Course Content
Course Introduction
This beginner-friendly course provides a comprehensive introduction to Geographic Information Systems (GIS) using the free and open-source software QGIS. Learn fundamental GIS concepts, data visualization, spatial analysis, and create your own maps. Perfect for students, researchers, and anyone looking to explore the world through data. Enroll now and start your GIS journey with QGIS!
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Course Outline
00:48
Introduction to GIS Concepts
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What is GIS?
04:05
GIS Components
04:01
GIS Applications
05:56
GIS Data Types
07:20
GIS Data Sources
03:35
Coordinate Reference Systems
10:33
Getting Started with QGIS
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Download and Install QGIS
05:47
Introduction to QGIS interface
07:57
Saving QGIS Projects
01:40
Working with Spatial Data – Vector Layers
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Downloading Geospatial Data – Point Layer
06:06
Loading GIS Data
11:46
Working with Attribute Table
03:23
Working with Spatia Data – Symbology
0/11
Layer Symbology – Single Symbology
09:53
Layer Symbology – Categorized Symbology
06:33
Layer Symbology – Graduated Symbology
11:47
Layer Symbology – Rule-Based Symbology
08:12
Layer Symbology – Point Cluster Symbology
03:02
Downloading Data – Line Data
02:15
Downloading Data – Polygon Layer
02:51
Exporting Spatial Data
03:13
Line Layer Symbology
08:59
Polygon Layer Symbology
05:46
Copy-Pasting Layer Styles
00:31
Working with Spatial Data – Labeling
Layer Labeling (Formatting, Buffer and Background)
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Layer Labeling (Formatting, Buffer and Background)
11:17
Layer Labelling (Shadow, Callouts and Placement)
09:23
Scale-Dependent Layer Labeling
04:40
Rule-Based Labeling
04:24
Line Labeling
03:59
Polygon Labeling
05:33
Working with Spatial Data – Data Selection and Filtering
0/6
Select By Expression
12:13
Select by Expression Part 2
07:19
Export Selection Results
03:29
Select by Value
02:59
Using Select Tool – By radius, by freehand
05:46
Select by Location
08:33
Working with Spatial Data – Geoprocessing Tools
Explore the geoprocessing tools in GIS. These include buffer, clip, dissolve, intersect, difference and many more
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Buffer
16:20
Buffer – Part 2
04:19
Clip (Points)
03:11
Clip (Lines and Polygons)
01:59
Difference
08:24
Dissolve
03:22
Working with Spatial Data – Field Calculator
Automate attribute calculations in your QGIS project
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Using Field Calculator – Part 1
08:17
Using Field Calculator – Part 2
05:27
Working with Spatial Data – Raster Data
In this topic we get into the other common data format in geospatial; Raster files
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Introduction to Raster Files
02:22
Downloading Raster Files
05:23
Raster Symbology
07:41
Raster Layer Clipping
07:05
Using Raster Calculator
06:54
Adding XYZ Tiles
10:15
Working with Spatial Data
00:10:00
Creating Spatial Data
In this topic, we will explore the methods of creating our own spatial data in QGIS. This process is more of converting raster to vector data
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Creating Spatial Layers Overview
02:29
Creating Point Data
14:05
Editing Point Layer
03:12
Creating Line Layers
08:24
Editing Line Layers
03:03
Creating Polygon Layers
06:34
Editing Polygon Layers
11:47
Map Making
This is an interesting topic. You get to bring together all the skills learnt in the previous topics into actionable outputs. Create stunning maps for reports or embending on you documents.
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Map Making Intro
00:50
Print Layouts
10:57
Working with Map Elements
12:51
Exporting Maps
04:55
Map Automation – Atlas
Use the tips and tricks to automate your map making processes. Save time with the hacks in this topic
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Introduction to Atlas
10:21
Exporting Atlas
01:49
Layer Filtering in Atlas
06:54
Custom Labels in Atlas
05:52
Conclusion
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Final Remarks
01:32
Introduction to GIS with QGIS
About Lesson

Raster files are a fundamental type of spatial data used in GIS. They consist of a grid of pixels (cells), where each cell holds a value representing a specific attribute such as elevation, temperature, or land cover. Raster data is commonly used for continuous data representation, such as satellite imagery, digital elevation models (DEMs), and remote sensing data.

Why Use Raster Data?

  • Ideal for analyzing continuous phenomena like terrain, climate, and vegetation.
  • Compatible with remote sensing techniques for large-scale environmental studies.
  • Efficient for spatial modeling, such as hydrological analysis and land cover classification.
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Types of Raster Data

  1. Satellite Imagery – Captured by satellites for earth observation and monitoring.
  2. Digital Elevation Models (DEMs) – Represent terrain elevation for topographic analysis.
  3. Land Cover Maps – Show different land use categories derived from remote sensing.
  4. Aerial Photographs – High-resolution imagery used for detailed mapping.
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