» 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
» Layers can be overlaid - placed one over the other based on a shared geographic reference – allows analysis of the relationships between layers
» Raster analysis is one method of Spatial Analysis.
» 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
» A matrix of cells » Rows and columns (grid) » Examples: aerial photographs, digital photos, scanned maps » Examples in spatial analyst…
» As basemaps » As surface maps » As thematic maps
» 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)
Number of rows Number of Columns (X,Y) Cell size NODATA cell
» derive new information from your existing data, » analyze spatial relationships, » build spatial models, and » perform complex raster operations.
» 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
» 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
» 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
Ensure that each layer in your project has the SAME projection
Check the map units *Even if you change the “display” units, spatial analysis will be conducted using the “map” units
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
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%