1 / 31

Let’s pretty it up!

Let’s pretty it up!. Border around project area. Big circles… and semi-transparent. Color distinction is clear. Everything else is hardly noticeable… but it’s there. Spatial Analysis. Spatial Analysis .

meena
Download Presentation

Let’s pretty it up!

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Let’s pretty it up!

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

  3. Spatial Analysis

  4. Spatial Analysis • 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…

  8. Vector vs Raster

  9. 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

  10. 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)

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

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

  13. 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.

  14. 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

  15. 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

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

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

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

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

  20. Step 4 Set the environment Processing ExtentUsually set this to the extent of your project, or the largest layer Raster AnalysisCell size and Mask

  21. Step 5 Diagram your work flow

  22. Best site for new facility 25% 50% 25% Far from existing facilities Close to areas with high numbers of senior citizens Close to major streets 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

  23. Step 6 Do the analysis

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

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

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

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

  28. 3 3 3 25% .75 .75 .75 Long Beach Facilities 1 3 2 .25 .75 .5 1 1 2 .25 .25 .5 1 1 3 .5 .5 1.5 50% Long Beach Census Tracts 1 2 3 .5 1 1.5 2 2 3 1 1 1.5 2 1 3 .5 .25 .75 25% Long Beach Major Roads 2 1 1 .5 .25 .25 2 2 1 .5 .5 .25 Spatial Analysis Tools > Map Algebra > Raster Calculator 1.75 1.5 3 1.25 2 2.25 1.75 1.75 2.25

More Related