Unit-9 :Geographical Information System-GIS (Notes of TU BSc. 4th Year Computer Science)

Geographical Information System (GIS)

Syllabus : Definition of GIS and Remote Sensing; Components of GIS; Map Projections: Spatial and Non- spatial Data; Data Model and Input, Data Analysis and Output; Remote Sensing Applications: Agriculture, Forestry, Land Use / Land Cover Mapping, Water Resources, Snow and Glacier, Wetland Management 

GIS

A GIS is a computer based tool for mapping and analyzing feature events on earth and space. GIS integrates common database operations such as query and statistical analysis with maps.

Simply, we can say that GIS is an integrated set of hardware and software tools used for the manipulation and management of geographical data and related attribute data. GIS performs map making and geographic analysis faster and with more sophistication than traditional manual   methods. Some advantages of GIS are:

1. Improved decision making - Decisions are made easier because specific and detailed information is presented about one or more locations.
2. Reduced costs and increased efficiency : Route of delivery can be optimized with the help of GIS which saves time.
3. Improved communication : Communication in the visual format is easily understood by all.
4. Easy record keeping : Geographical changes are easily recorded by GIS for those responsible for recording the change.
5. Managing geographically : Knowing what is and when will occur in geographic space in order to plan a course of action.

Remote Sensing

Art and science of making measurement of the earth using sensors on airplane or satellites is called remote sensing. Sensors collect data in the form of images and provide specialized capabilities for manipulating, analyzing and visualizing those images. Remote sensed imageries integrated within a GIS. RADAR and LiDAR are examples of active remote sensing. Film photography, infrared, charge couple devices, etc. are examples of passive remote sensing.

Passive sensors gather radiation that is emitted or reflected by the object or surrounding.

Active sensors emits energy in order to scan objects and areas whereupon a sensor that detects and measures the radiation that is reflected or backscattered from the target.

Who uses Remote Sensing and why?

1. Geographer - to look changes on earth’s surface that need to be mapped.
2. Forester - for information about what types of trees are growing.
3. Environmentalist - who wants to detect, identify and follow movement of pollutants such as oil sticks on oceans.
4. Geologist - who is interested in finding valuable minerals. 
5. Farmers - for keeping eye on how crops are growing.
6. Ship captain - for finding routes.

Components of GIS

The different components of GIS are:

1. Hardware
2. Data
3. People
4. Methods
5. Software

a) Hardware

It is the computer on which a GIS operates. Software runs an a wide range of hardware types, from centralized computer servers to desktop computers used in stand alone or networked configurations. 

b) Data

It is most important and often most expensive component of GIS. Geographic data which is comprised of geographical features and their corresponding attribute information is entered into a GIS using a technique called digitizing. Process involves digitally encoding geographic features such as buildings, roads or country boundaries.

c) People

Real power of GIS comes from the people who use them. GIS is being used by people in many different fields as a tool that enables them to perform their jobs more effectively. Police use GIS to solve crime, teachers use GIS to teach lessons in geography, etc.

d) Methods

A successful GIS operators according to a well designed implementation plan and business rules, which are the models and operating practices unique to each organization.

e) Software

It provides functions and tools needed to input and store geographic information. All GIS software packages rely on an underlying database management system for storage and management of the geographic and attribute data.

The functional components of GIS are:

1. Map (Data input system)
2. Data Storage and Retrieval System
3. Data Manipulation and Analysis System
4. Presentation
5. Data Output System

Map Projections : Spatial and Non-Spatial Data

As GIS is based on data, hence there must be a data model that has to be followed to standardize procedure. They are:

1. Spatial data models - Spatial data describes absolute and relative location of a geographic features and is classified as  (a)Raster Data  (b)Vector Data  (c)Image Data. A data model is a way of defining and representing real world surfaces and characteristics in GIS.
2. Attribute data or non-spatial data - Attribute data describes the characteristics of the spatial features which can be quantitative or qualitative in nature.

Data Models

Spatial Data Model

1) Vector Data Model: It uses discrete points, lines or areas corresponding to discrete objects with name or code number of attributes.

Advantages:

• Data can be represented at its original resolution and form without generalization.
• Graphic output is usually more aesthetically pleasing.
• Accurate geographic location of data is maintained.
• Since most data (eg. Hard copy maps) is in vector form, no data conversion is required.
• Allows for efficient encoding of topology, and as a result more efficient operations that require topological informations.

Disadvantages:

• Location of each vertex needs to be stored explicitly.
• For effective analysis, vector data must be converted into topological structures.
• Topology is static and any updating or editing of the vector data requires rebuilding of the topology.
• Algorithms for manipulative and analysis function are complex and may be processing intensive.
• Often this inherently limits the functionality of large data sets.

2) Raster Data Model: It is a regular grid of cells divided into rows and columns. An element of the  grid cell is to called a pixel (picture cell).

Advantages:

• It is a simple data structure.
• It has the ability to represent continuous surfaces and performs surface analysis.
• The ability to uniformly store points, lines, polygons and surfaces.
• The ability to perform fast overlays with complex database or sets.
• Also compatible with digital satellite imagery.

Disadvantages:

• There can be spatial inaccuracies due to limits imposed by raster data set cell dimension.
• Raster datasets are potentially very large. Resolution increases as the size of cells decreases. Thus cost and disk space used also increases.
• There is also a loss of precision that accompanies restructuring data to a regularly spaces raster cell boundary.
• Raster maps normally reflects only one attribute or characteristic for an area.

