trend is noted, and suggestions for moving ahead more quickly are put forth. These include instructional efforts, software development, and substantive research that will provide a demonstration effect, guide, and direction for others.     

The habitation Model Trend Calculation (MTC): A new effective tool for predictive modeling in archaeology

ABSTRACT

The aim of this paper is to create and present a new archaeological predictive model via GIS, incorporating what archaeologists consider the most important criterion absent of similar past models, that of critical thinking. The new model suggested in this paper is named habitation Model Trend Calculation (MTC) and is not only integrates the archaeological questions with a critical view, but it can be easily adjusted, according to the conditions or the questions concerning the archaeological community. Furthermore, it uses new topographical and geomorphological indexes such as Topographical Index (TPI), Hillslope and Landform Classification that give a new sense of the topographical and geomorphological characteristics of the examined area; therefore this model is a more powerful tool compared to older models that did not use new topographical and geomorphological indexes. The success of the created model is checked as a case study in the region of Messenia, Greece during the Mycenaean era. The region of Messenia is considered as one of the most important Mycenaean regions of Greece due to the great number and the importance of Mycenaean sites identified. For the present paper, 140 habitation sites were divided into four hierarchical categories (centers, large villages, villages, and farms) based on the extent and the plurality of the tholos tombs that exist in the broader region and according to the hierarchical categorization used by the archaeologists who have studied the area. The new predictive model presented in this work can assist in solving a series of criticisms that have been expressed in the previous studies regarding such models. Additionally, in the case of Mycenaean Messenia, the model shows excellent results in relation to the habitats of the time.