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Esriuk_track3_esri spatial analysis presentation
This document summarizes a presentation on spatial analysis given at the Esri UK Annual Conference in 2015. Spatial analysis involves understanding where things are located, measuring their size, shape and distribution, determining how places relate to each other, finding optimal locations, detecting patterns, and making predictions. The presentation categorized spatial analysis techniques and provided examples of how they can be used to gain insight, make more informed decisions, and achieve objectives like reducing costs and increasing efficiency. It concluded by listing common business benefits of spatial analysis and directing attendees to case studies on the Esri UK website.
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Esriuk_track3_esri spatial analysis presentation
- 1. Esri UK AnnualConference 2015 Understanding Spatial Analysis Robin Appleby & Daniel Cronin Customer Success Consultants
- 2. • New Users -Give an overview of types of Spatial Analysis • Existing Users - Expand your awareness of what analysis is possible • All Users - Provide a common terminology for articulating analysis techniques and business benefits Session Aims
- 3. • Spatial analysisis how we understand our world - mapping where things are, how they relate, what it all means, and what actions to take What is Spatial Analysis?
- 4. • Understanding Where •Measuring Size and Distribution • Determining how places are related • Finding the best locations and paths • Detecting and quantifying patterns • Making Predictions Categories of Spatial Analysis http://www.esri.com/products/arcgis-capabilities/spatial-analysis
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- 7. Understanding Where1 • Revealpatterns and trends • Visualise change over time • Combine unrelated data • Gain insight and understanding • Quick and easy to achieve
- 8. Measuring size, shape anddistribution 2
- 9. Measuring size, shape anddistribution 2
- 10. Measuring size, shape anddistribution 2 • Gain new geographic insight into existing data (area / perimeter / height) • Derive new insight through the spatial distribution of data (centre, extent) • Scientific / Objective approach rather than subjective
- 11. Determining how places arerelated 3
- 12. Determining how places arerelated 3
- 13. Determining how places arerelated 3 • Answer specific geographic questions ‘where is my nearest, how many are within?’ that would otherwise be impossible. • Understand and measure impact of one dataset on another (insurance risk) • Methodology for answering question can be shared with end users
- 14. Finding the best locationsand paths 4
- 15. Finding the best locationsand paths 4
- 16. Finding the best locationsand paths 4 • Scientifically ascertain most suitable locations based on measureable criteria • Calculate least cost routes to save mileage / costs • Quickly understand the impact of disruptions to a network and respond more appropriately.
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- 19. Detecting and quantifying patterns 5 •Objectively ascertain significance of patterns/trends in data – should I be concerned? • Better understand the processes affecting outcomes • Understand significance of change over time
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- 22. Making predictions6 • Findother successful locations to site services • Ascertain and quantify the factors affecting outcomes • Predict / model spread of data from a sample • Predict where patterns will spread in future • Test and evaluate proposed scenarios at low cost/risk
- 23. • Understanding Where •Measuring Size and Distribution • Determining how places are related • Finding the best locations and paths • Detecting and quantifying patterns • Making Predictions Categories of Spatial Analysis http://www.esri.com/products/arcgis-capabilities/spatial-analysis
- 24. • Achieve objectives •Improve program outcomes • Reduce costs • Avoid costs • Increase efficiency and productivity • Increase revenue • Assure revenue • Protect staff and public (health and safety) • Support regulatory compliance • Improve customer service • Enhance customer satisfaction • Enhance competitive advantage Benefits of Spatial Analysis Esri UK Case Studies: http://www.esriuk.com/Resources/case-studies
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