GIS 2 Spatial Analysis - Training Course
Master GIS spatial analysis techniques, including location mapping, density analysis, change detection, and pattern identification at ETC Training Center in Lebanon.
Duration: 20 hours
Teaching Methodology: Hands on
Course Schedule: Schedule
Fees: $450
Course Mode: Blended (Face-to-face or online via Zoom)
 |
 |
 |
 |
DESCRIPTION
Geographic Information Systems (GIS) are computerized systems designed for the storage, retrieval, and analysis of geographically referenced data.
GIS uses advanced analytical tools to explore at a scientific level the spatial relationships, patterns, and processes of cultural, biological, demographic, economic, geographic, and physical phenomena.
PREREQUISITES
AUDIENCE
Professionals and students exploring a potential career with GIS.
COURSE CONTENTS
This course provides a system for GIS users to develop proficiency in various spatial analysis methods, including location analysis, change over time, location and value comparisons, geographic distribution, pattern analysis, and cluster identification.
Chapter 1: Mapping where things are
1-1 Working with categories
1-2 Controlling which values are displayed
1-3 Limiting values to display
Chapter 2: Mapping the most and least
2-1 Mapping quantities
2-2 Choosing classes
2-3 Creating a map series
2-4 Working with charts
Chapter 3: Mapping density
3-1 Displaying density for analysis
3-2 Creating dot density maps
3-3 Creating a density surface
Chapter 4: Finding what's inside
4-1 Overlaying datasets for analysis
4-2 Finding features partially inside
Chapter 5: Finding what's nearby
5-1 Selecting features nearby
5-2 Creating buffer features
5-3 Clipping features
5-4 Buffering values
5-5 Using multiple buffer zones
5-6 Quantifying nearness
5-7 Creating distance surfaces
5-8 Calculating cost along a network
5-9 Calculating nearness along a network
Chapter 6: Mapping change
6-1 Mapping change in location
6-2 Mapping change in location and magnitude
6-3 Mapping percentage change in value
Chapter 7: Measuring geographic distribution
7-1 Calculating centers
7-2 Adding weights to centers
7-3 Calculating standard distance
7-4 Calculating a standard deviational ellipse
7-5 Calculating the linear directional mean
Chapter 8: Analyzing patterns
8-1 Using average nearest neighbor
8-2 Identifying the clustering of values
8-3 Checking for multidistance clustering
8-4 Measuring spatial autocorrelation
Chapter 9: Identifying clusters
9-1 Performing cluster and outlier analysis
9-2 Performing hot spot analysis