1. Esri International User Conference | San Diego, CA Technical Workshops | An Overview of Solving Spatial Problems Using ArcGIS Linda Beale, Jian Lange July 12 th, 2011

2. Using Spatial Analysis for Search and Rescue Real World Example

3. Objectives What can you do with Spatial Analysis?How can it be done?Where can you go next to learn more?..

4. The Basis of Spatial Analysis Spatial relationships Los Angeles is contained in CA Hwy 405 is adjacent to the coast LAX is 3.2 miles west off Hwy 105 - Containment - Adjacency - Distance - Selection and Statistics

5. The Spatial Analysis Workflow 5 Frame the question Explore the Data Choose the method Perform the analysis Examine Results Representation Distribution Accuracy Scale Format Break it down Audience? Automation: Use models, code Visually but … importantly, statistically Review question Common approaches Data suitable? Share analysis

6. Spatial Analysis is about Solving Problems What is inside an area?What is inside an area? What is nearby?What is nearby? Where are the events concentrated?Where are the events concentrated? Where do things move over time?Where do things move over time? Why things occur where they do?Why things occur where they do? How can we estimate values for a whole area?How can we estimate values for a whole area? What is a suitable location for …?What is a suitable location for …?

7. What is inside an area? Step 1: Frame the question : How do gas prices differ in different counties in Southern California?

8. Step 2: Explore Data - Individual gas stations in Southern California with price information - County boundaries What is inside an area?

9. Step 3: Choose a Method Spatial Join

10. What is inside an area? Step 4: Perform Analysis Step 5: Present Results (Create a report)

11. What is near by? Step 1: Frame the question Where is the closest gas stations for each freeway exit?

12. What is near by? Step 2: Explore the data Gas station locations

13. What is near by? Step 2: Explore the data Freeway exits

14. What is near by? Step 3: Choose a Method 1) Create a (1 mile) buffer around freeway and locate gas stations inside

15. What is near by? Step 3: Choose a Method (within Buffer)

16. What is near by? Step 3: Choose a Method 2) Calculate the crow’s flight (Euclidean distance) from each exit with the Near tool.

17. What is near by? What is near by? Step 3: Choose a Method (Crow’s Flight)

18. What is near by? Step 3: Choose a Method 3) Use network analysis tools (Network Analyst – Closest Facility)

19. What is near by? Step 4: Perform Analysis Demo

20. What is the spatial pattern? Step 1: Frame the question : Are there areas where gas stations have similar prices (high or low)?

21. What is the spatial pattern? Step 2: Explore the data Gas station locations with price

22. What is the spatial pattern? Step 3: Choose a Method Test Spatial Autocorrelation Hypothesis: Gas prices in Los Angeles are spaced evenly and ubiquitously throughout

23. What is the spatial pattern? Step 4: Perform Analysis

24. What is the spatial pattern? Step 5 Examine Results file:///C:/Users/jian1694/Documents/ArcGIS /MoransI_Result1.html

25. Where are clusters? Step 1: Frame the question : Where are areas with high gas prices and where are areas with low prices ?

26. Where are clusters? Step 2: Explore the data Gas station locations with price The gas price is spatially clustered

27. Where are clusters? Step 3: Choose a Method Hot Spot and Cold Spot Analysis

28. Where are clusters? Step 4: Perform Analysis

29. Where are clusters? Step 5 Examine Results

30. How do clusters move over time? Step 1: Frame the question : When the gas price goes up, do gas stations in different areas increase the price at the same time? If not, which areas are leading the pack? Which areas are trailing behind and catching up later?

31. How do clusters move over time?

32. What contributes to the spatial pattern and by how much? Step 1: Frame the question : Why the gas price is higher in Beverly Hills than in Pomona ?

33. What contributes to the spatial pattern and by how much? Step 2: Explore the Data

34. What contributes to the spatial pattern and by how much? Step 3: Choose the method Regression Analysis

35. What contributes to the spatial pattern and by how much? Step 4: Perform Analysis Regression Analysis

36. What contributes to the spatial pattern and by how much? Step 5: Examine Results

37. Traffic Related Air Pollution Demo Linda Beale

38. Overview of our analysis We had a clear objective Data availability and structure guided our choice of appropriate analysis techniques We investigated a variety of different approaches We validated our results Frame the question Explore the Data Choose the method Perform the analysis Examine Results

39. Overview of surface analysis Spatial interpolation: - used to estimate a value of a variable at an un-sampled location from measurements made at other sites - Continuous features Surface density: - Quantity distributed over a surface area (mass/area) - Discrete features

40. Surfaces: Choosing the best method Your choice of method is related to your data: - Distribution of the known points - relationship between points and their values (e.g. stationary, normal distribution) - Representivity of the known values (e.g. exact, approximate)

41. Overview of suitability analysis Identify the key factors: - Continuous features/Discrete features - Using relative values - Results are dependent of the weights used

42. Topics Combine different data sources Summarize data in defined areas Overlay Calculate and add distance Proximity Looking at spatial patterns? Finding where the clusters are? Clusters Understand contributors to a spatial pattern By how much? Regression 2 or 3D Discrete or continuous Surface Analysis Understand your data What methods are possible Interpolation Find best locations Select and weight factors Suitability

43. Analysis and Geoprocessing Spatial Analysis: - ArcToolbox - Extensions - Tip : Use the search

44. ModelBuilder Create a new toolboxAdd a new tool

45. Web resources Resource Center ArcGIS.com

46. The Collaborative Workflow 46 Analysis To help solve real problems by real people GIS Professionals

47. Final comments Analysis is not the end of the story Think about how you display the results - A data frame is not a map - Your map should be changed to suit: - Purpose and audience Remember… The accuracy of analysis results is completely dependent on the input data (GIGO)

48. Questions? http://www.esri.com/sessionevals Please complete the session evaluations at: