Geo-information
Cartography and GIS are increasing its role in many applications, in particular many info-mobility applications are based on LBS- Location Based Services. The main technical problem is the availability of GIS information on small and portable terminals by Internet network. The communication problem are solving by the W3C’s Mobile Access Activity that is working to ensure that the protocols and data formats of the Web provide an effective fit for all mobile devices. While the GIS applicable standard are managed in OpenGIS worldwide consortium. Until now the loss of the success of GIS is due to the low number of available end user applications. The situation is changing given that some specialized and mass market applications have been developed and the users are starting to appreciate them. The increase of the GIS utilization in the Cadastral Systems and in the cars terminals are two relevant examples. GIS services market is changing, so the GIS companies in order to increase their business must develop and offer new services and not only deliver maps to users. The project meets this market requirement.
Geographical Information Services are furthermore converging to open standards: a remarkable approach is the OpenGIS project and the GML (Geographical Markup Language).

OVERVIEW OF GEOGRAPHIC INFORMATION SYSTEMS

A geographic information system (GIS) is a computer-based tool for mapping and analyzing geographic phenomenon that exist, and events that occur, on Earth. GIS technology integrates common database operations such as query and statistical analysis with the unique visualization and geographic analysis benefits offered by maps. These abilities distinguish GIS from other information systems and make it valuable to a wide range of public and private enterprises for explaining events, predicting outcomes, and planning strategies. Map making and geographic analysis are not new, but a GIS performs these tasks faster and with more sophistication than do traditional manual methods.
We commonly think of a GIS as a single, well-defined, integrated computer system. However, this is not always the case. A GIS can be made up of a variety of software and hardware tools. The important factor is the level of integration of these tools to provide a smoothly operating, fully functional geographic data processing environment.

Components of a GIS

An operational GIS has a series of components that combine to make the system work. These components are critical to a successful GIS.
A working GIS integrates five key components:
Hardware
Hardware is the computer system on which a GIS operates. Today, GIS software runs on a wide range of hardware types, from centralized computer servers to desktop computers used in stand-alone or networked configurations.
Software
GIS software provides the functions and tools needed to store, analyze, and display geographic information. A review of the key GIS software subsystems is provided above.
Data
One very important component of a GIS is the data. Geographic data and related tabular data can be collected in-house, compiled to custom specifications and requirements, or occasionally purchased from a commercial data provider. A GIS can integrate spatial data with other existing data resources, often stored in a corporate DBMS. The integration of spatial data (often proprietary to the GIS software), and tabular data stored in a DBMS is a key functionality afforded by GIS.
People
GIS technology is of limited value without the people who manage the system and develop plans for applying it to real world problems. GIS users range from technical specialists who design and maintain the system to those who use it to help them perform their everyday work. The identification of GIS specialists versus end users is often critical to the proper implementation of GIS technology.
Methods
A successful GIS operates according to a well-designed implementation plan and business rules, which are the models and operating practices unique to each organization.
As in all organizations dealing with sophisticated technology, new tools can only be used effectively if they are properly integrated into the entire business strategy and operation.
Three basic types of spatial data models have evolved for storing geographic data digitally. These are referred to as :
- Vector
- Raster
- Image Data

Vector
Points – x,y co-ordinates representing individual points e.g. trees
Lines – sets of points representing linear features e.g. roads, rivers
Areas – closed set of lines such as woodlands or a city boundary
Vector model topology is characterised by:
- Connectivity – e.g. street or pipe networks
- Adjacency – adjacent buildings sharing common walls
- Containment – one area within another e.g. building inside land parcel

Raster
Raster model is the representation of spatial information with pixels.

