Geographic Information System or GIS is no doubt the most effective and fastly growing domain in the last decade. After the introduction of Googlemaps , Google earth , bing maps and other related web/desktop based crowed sourced GIS systems , the role of the intelligent mapping system and the availability of the geospatial data at the required time is the dire need of today’s fast and challanging life. This puts a ever required need to have an executive introduction to Geographic Information System (GIS).

Those who are involved in the early days of GIS based systems , can appreciate the fact that the current progress of the GIS solutions have a major impact on our life. And now every person is some how utilizing or contributing into the GIS systems. Like the use of Google Maps for determination of the traffic condition on the particular road. Google maps has introduced the nice feature of the traffic layer that provides you the information about the road/traffic conditions in near real time by collecting the information from the user’s mobile that have and are


traveling on the road while being assisted from the positioning technologies like GPS, GLONASS e.t.c.

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.

Before we go into the minute details of the GIS , let us first take a look at what exactly GIS acronym is used for. We will look at a very basic level of information helping to develop the understanding of the novice user regarding GIS.  

What does GIS stand for?

There are two commonly used areas for which GIS as a acronym is mostly used. One is “Geographic Information Science” and the other one is “Geographic Information System“. No doubt the most common understanding and meaning taken from GIS is the lateral one. However we are doing to look at the both areas very briefly.

GIS is a system for inputting, storing, manipulating, analyzing, and reporting Geospatial data.

Geographic Information Science

It is the science concerned with the systematic  and automatic processing of spatial data and information with the help of computers. It is also known as the theory behind how to solve spatial (related to Space , can be GeoSpatial or hyperspatial) problems with computers. Geographic Information Science actually represents a framework for using information theory, spatial analysis and statistics, cognitive understanding, and cartography.

Geographic Information System 

It focuses on the processes and methods that are used to sample, represent, manipulate and present information about the world. It is a system designed for storing, analyzing, and displaying spatial data. It is the use of hardware, software, people, procedures, and data.

GIS is an organized collection of computer hardware, software, geographic-data,procedures, and personnel designed to handle all phases of geographic data- capture, storageanalysis, query, display, and output.

Literal Definition Of GIS

Let us take a look at the literal defination of the terminolgy “GIS” ,

  • Geographic relates to the surface of the earth.
  • Information is a knowledge derived from study, experience, or instruction.
  • System is a group of interacting, interrelated, or interdependent elements forming a complex whole.
  • Science is the observation, identification, description, experimental investigation, and theoretical explanation of phenomena.

Functions of GIS

GIS provides facilities for data capture, data management, data manipulation and analysis, and the presentation of results in both graphic and report form.The ability to incorporate spatial data, manage it, analyze it, and answer spatial questions is the distinctive characteristic of geographic information systems.The most commonly employed functions of the GIS are the three that are specified below:

  •  Data collection / Capture data

A data input subsystem allows the user to capture, collect, and transform spatial and thematic data into digital form. The data inputs are usually derived from a combination of hard copy maps, aerial photographs, remotely sensed images, reports, survey documents, etc.

  •   Data storing, processing & analysis

1. Store data
2. Query data
3. Analyze data

The data storage and retrieval subsystem organizes the data, spatial and attribute, in a form which permits it to be quickly retrieved by the user for analysis, and permits rapid and
accurate updates to be made to the database. This component usually involves use of a
database management system (DBMS) for maintaining attribute data. Spatial data is usually encoded and maintained in a proprietary file format.The data manipulation and analysis subsystem allows the user to define and execute spatial and attribute procedures to generate derived information. This subsystem is commonly thought of as the heart of a GIS, and usually distinguishes it from other database information systems and computer-aided drafting (CAD) systems.

  • Output production

1. Display data for visualization
2. Produce output on some printed format

The data output subsystem allows the user to generate graphic displays, normally maps, and tabular reports representing derived information products.

Basic Elements Of GIS

These are the infact most important elements of GIS based systems that are to be taken into serious consideration when you are going for the GIS based solutions or the development of subsequent system.

  • People

People are the most important part of a GIS. They define and develop the procedures used
by a GIS. They can overcome shortcoming of the other 4 elements (data, software, hardware,
procedure), but not vice-versa.

  • Data

Data is the information used within a GIS . Since a GIS often incorporates data from multiple sources, its accuracy defines the quality of the GIS. GIS quality determines the types of questions and problems that may be asked of the GIS.