Raster	Vector
1) Simple data structure.	More complex structure.
2) Overlay operations are easily and effectively implemented.	2) Are more difficult to implement.
3) High spatial variability is efficiently represented in a raster format.	3) Representation of high spatial variability is inefficient.
4) Raster data structure is less compact.	4) Vector provides more compact data structure.
5) Topological relationships are more difficult to represent.	5) Provides efficient encoding of topology.
6) Manipulation and enhancement of digital images can be effectively done.	6) Cannot be effectively done in the vector domain.

Non-spatial data (Attribute Data Models)

Attribute data is information appended in tabular format to spatial features. A separate data model is used to store and maintain attributes data for software.

Data Input

Data Input Techniques

The input of attribute data is usually quite simple. The discussion of data input techniques will be limited to spatial only. There are at least 4 basic procedures for inputing spatial data in GIS.

1. Manual Digitizing - While considerable work has been done with newer technologies, the overwhelming majority of GIS spatial data entry is done by manual digitizing. The coordinates are recorded in a user defined coordinate system or map projection. Latitude and longitude is most often used. The ability to adjust or transform data during digitizing from one projection to another is a desirable function of the GIS software. Numerous functional techniques exist to aid the operator in the digitizing process.
2. Automatic Scanning - A variety of scanning device exists for the automatic scanning or capture of spatial data. We can capture spatial features from a map at a rapid rate. Large data capture work are done using scanning technology. Scanners are generally expensive to acquire and operate.
3. Coordinate Geometry - The input of spatial data involves the calculation and entry of coordinate geometry (CoGo) procedures. This input technique is very costly and labor intensive and is rarely used for natural application in GIS. It is more appropriate for land record measurement.
4. Conversion of Existing Digital Data - Conversion of existing digital data is  being increasingly popular. A variety of spatial data including digital maps are openly available from a wide range of government and private sources. The most common digital data to be used in a GIS is data from CAD systems. A number of data conversion programs exists, mostly from GIS software vendors to transform data from CAD to a raster/vector format.

Data Source

Two types of data are input into a GIS, spatial and attribute data. The data input process is the operation for encoding both types of data into the GIS database formats. A wide variety of the data source exists for both spatial and attribute data. 

The most common general source for spatial data are:

1. Analogue maps
2. Imageries
3. Global positioning system
4. Statistical data
5. Existing digital data files

Existing hardcopy maps provide the most popular source for GIS project.

Data Analysis

Geographical analysis reveals new or previously unidentified relationships within and between data sets, thus increasing our understanding of the real world. Geographical analysis module usually contains 4 important function:

1. Selection is a simple operation
2. Manipulation has to do with aggregation, buffering, overlaying and interpolation.
3. Exploration is the 1st step in discovering any kind of pattern or cluster in a data set.
4. Confirmation can be seen as a tool for estimation of process models, stimulation and forecasting.

Types of GIS analysis

1. Spatial measurements: Spatial measurements can be the distance between two points, the area of a polygon or the length of a line or boundary.
2. Information retrieval: With a GIS we can point at a location, object or area on the screen and retrieve recorded information about it.
3. Searches by attribute: As most GIS systems are simply built on the existing capabilities of a database system, searches by attribute are thus controlled by the capabilities of database manager.
4. Searches by geography: GIS spatial retrieval is the generating maps which allows searching for information visually and highlights the results.
5. The query interface: User must interact with the data in appropriate way. To do that we need the query interface.
6. Spatial overlay: The way to identify spatial relationships is through the process of spatial overlay.
7. Boundary analysis: It is often referred to as districting which helps define regions according to certain criteria.
8. Buffer Analysis: Used for identifying areas surrounding geographic features.
9. Neighborhood operations: Can evaluate the characteristics of the area surrounding a specific location.

Data Output

The operation of presenting results of data analysis in a form that is understandable to a user, or in a form that allows data transfer to another computer system is called data output.

Remote Sensing Applications

Can be useful and employed in almost area. Some major areas are,

1. Agriculture : Satellite and airborne images are used as mapping tools to classify crops, examine their health and viability and monitor farming practices. Agriculture application of remote sensing includes crop type classification, crop condition assessment, crop yield estimation, mapping of soil management practices, etc.
2. Forestry : Includes reconnaissance mapping, commercial forestry and environmental monitoring, etc. Objectives to be met by national forest/environment agencies include forest cover updating, depletion monitoring and measuring biophysical properties of forest stands, forest cover type, etc.
3. Land cover and land use : Resource managers involved in parks, oil, timber and mining companies are concerned with both land use and cover, as are local resource inventory or natural agencies. Land use application of remote sensing include natural resource management, wildlife habitat protection, routing and logistic planning for seismic/exploration/resource extraction activities, etc.
4. Hydrology or water resources : Offers a synoptic view of the spatial distribution and dynamics of hydrological phenomena. Examples of hydrological applications includes wetlands mapping and monitoring, soil moisture estimation, measuring snow thickness, flood mapping and monitoring, glacier dynamics monitoring, irrigation scheduling, etc.
5. Snow and Glacier : The snow bound areas in the Himalaya lie at high altitudes where the terrain is rugged and inaccessible which causes the conventional methods of study not only difficult but hazardous as well. Remote sensing techniques, therefore, have a vital role to play in these studies for quick results with much less cost. Visual interpretation of Landsat imagery and use of aerial photographs for glacier inventory is facilitating in snow and glacier study.
6. Wetland management : To better manage and conserve wetland resources, we need to know the distribution and extent of wetlands and monitor their dynamic changes. Wetland maps and inventories can provide crucial information for wetland conservation, restoration, and management. Geographic Information System (GIS) and remote sensing technologies have proven to be useful for mapping and monitoring wetland resources.