Image Data
Image data is most often used to represent graphic or pictorial data. The term image inherently reflects a graphic representation, and in the GIS world, differs significantly from raster data. Most often, image data is used to store remotely sensed imagery, e.g. satellite scenes or orthophotos, or ancillary graphics such as photographs, scanned plan documents, etc. Image data is typically used in GIS systems as background display data (if the image has been rectified and georeferenced); or as a graphic attribute. Remote sensing software makes use of image data for image classification and processing. Typically, this data must be converted into a raster format (and perhaps vector) to be used analytically with the GIS.
Image data is typically stored in a variety of de facto industry standard proprietary formats. These often reflect the most popular image processing systems. Other graphic image formats, such as TIFF, GIF, PCX, etc., are used to store ancillary image data. Most GIS software will read such formats and allow the display of this data.

Functions of a GIS
The basic functions which a GIS can support are:
• data input
Data can be input to a GIS from various sources eg. Vector or raster digital maps, images of various formats, text files, RDBMS tables, GPS data etc. Most GIS’s support digitizing procedures as well, for the creation of digital layers from existing conventional maps.
• data storage
A large amount of spatial data and their related attributes can be stored in the geographical Data base of a GIS. This data can be also managed by either the internal or an external DBMS.
In fact, most GIS software provides an internal relational data model, as well as support for commercial off-the-shelf (COTS) relational DBMS. COTS DBMS are referred to as external DBMS. This approach supports both users with small data sets, where an internal data model is sufficient, and customers with larger data sets who utilize a DBMS for other corporate data storage requirements. With an external DBMS the GIS software can simply connect to the database, and the user can make use of the inherent capabilities of the DBMS. External DBMS tend to have much more extensive querying and data integrity capabilities than the GIS internal relational model. The emergence and use of the external DBMS is a trend that has resulted in the proliferation of GIS technology into more traditional data processing environments.
The relational DBMS is attractive because of its :
- simplicity in organization and data modelling.
- flexibility – data can be manipulated in an ad hoc manner by joining tables.
- efficiency of storage – by the proper design of data tables redundant data can be minimized.
- The non-procedural nature – queries on a relational database do not need take into account the internal organization of data.

• data transformation
Most GIS’s support advanced transformation utilities for transforming data from one format to another and from vector to raster and raster to vector models.
• data analysis
Analysis which can be performed on spatial data using a GIS tool include
Measurement distance, area, perimeter
Query spatial, attribute
Buffering inside, outside
Neighbourhood operations reclassification
Interpolation prediction
Surface analysis slope, aspect, viewsheds
Network analysis routes
supply and demand
Overlay
• data output
Outputs from a GIS system include: maps, surface visualisations, tables, lists, multimedia, animated map sequences.

State of the art and trends

MAPPING and Geographical Data

Prior to the late 1950s the analog map was the primary device or tool for storing, organizing, and displaying the locations of features on the earth’s surface. While geographic representation could certainly be achieved by means of drawings, text, and numerical arrays, the printed map was generally the medium of choice.
The evolution of GIS technology suddenly changed all this in two distinctively different ways. On one hand, cartographers saw computer technology as a means for producing traditional analog maps. This was called “automated” (or “computer” or “digital”) cartography. On the other hand, researchers, government administrators, business managers, earth scientists, military planners and developers, and others) saw computer technology as a tool for providing alternatives to printed maps. GIS technology would allow them to store, process, analyze, and display spatially distributed data in various forms, including but not limited to maps.
Researchers have found that map-derived digital data in a GIS can improve the accuracy of interpretation of remotely sensed data while remotely sensed data provides the ability to update map products in a more expeditious manner. The data produced by all these systems have a spatially referenced component.
Nowadays, there is a huge number of digital spatial data sets which have been developed by institutions, private companies or army services. These data sets are produced in various scales and characterized by various accuracy values. Accuracy and precision standards for the production of spatial digital data have also been defined by several organizations and institutions in Europe and USA. Thus, even though not a single international set of standards exists yet, some basic guidelines are available for the creation of reliable data sets and for the avoidance of gross errors in geographical data production.
In many cases data sets for GIS are initially generated from existing maps, but given the relative ease with which all digital data (if it is coordinate-based) can be combined, data sets can now be assembled from many diverse sources, including:
• Aerial photography,
• global positioning systems,
• electronic imaging (often from a remote sensing platform),
• newly created maps
There are currently several available digital spatial data sets for the Athens and Rome areas which have been developed by private companies and also by institutions and the army services from existing conventional maps in combination with ortho-rectified aerial- photographs. Most of these sets concern road network and building blocks. Detailed geocoding information is available for specific areas, even though has not been created in a systematic way.
The organization of the Olympic Games in Greece generated the need for the production of more detailed and more accurate spatial data. Thus campaigns have been organized by institutions and private companies for the creation of new data sets or the revision and improvement of the existing ones. Very high resolution satellite images are used as a new and more reliable source in combination with classical survey methods.
To anticipate the future nature and use of geographic data, it is important to understand the means by which this data is produced and processed. Trends on the production and use of digital maps are affected mainly by the following factors:
The new generation GIS packages and functionality allow more and more complicate and sophisticated analysis of spatial data. New thematic layers are required as inputs and new thematic maps derive as outputs.
Growing dependency on Geographic Information System technology and the evolution of positioning technologies (GPS, EGNOS/GALILEO, DGPS) has generated reasonable concern about the accuracy and precision of geospatial data.
Very high resolution satellite imagery (ie. IKONOS, QBIRD) provide a powerful alternative for the creation of large scale thematic layers which require less effort in time-consuming and costly field surveys.

