Concepts Of Space And Time In Spatial Information Systems

Spatial information is always related to geographic space, i.e., large-scale space. This is the space beyond the human body, space that represents the surrounding geographic world. Within such space, we constantly move around, we navigate in it, and we conceptualize it in different ways. Geographic space is the space of topographic, land use/land cover, climatic, cadastral, and other features of the geographic world. Geographic information system technology is used to manipulate objects in geographic space, and to acquire knowledge from spatial facts.

Geographic space is distinct from small-scale space, or tabletop space. In other words, objects that are smaller than us, objects that can be moved around on a tabletop, belong to small-scale space and are not subject of our interest.

The human understanding of space, influenced by language and cultural background, plays an important role in how we design and use tools for the processing of spatial data. In the same way as spatial information is always related to geographic space, it relates to geographic time, the time whose effects we observe in the changing geographic world around us. We are less interested in pure philosophical or physical considerations about time or space-time, but more in the observable spatio-temporal effects that can be described, measured and stored in information systems.

Spatial information systems

The handling of spatial data usually involves processes of data acquisition, storage and maintenance, analysis and output. For many years, this has been done using analogue data sources, manual processing and the production of paper maps. The introduction of modern technologies has led to an increased use of computers and information technology in all aspects of spatial data handling. The software technology used in this domain is geographic information systems (GIS).

A general motivation for the use of GIS can be illustrated with the following example. For a planning task usually different maps and other data sources are needed. Assuming a conventional analogue procedure we would have to collect all the maps and documents needed before we can start the analysis. The first problem we encounter is that the maps and data have to be collected from different sources at different locations (e.g., mapping agency, geological survey, soil survey, forest survey, census bureau, etc.), and that they are in different scales and projections. In order to combine data from maps they have to be converted into working documents of the same scale and projection. This has to be done manually, and it requires much time and money.

With the help of a GIS, the maps can be stored in digital form in a database in world co-ordinates (meters or feet). This makes scale transformations unnecessary, and the conversion between map projections can be done easily with the software. The spatial analysis functions of the GIS are then applied to perform the planning tasks. This can speed up the process and allows for easy modifications to the analysis approach.

GIS, spatial information theory, and the Geoinformatics context

Spatial data handling involves many disciplines. We can distinguish disciplines that develop spatial concepts, provide means for capturing and processing of spatial data, provide a formal and theoretical foundation, are application-oriented, and support spatial data handling in legal and management aspects. Table 1 shows a classification of some of these disciplines. They are grouped according to how they deal with spatial information. The list is not meant to be exhaustive.

Table 1: Classification of disciplines involved in spatial analysis

Characteristics of disciplines

Sample disciplines

Development of spatial concepts

Geography

Cognitive Science

Linguistics

Psychology

Means for capturing and processing spatial data

Remote Sensing

Surveying Engineering

Cartography

Photogrammetry

Formal and theoretical foundation

Computer Science

Expert Systems

Mathematics

Statistics

Applications

Archaeology

Architecture

Forestry

Geo-Sciences

Regional and Urban Planning

Surveying

Support

Legal Sciences

Economy

The discipline that deals with all aspects of spatial data handling is called Geoinformatics. It is defined as:

Geoinformatics is the integration of different disciplines dealing with spatial information.

Geoinformatics has also been described as "the science and technology dealing with the structure and character of spatial information, its capture, its classification and qualification, its storage, processing, portrayal and dissemination, including the infrastructure necessary to secure optimal use of this information". It is also defined as "the art, science or technology dealing with the acquisition, storage, processing, production, presentation and dissemination of geoinformation."

A related term that is sometimes used synonymously with geoinformatics is Geomatics. It was originally introduced in Canada, and became very popular in French speaking countries. The term geomatics, however, was never fully accepted in the United States where the term geographical information science is preferred.

There is no clear-cut definition for GIS. Different people defined GIS according to capability and purpose for which it is applied. Few of the definitions are:

• "A computer - assisted system for the capture, storage, retrieval, analysis and display of spatial data, within a particular Organization" (Stillwell & Clarke, 1987).

• "A powerful set of tools for collecting, storing, retrieving at will, transforming and displaying spatial data from the real world" (Burrough,

• A GIS is also defined as follows (Aronoff, 1989):

- A GIS is a computer-based system that provides the following four sets of capabilities to handle geo-referenced data:

- data management (data storage and retrieval),

- manipulation and analysis, and

• "An internally referenced, automated, spatial information system".

• "A system for capturing, storing, checking, manipulating, analyzing and displaying data which are spatially referenced to the Earth".

• "An information technology which stores, analyses and display both spatial and non-spatial data".

• "A database system in which most of the data are spatially indexed, and upon which a set of procedures operated in order to answer queries about spatial entities in the database".

• "An automated set of functions that provides professionals with advanced capabilities for the storage, retrieval, manipulation and display of geographically located data".

• "A decision support system involving the integration of spatially referenced data in a problem solving environment".

• "A system with advanced geo - modeling capabilities".

Although the above definitions cover a wide range of subjects, the activities best refer to geographical information. Some times it is also termed as Spatial Information Systems as it deals with located data, for objects positioned in any space, not just geographical, a term for world space. Similarly, the term 'a spatial data' is often used as a synonym for attribute data (i.e. rainfall/ temperature/ soil chemical parameters/ population data etc.).

Frequently used technical terms in spatial data handling are:

• Geographic (or geographical) Information System (GIS),

• Geo-information System,

• Spatial Information System (SIS),

• Land Information System (LIS), and

• Multi-purpose Cadastre.

Geographic information systems are used by various disciplines as tools for spatial data handling in a geoinformatics environment.

Depending on the interest of a particular application, a GIS can be considered to be a data store (application of a spatial database), a tool- (box), a technology, an information source or a science (spatial information science).

Like in any other discipline, the use of tools for problem solving is one thing; to produce these tools is something different. Not all are equally well suited for a particular application. Tools can be improved and perfected to better serve a particular need or application. The discipline that provides the background for the production of the tools in spatial data handling is spatial information theory (or SIT).

Geographic information technology is used to manipulate objects in geographic space, and to acquire knowledge from spatial facts. Spatial information theory provides a basis for GIS by bringing together fields that deal with spatial reasoning, the representation of space, and human understanding of space:

Spatial reasoning addresses the inference of spatial information from spatial facts. It deals with the framework and models for space and time, and the relationships that can be identified between objects in a spatio-temporal model of real world phenomena.

Scientific methods for the representation of space are important for the development of data models and data structures to represent objects in spatial databases. Spatial databases are distinguished from standard databases by their capability to store and manage data with an extent in space and time (spatial data types).

The human understanding of space, influenced by language and culture, plays an important role in how people design and use GIS.

The theory is used for the design of high-level models of spatial phenomena and processes. They are then mapped into conceptual, logical and physical models of spatial databases. The database stands central in the geoinformatics environment. It is the database that holds the data; without it, no useful function can be performed. Data are entered into the database in input processes. Later, they are extracted from the database for spatial analysis and display.

The processes of data management, analysis and display are often supported by rules that are derived from domain experts. Systems that apply stored rules to arrive at conclusions, are called rule-based or knowledge-based systems. Those that support decision making for space-related problems are known as spatial decision support systems (or SDSS). They are becoming increasingly popular in planning agencies and management of natural resources.

All these activities happen in a social, economic and legal context. It is generally referred to as spatial information infrastructure. Everything within this infrastructure and all concepts of space and time in turn are shaped and determined by the cultural background of the individuals and organizations involved.

HISTORY OF GIS

The GIS history dates back to 1960 when computer based GIS have been used and their manual procedures were in life 100 years earlier or so. The initial developments originated in North America with the organizations such as US Bureau of the Census, The US Geological Survey and The Harvard Laboratory for computer graphics and Environmental Systems Research Institute (commercial). Canadian Geographic Information Systems (CGIS) in Canada, Natural Experimental Research Center (NREC), Department of Environment (DOE) and other notable organizations in U.K. were involved in early developments. The laboratory for Computer Graphics and Spatial Analysis of the Harvard Graduate School of Design and the State University of New York at Buffalo achieved worldwide recognition. Commercial agencies started to develop and offer GIS software. Among them were today's market leaders ESRI, Intergraph, Laserscan, Autodesk etc.

A sound and stable data structure to store and analyze map data became dominant in the early 1970 s. This has lead to the introduction of topology into GIS. Topology and the related graph theory proved to be effective and efficient tools to provide logically consistent two-dimensional data representations. Another significant break through occurred with the introduction and spread of personal computers in 1980s. It was possible to have a computer on the desk that was able to execute programs that previously could only be run on mainframe computers. At the same time minicomputers, and later, workstations became widely available. Relational database technology became the standard. Research on spatial data structures, indexing methods, and spatial databases made tremendous progress. The 1990's can be characterized as a period of the breakthrough of object-orientation in system and database design, recognition of geoinformatics as a professional activity, and spatial information theory as the theoretical basis for GIS. Potentiality of GIS is realized in the recent past and now it has become popular among many users for a variety of applications.

In India the major developments have happened during the last one-decade with significant contribution coming from Department of Space emphasizing the GIS applications for Natural Resources Management. Notable among them are Natural Resource Information System (NRIS), Integrated Mission for Sustainable Development (IMSD) and Bio-diversity Characterization at National Level. IIRS is also playing a major role in GIS

through education and training programs at the National and International level. Recently the commercial organizations in India have realized the importance of GIS for many applications like natural resource management, infrastructure development, facility management, business/market applications etc. and many GIS based projects according to the user organization requirements were developed.

GIS OBJECTIVES

• Maximize the efficiency of planning and decision making

• Provide efficient means for data distribution and handling

• Elimination of redundant data base - minimize duplication

• Capacity to integrate information from many sources

• Complex analysis/query involving geographical referenced data to generate new information.

For any application there are five generic questions a GIS can answer:

Location

Condition

Trends

Patterns

Modeling

Elements of A GIS:

What exists at a particular location?

Identify locations where certain conditions exist.

What has changed since?

What spatial pattern exists?

The GIS has been divided into four elements. They are hardware, software, data, and liveware. Table-2 gives complete details of different elements.

Table 2: Details of Elements of GIS

S. No.

Elements of GIS

Details

1.

Hardware

Type of Computer Platforms

Modest Personnel Computers

High performance workstations

Minicomputers

Mainframe computers

Input Devices

Scanners

Digitizers

Tape drivers

CD

Keyboard

Graphic Monitor

Output Devices

Plotters

Printers

2.

Software

Input Modules

Editing

MRP Manipulation/ Analysis Modules

Modeling Capability

3.

Data

Attribute Data

Spatial Data

Remote Sensing Data

Global Database

4.

Liveware

People responsible for digitizing, Implementing

using GIS Trained personnel

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