  • Software

It encompasses not only to the GIS package, but all the software used for databases, drawings,
statistics, and imaging. The functionality of the software used to manage the GIS determines the type of problems that the GIS may be used to solve. The software used must match the needs and skills of the end user. Example of some Popular Vector-based GIS are  ArcGIS (ESRI)ArcViewMapInfo. Some of the popular Raster-based GIS are Erdas Imagine (Leica)ENVI (RSI)ILWIS (ITC)IDRISI (Clark Univ) .

  •  Hardware

The type of hardware determines, to an extent, the speed at which a GIS will operate. Additionally, it may influence the type of software used. To a small degree, it may influence the types/ personalities of the people working with the GIS.

  • Procedures/Methods

The procedures used to input, analyze, and query data determine the quality and validity of the final product. The procedures used are simple the steps taken in a well defined and consistent method to produce correct and reproducible results from the GIS system.

Types Of GIS Data and Spatial Model

There are basically two data types namingly ,  Spatial and Attribute data. The spatial data model contain the vector and the raster . Images that are geo-rectified are also considered as the part of the data models to employed in the GIS.  The Spatial data model describes the absolute and relative location of geographic features. The Attribute Data model describes characteristics of the spatial features. These characteristics can be quantitative and/or qualitative in nature. Attribute data is often referred to as tabular data.

  • Vector

In the vector data model, various features on the earth are represented as:
1. Points
2. Lines
3. Polygons

All spatial data models are approaches for storing the spatial location of geographic features in a database. Vector storage implies the use of vectors (directional lines) to represent a geographic feature. Vector data is characterized by the use of sequential points or vertices to define a linear segment. Each vertex consists of an X coordinate and a Y coordinate. Vector lines are often referred to as arcs and consist of a string of vertices terminated by a node. A node is defined as a vertex that starts or ends an arc segment. Point features are defined by one coordinate pair, a vertex. Polygonal features are defined by a set of closed coordinate pairs. In vector representation, the storage of the vertices for each feature is important, as well as the connectivity between features, e.g. the sharing of common vertices where features connect. Several different vector data models exist, however only two are commonly used in GIS data storage.

1. Vector topologic data structure

The topologic data structure is often referred to as an intelligent data structure because spatial relationships between geographic features are easily derived when using them. Primarily for this reason the topologic model is the dominant vector data structure currently used in GIS technology. Many of the complex data analysis functions cannot effectively be undertaken without a topologic vector data structure.

 2. CAD-data structure.

This structure consists of listing elements, not features, defined by strings of vertices, to define geographic features, e.g. points, lines, or areas. There is considerable redundancy with this data model since the boundary segment between two polygons can be stored twice, once for each feature. The CAD structure emerged from the development of computer graphics systems without specific considerations of processing geographic features. Accordingly, since features, e.g. polygons, are self-contained and independent, questions about the adjacency of features can be difficult to answer. The CAD vector model lacks the definition of spatial relationships between features that is defined by the topologic data model.

  • Raster

In the raster data model, a geographic feature like land cover is represented as single square cells. Raster data model commonly employees images that are geocoded . Each pixel or set of pixels can be related to the purticular geographic feature on earth. Raster data models incorporate the use of a grid-cell data structure where the geographic area is divided into cells identified by row and column. This data structure is commonly called raster. While the term raster implies a regularly spaced grid other tessellated data structures do exist in grid based GIS systems. In particular, the quadtree data structure has found some acceptance as an alternative raster data model.The size of cells in a tessellated data structure is selected on the basis of the data accuracy and the resolution needed by the user. A raster data structure is in fact a matrix where any coordinate can be quickly calculated if the origin point is known, and the size of the grid cells is known. Since grid-cells can be handled as two-dimensional arrays in computer encoding many analytical operations are easy to program.

  • Attribute

Attribute values in a GIS are stored as relational database tables.Each feature (point, line, polygon, or raster) within each GIS layer will be represented as a record in a table.

Important Geographic Data Features Types

All geographic features on the earth’s surface can be characterized and defined as one of three
basic feature types. These are points, lines, and polygons.

  • Point data exists when a feature is associated with a single location in space. Examples of point features include a fire lookout tower, an oil well or gas activity site, and a weather station.
  • Lines or Linear data exists when a feature’s location is described by a string of spatial coordinates. Examples of linear data include rivers, roads, pipelines, etc.
  • Polygon data exists when a feature is described by a closed string of spatial coordinates. Polygonal data is the most common type of data in natural resource applications. Examples of polygonal data include forest stands, soil classification areas, administrative boundaries, and climate zones. Most polygon data is considered to be homogeneous in nature and thus is consistent throughout.

Every geographic entity/phenomenon , in principle can be represented by either a point, line, and/or an polygon.