1 / 30

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. Introduction to GIS – Yoh Kawano. Spatial Analysis.

meadow
Télécharger la présentation

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. Introduction to GIS – Yoh Kawano 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 Spatial Analysis

  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. 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 Raster Data

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

  9. Vector vs Raster

  10. As basemaps • As surface maps • As thematic maps Types of Raster Data

  11. 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) The grid data structure

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

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

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

  15. 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 Applications of spatial analysis

  16. 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 How to find “suitable” locations

  17. 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 ArcGIS Workflow

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

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

  20. Right click Step 3 Access ArcToolbox Environments

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

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

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

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

  26. 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

  27. 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 1.75 1.5 3 1.25 2 2.25 Spatial Analysis Tools > Map Algebra > Raster Calculator 1.75 1.75 2.25

More Related