1. Let’s pretty it up!

2. Border around project area Everything else is hardly noticeable… but it’s there Big circles… and semi- transparent Color distinction is clear

3. Spatial Analysis

4. Spatial analysis refers to the formal techniques to conduct analysis using their topological, geometric, or geographic properties. In a narrower sense, spatial analysis is the process of analyzing geographic data. Types of spatial analysis you have already been doing: – Buffering – Select by location

5. Layers can be overlaid - placed one over the other based on a shared geographic reference – allows analysis of the relationships between layers

6. Raster analysis is one method of Spatial Analysis.

7. Raster Data A matrix of cells Rows and columns (grid) Examples: aerial photographs, digital photos, scanned maps Examples in spatial analyst…

9. Vector vs Raster

11. Raster Data Why do we have to use raster data? – Vector data (points, lines and polygons) are limited to only certain spatial analyses Point in polygon (which points are within Line intersections – Vector data only knows about the space it occupies Raster data covers the entire region Provides a more powerful format for advanced spatial and statistical analysis

12. Types of Raster Data As basemaps As surface maps As thematic maps

13. The grid data structure Grid size is defined by extent, spacing and no data value information – Number of rows, number of column – Cell sizes (X and Y) – Top, left, bottom and right coordinates Grid values – Real (floating decimal point) – Integer (may have associated attribute table)

14. Definition of a Grid Number of rows Number of Columns (X,Y) Cell size NODATA cell

16. Value attribute table for categorical (integer) grid data

17. So now that I know what a raster is… what can I do with it? derive new information from your existing data, analyze spatial relationships, build spatial models, and perform complex raster operations.

18. Applications of spatial analysis Find suitable locations Model and visualize crime patterns Analyze transportation corridors Perform land use analysis Conduct risk assessments Predict fire risk Determine erosion potential Determine pollution levels Perform crop yield analysis

19. How to find “suitable” locations Step 1: State the Problem – Find the most suitable location for a new long-term care facility in Long Beach Step 2: Identify the Parameters and Weight – Supply: needs to be far from existing facilities (weighted by number of beds in the facilities) ( 25% ) – Demand: number of persons over 65 ( 50% ) – Access: close to major streets ( 25% ) Step 3: Prepare Your Input Datasets – Long Beach Facilities (point) – Census Tracts – Age>65 (polygon) – Major Streets (line) Step 4: Perform the Analysis

20. ArcGIS Workflow ArcCatalog: – Make sure all your layers are in the same projection (eg: UTM Zone 11N) ArcMap: 1.Load all your layers, double check that you are on the right projection and units (eg: miles) 2.Turn on Spatial Analyst Toolbar 3.Set the Environment (very important, ensures that raster layers have the same cell size!) 4.Load your indicator layers 5.“Rasterize” your layers (Ex: Kernel Density, Feature to Raster, Euclidean Distance) 6.Reclassify 7.Apply weights 8.Generate final raster

21. Step 1 Ensure that each layer in your project has the SAME projection

22. Step 2 Check the map units *Even if you change the “display” units, spatial analysis will be conducted using the “map” units

23. Step 3 Access ArcToolbox Environments Or… From the file menu: Geoprocessing, Environments Right click

24. Step 4 Set the environment 1.Processing Extent Usually set this to the extent of your project, or the largest layer 2.Raster Analysis Cell size and Mask

25. Step 5 Diagram your work flow

26. Best site for new facility Kernel Density on Number of Beds Feature to Raster on Age>65 Euclidean Distance Long Beach Facilities Long Beach Census Tracts Long Beach Major Roads Far from existing facilities Close to areas with high numbers of senior citizens Close to major streets 25% 50% 25%

27. Step 6 Do the analysis

28. Example: Kernel Density Spatial Analysis Tools > Density > Kernel Density

29. Example: Euclidean Distance Spatial Analysis Tools > Distance > Euclidean Distance

30. Example: Feature to Raster Conversion Tools > To Raster > Feature to Raster

31. Long Beach Facilities Long Beach Census Tracts Long Beach Major Roads Kernel Density on Number of Beds Feature to Raster on Age>65 Euclidean Distance Reclassify: 3 most desirable 1 = least desirable Reclassify: 3 most desirable 1 = least desirable Reclassify: 3 most desirable 1 = least desirable Reclassify: 3 most desirable 1 = least desirable Reclassify: 3 most desirable 1 = least desirable Reclassify: 3 most desirable 1 = least desirable 3 3 3 3 1 1 3 3 3 3 2 2 1 1 1 1 2 2 1 1 1 1 1 1 2 2 3 3 3 3 2 2 2 2 3 3 2 2 1 1 2 2 1 1 3 3 1 1 2 2 2 2 1 1 Spatial Analysis Tools > Reclass > Reclassify

32. 3 3 3 3 1 1 3 3 3 3 2 2 1 1 1 1 2 2 1 1 1 1 1 1 2 2 3 3 3 3 2 2 2 2 3 3 2 2 1 1 2 2 1 1 3 3 1 1 2 2 2 2 1 1 Long Beach Facilities Long Beach Census Tracts Long Beach Major Roads.75.25.75.5.25.5 1 1 1.5 1 1 1 1.5.25.5.25.75.25.5.25 1.75 1.5 1.25 2 2 3 3 2.25 1.75 2.25 Spatial Analysis Tools > Map Algebra > Raster Calculator