Data Accuracy and Quality

The quality of data sources for GIS processing is becoming an ever increasing concern among GIS application specialists. With the influx of GIS software on the commercial market and the accelerating application of GIS technology to problem solving and decision making roles, the quality and reliability of GIS products is coming under closer scrutiny. Much concern has been raised as to the relative error that may be inherent in GIS processing methodologies. While research is ongoing, and no finite standards have yet been adopted in the commercial GIS marketplace, several practical recommendations have been identified which help to locate possible error sources, and define the quality of data.
Successful and operative use of infomobility applications depend to great extend on the geographic data quality and in particular on absolute and relative accuracy of data as defined below. The following review of data quality focuses on three distinct components, data accuracy, quality, and error.
• Accuracy
The fundamental issue with respect to data is accuracy. Accuracy is the closeness of results of observations to the true values or values accepted as being true. This implies that observations of most spatial phenomena are usually only considered to estimates of the true value. The difference between observed and true (or accepted as being true) values indicates the accuracy of the observations.
Basically two types of accuracy exist. These are positional and attribute accuracy.
• Positional accuracy is the expected deviance in the geographic location of an object from its true ground position. This is what we commonly think of when the term accuracy is discussed. There are two components to positional accuracy. These are relative and absolute accuracy. Absolute accuracy concerns the accuracy of data elements with respect to a coordinate scheme, e.g. UTM. Relative accuracy concerns the positioning of map features relative to one another.
For most geographic applications, relative accuracy is of greater concern than absolute accuracy. For example, most GIS users can live with the fact that their survey township coordinates do not coincide exactly with the survey fabric, however, the absence of one or two parcels from a tax map can have immediate and costly consequences.
However, for applications related to precise positioning like , absolute accuracy is very essential.
The geographical data included in these applications should necessarily be characterized by both high absolute and relative accuracy.
• Attribute accuracy is equally as important as positional accuracy.
One of the major problems currently existing within GIS is the aura of accuracy surrounding digital geographic data. Often hardcopy map sources include a map reliability rating or confidence rating in the map legend. This rating helps the user in determining the fitness for use for the map. However, rarely is this information encoded in the digital conversion process.
Often because GIS data is in digital form and can be presented using various zoom factors (usually higher than those of the initial source), it is considered to be totally accurate. In reality, a buffer exists around each feature which represents the actual positional location of the feature. For example, data captured at the 1:20,000 scale commonly has a positional accuracy of +/- 20 metres. This means the actual location of features may vary 20 metres in either direction from the identified position of the feature on the map. Considering that the use of GIS commonly involves the integration of several data sets, usually at different scales and quality, one can easily see how errors can be propagated during processing.
• Data quality
Quality can simply be defined as the fitness for use for a specific data set. Data that is appropriate for use with one application may not be fit for use with another. It is fully dependant on the scale, accuracy, and extent of the data set, as well as the quality of other data sets to be used.
Two sources of error, inherent and operational, contribute to the reduction in quality of the products that are generated by geographic information systems. Inherent error is the error present in source documents and data. Operational error is the amount of error produced through the data capture and manipulation functions of a GIS. Possible sources of operational errors include :
• mislabelling of areas on thematic maps;

