Introduction to Geographic Information Systems (GIS)

1. Introduction to Geographic Information Systems (GIS)
Understanding the Basics and Applications

2. Learning outcomes:-
• Introduction to GIS
• Components of GIS
• GIS Data Types
• Applications of GIS
• Software Involved in GIS

3. Introduction to GIS
• Definition: GIS is a system designed to capture, store, manipulate,
analyze, manage, and present spatial or geographic data.
Importance:
GIS is essential because it allows us to understand geographic data.
(Spatial patterns, relationships, and trends)
History:
The evolution of GIS can be traced back to early cartography and
manual map overlay techniques.

4. Evolution of GIS
Early Developments:
Before the advent of computers, maps were created manually using
techniques like cartography and map overlay.
• labor-intensive & limited in their analytical capabilities.
Emergence of Computerized GIS:
With the introduction of computers, GIS evolved into digital mapping
and database systems.
• The storage and manipulation of spatial data in electronic formats,
making analysis more efficient.
Modern GIS: Combined with
Remote sensing, GPS, and spatial analysis tools.
Remote sensing is the acquiring of information from a distance.

5. Components of GIS

6. Software Components
• ArcGIS: Developed by Esri, ArcGIS is one of the most widely used
GIS software packages. It consists of multiple modules, including
ArcMap for traditional desktop GIS
• QGIS: is an open-source GIS software known for its user-friendly
interface and extensive plugin ecosystem. It provides a wide range
of features for data visualization, analysis, and editing.
• GRASS GIS: is a free and open-source software suite for geospatial
data analysis and management. It offers advanced capabilities for
raster and vector data processing, as well as a command-line
interface for scripting and automation.
• Google Earth: is a web-based mapping service that allows users to
explore geographic data in a 3D virtual environment.

7. Data Components
• Spatial Data Types: Spatial data represents the geographic location
and shape of features on Earth's surface. It can be categorized into
vector data (points, lines, polygons) and raster data (grids of cells).
• Attribute Data: Attribute data consists of descriptive information
associated with spatial features. This can include attributes such as
population density, land use classification, or soil types.
• Sources of GIS Data: Remote sensing satellites, aerial surveys, GPS
devices, field surveys, and government agencies.

8. Data Components

9. Vector Data:
• Points: Specific locations on Earth's surface, such as landmarks,
buildings, or sampling sites. They are commonly used to store
discrete data, such as the location of a city or the position of a tree.
• Lines: linear features, such as roads, rivers, or pipelines. They are
used to represent features that have length but negligible width,
such as transportation networks or utility lines.
• Polygons: Areas or regions on Earth's surface, such as land parcels,
administrative boundaries, or land cover types. They are used to
delineate boundaries and represent features with defined
boundaries and shapes.

10. Raster Data:
• Grid Structure: Organized into a grid of cells, with each cell
representing a unit of space on Earth's surface. (Continuous
phenomena, such as elevation or temperature, across a landscape)
• Pixel Values: Each cell in a raster dataset stores a value
representing a specific attribute or phenomenon. For example, in a
digital elevation model (DEM), each cell stores elevation data,
while in a land cover classification raster, each cell stores
information about the land cover type present at that location.
• Applications: Raster data is commonly used in remote sensing,
digital terrain modeling, land cover mapping, and environmental
modeling.

11. GIS Data Formats:
• Shapefiles: Shapefiles are a common vector data format used in
GIS. They consist of multiple files (.shp, .shx, .dbf, etc.)
• GeoTIFF: is a raster data format that allows for the embedding of
georeferencing information within the image file. This makes it
possible to accurately locate and display raster data within a GIS
environment.
• KML (Keyhole Markup Language): KML is an XML-based file format
used for representing geographic data in Google Earth and other
mapping applications.
• GeoJSON: is a lightweight data interchange format used for
encoding geographic data structures. It is commonly used for web
mapping applications.

12. Thank you