GIS, Spatial Analysis, and Modeling

 

Ø INTRODUCTION


Introduction

This IACT course aims to further develop Participants’ GIS and spatial analysis skills, allowing them to become independent learners able to solve complex spatial problems. It builds on existing knowledge of GIS that the Participants must have acquired through a previous module and assumes a basic understanding of data handling and manipulation techniques

IACT course help you to comprehend how GIS technology, built essentially for handling maps and " map-related ideas " , can be adapted to the needs of dynamic simulation modelling; especially when it is not even perceived as an optimal platform for modelling.

 

Ø Objectives

 

At this program's conclusion, participants should be able to:

l  Quantify spatial patterns using spatial statistics and analyze change over time to identify emerging hot spots.

l  Use interpolation and regression analysis to explain why patterns occur and predict how patterns will change.

l  Prepare data and choose appropriate tools and settings for an analysis.

l  Examine features and distribution patterns within an area of interest and identify optimal locations using  3D analysis tools.

l  Developed a basic understanding of the analysis and modeling of geographic information.

l   Understood the application of GIS operations to vector and raster data including proximity and overlay operations, terrain analysis, and distance modeling.

l   Developed basic skills in applying appropriate GIS methods for problem solving in spatial analysis and modeling (site suitability and statistical).

 

 

Ø TRAINING METHODOLOGY


This training course will combine presentations with instructor-guided interactive discussions between participants relating to their individual workplace. Practical exercises, video material and case studies aiming at stimulating these discussions and providing maximum benefit to the participants will support the training.

This interactive training course includes the following training methodologies as a percentage of the total tuition hours:

l  30% Lectures, Concepts, Role Play

l  30% Workshops & Work Presentations, Techniques

l  20% Based on Case Studies & Practical Exercises

l  20% Videos, Software & General Discussions

Pre and Post Test

 

Ø WHO SHOULD ATTEND?

 

This course is designed for participants who have limited prior knowledge of spatial analysis in the context of retail analytics. Participants are likely researchers looking to work with spatial data related to consumers or the retail sector whether in a commercial, public sector or policy focused context.

Process analysts, business analysts, project managers, business process owners, general business managers

 

 

                                                                               Outline

Day 1

Building a foundation for spatial analysis

·        What is spatial analysis?

·        Benefits of spatial analysis

·        Common analysis problems

·        Spatial analysis tools

·        Spatial analysis workflow

Applying spatial analysis

·        Planning and preparing for spatial analysis

·        Data properties Raster data considerations

·        Environment settings

 

 

Day  2

 

 

Proximity analysis

·        Using proximity in everyday life

·        Choosing the best distance measure

·        Ways to measure distance

·        Outputs of proximity analysis

·        Buffering using different distance measures

Overlay analysis

·        How overlay works

·        Overlay tools

·        Choosing the appropriate tool

·        Perform overlay analysis

·        Make selections based on location

 

 

 

Day 3

 

 

Automating spatial analysis

·        Automating workflows

·        Automation methods in ArcGIS Pro

·        Batch geo processing

·        Build a model

Creating surfaces using interpolation

·        What is interpolation?

·        Interpolation methods

·        Interpolation tools

·        Deterministic interpolation

 

Day 4

 

Suitability modeling

·        What is suitability modeling?

·        Suitability modeling workflow

·        Evaluating analysis criteria

·        Choosing vector or raster overlay

·        Deriving surfaces from other sources

Spatial statistics

·        What are spatial statistics? Types of spatial statistics

·        Interpreting inferential statistics

·        Descriptive versus inferential

·        Spatial statistics tools

·        Clusters and outliers

·        Clustering tools

 

 

 

 

Day 5

 

Regression analysis

l  Explaining spatial patterns

l  Causes of spatial patterns

l  What is regression?

l  Regression equation

l  OLS regression

l  Checkpoint

l  Interpreting OLS diagnostics

l  Six OLS checks

l  OLS reports

l  Exploratory regression

3D analysis

l  When to use 3D analysis

l  3D analysis examples

l  Interactive 3D analysis

 

 

Schedule

 

  • 08:30 – 10:15 First Session
  • 10:15 – 10:30 Coffee Break
  • 10:30 – 12:15 Second Session
  • 12:15 – 12:30 Coffee Break
  • 12:30 – 14:00 Third Session
  • 14:00 – 15:00 Lunch

 

Fees

 The Fee for the seminar, including instruction materials, documentation, lunch, coffee/tea breaks & snack :

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