• misplacement of horizontal (positional) boundaries
• human error in digitizing
• classification error
• GIS algorithm inaccuracies, and
• human bias.
While error will always exist in any scientific process, the aim within GIS processing should be to identify existing error in data sources and minimize the amount of error added during processing. Because of cost constraints it is often more appropriate to manage error than attempt to eliminate it. There is a trade-off between reducing the level of error in a data base and the cost to create and maintain the database.
An awareness of the error status of different data sets will allow us to make a subjective statement on the quality and reliability of a product derived from GIS processing.

Geographic Information Systems

The field of digital geographic data processing is now over two decades old. Over the past several years, it has grown dramatically, not only in terms of the numbers of individuals involved and the variety of applications addressed, but also in terms of the sophistication of the applications addressed.
The field has not reached its maturity, it is yet in a developing stage. New capabilities are discovered, more attention is being paint in this technology and heightened expectations can be faced.
Much of this recent advancement in the field of geographic data processing can be attributed to more general trends in the broader field of computing. As we move from the processing of numbers to words and to pictures (such as maps), certain patterns in this evolution are perceptible, perhaps most notably a shift from highly centralized computing to more decentralized but still highly integrated networks.
The general trend of GIS development seems to indicate that it will continue to become:
• easier to use
• more intuitive
• more analytic
• more embedded within a variety of technologies.
While the de facto operating system standard has been UNIX, the Windows NT/2000/XP operating system is emerging as a serious and robust alternative. This is especially prevalent with organizations wishing to integrate their office computing environment with their GIS environment. This trend is closely associated with the development of 32/64-bit micro-computers. SQL (Standard Query Language) has become the standard interface for all relational DBMS. The ability to customize user interfaces and functionality through Application Programming Interfaces (API) and macro languages. The major development in GIS technology over the past five years has been the ability to customize the GIS for specific needs. The development of GIS modules for mobile devices is also quite new. A few number of GIS packages have already included software modules for mobile devices running under Windows CE and other analogous operating systems.
One way to characterize the development in GIS technology is in terms of the three basic components of a GIS. Like those of any information-processing system, these include :
• Data
• A means of processing those data
• A mechanism to control that processing and to present processing results. ( i.e. User Interface)

Data
The data that tend to be processed by geographic information systems describe phenomena not only in terms of “what” and “when”, but mainly “where”. The magnitude of this locational component may be measured in units that range from centimeters to thousands of kilometers, and the ability to transform data from one scale to another and from one projection system to another is an important part of the geographic data processing. This is not simply a matter of changing the size of a particular graphic product, but a matter of moving accurately between data bases with efficiency and consistency.
The way in which geographic data are organized in a GIS can generally be expressed in terms of the way in which facts pertaining to what (theme), when (time), and where (location) are respectively either held constant, allowed to vary in a controlled manner, or measured. Most traditional maps record theme as a function of location at a constant time.
Data used in GIS have also traditionally been organized in this manner. Recently, however, new organizational schemes have begun to emerge.
A number of GIS have moved from location-oriented schemes to feature-oriented structures that record location as a function of theme at a constant point in time. Some systems are also beginning to address the temporal dimension of data as more than a constant. Thus, the traditional “map” format is becoming just one of many alternative ways to organize geographic data.
The ability to easily reconfigure data and to flexibly associate any one piece of information with others is coming to be regarded as a standard feature of any data management system.
The way in which geographic data are actually represented (stored, manipulated, and displayed) in a GIS may also vary from one system to another. Most of this variation relates not so much to the representation of what or when as where. Some encoding schemes associate theme and location on an atomistic basis. They refer to elemental pieces or “atoms” of cartographic space.
Other data encoding schemes are more holistic in nature. They associate theme and location by way of cartographic “wholes.” Raster (gridded image) and vector (line drawn) data structures are representatives of these two schemes, with atomic grid cells and holistic sets of points, lines, and polygons.
The distinction is beginning to fade, however, as raster resolution improves and as the ability to convert from one form to the other becomes routine.

Data processing
In terms of the ways in which these data are processed, GIS technology for many years was at a point where data are modeled after traditional techniques. Though the ability to do more work more rapidly and more economically is something we have come to expect, the new technology was most often used not to do new and different things but merely to do familiar things better. This process, however, is also changing. We are rapidly approaching a time when the GIS as a primary processor of geographic data is no longer what traditionally was, but a technology which offers new methods for elaborating and analyzing geographical data for the creation of a new generation of thematic layers and synthetic maps and for the provision of new services to the public and the private sector.
The data-processing capabilities of a GIS can nonetheless still be characterized in terms of four major types of traditional activity. They include data preparation, data interpretation, and data presentation and programming.
The data preparation capabilities of a GIS are those that provide for the acquisition, encoding, storage, and routine maintenance of geographic data. These may range from field investigations to digitizing to the reformatting of data.
The data interpretation capabilities of a GIS are those that provide for the transformation of data into information. This transformation generally involves a process in which facts of a general nature and potential utility (i.e., data) are translated into facts of a more specialized nature and actual utility (i.e., information) in answering questions, making decisions, or otherwise solving problems. For many applications, map reading has been replaced by interactive measurement, queries, and display functions.
The interpretative process typically involves both objective measurement and subjective judgment to transform facts, relationships, and/or meanings from an implicit to an explicit form. Interpretation of vegetation types, for example, might bring out facts pertaining to ecological characteristics. Interpretation of a topographic surface might rely on geometric relationships to infer a drainage pattern.
The data presentation capabilities of a GIS are those that provide for communication of facts to a general audience. This may involve maps, charts, reports, statistics, animations, and so on. Here, too, recent developments have been remarkable, and most current needs are generally being met.
Advances in this area, however, continue to be made with an increasing emphasis on visualization and the use of sound, motion, and whole-environment simulation.
It is the orientation toward data interpretation that distinguishes geographic information systems from other types of automated mapping systems. While mapping systems are primarily concerned with data preparation and presentation, the GIS is more concerned with data interpretation associated with on-the-ground applications. As the GIS user community has become more and more sophisticated in its ability to prepare and present its digital data, attention has now begun to focus on data interpretation and the techniques by which spatial phenomena can be modelled.
Modelling applications may range from land-use planning and environmental science to navigation and marketing.
One way to characterize their range is to draw a broad distinction between descriptive and prescriptive models. While the former deal with the realm of what is (e.g., landscape ecology or economic analysis), the latter deal with the various arts that focus on what should be (e.g., natural resource management or transportation planning).
Modelling capabilities in both of these generic areas are becoming more sophisticated and more accessible. They are becoming established tools for determining the capability or suitability of land for different purposes.
Perhaps the most notable trends are toward increasing dynamic visualization (i.e., simulated movement over time and/or space) and artificial intelligence (e.g., natural language interfaces, learning, and a mechanized ability to draw inferences for later use).
The programming capabilities of a GIS are those that affect the way in which a system is operated in general.
These are capabilities associated with user interaction, program execution, error handling, and so on. Development work in this area involves concerns that are common to all types of computing such as security, large-volume data handling, multiple and concurrent access to common data bases, updating, and data management in general.

User Interface
A third component of a GIS is its capability for user interaction. GIS user interfaces become more and more friendly offering new ways and tools for user interaction, requiring less effort by the user. Most of GIS packages include high level programming tools which allow the customization of the User Interface according to the specific user requirements. End-users feel more familiar with this technology than in the past since data input and analysis can be performed in a comprehensive and easy way.