Raster GIS Google Earth image (raster) with roads overlain (vector) Raster GIS The early years of GIS involved much debate on raster versus vector - advantages and disadvantages 1
Feb 21, 2010 MODIS satellite image Discrete data: values only at points, lines or within polygons Continuous data: implied values everywhere may be from discrete data 2
The Blob is a large mass of warm water in the Pacific Ocean off the coast of North America. It was first detected in late 2013 and is expected to continue through 2015. It is an anomaly in ocean conditions and is considered to have a role in the formation of the unusual weather conditions felt in the Pacific Coast. The warm waters of the Blob are nutrient poor and have adversely affected marine life. Raster GIS Raster applications Images and Continuous data: raster GIS required Elevation: DEMs versus TINs (raster mostly preferred) Discrete data: mostly vector - Stored as vectors - but can be converted to raster 3
Raster / vector strengths Raster Vector Analysis Database Modelling Input/ Output Vector strengths GIS analysis Location what is here Condition where can I find these features -------------------------------------------------- Raster strengths Patterns how is one layer related to another Trends what has changed overlay through time Modelling what if e.g. a condition changed 4
Converting points to raster Rasterised point layers are not compact one value per pixel 5
Lines to raster Lines are seen as contiguous pixels Vector to raster conversion Similar to scanning specify cell size (pixels) and the attribute used - Vector GIS handles attributes more effectively 6
Polygons to raster areas have similar adjacent pixels Attribute table shows the number of pixels in each value, these are graphed in a histogram GIS overlay analysis Drilling down a stack of layers 7
GIS overlay analysis Raster: comparison of aligned pixels Vector: resetting unaligned polygons Raster GIS overlay analysis a stack of layers 8
TINs versus raster DEMs TIN: elevations at triangle vertices of uniform facets.. Slope and aspect built in to each triangle DEM: elevation values, one for each grid square.. Slope and aspect are generated pixel by pixel TINs versus raster DEMs analogy? TINs would be easier if landscapes were shaped like this 9
Layers created from DEM DEMs: analysis per pixel Hill shading Slope Aspect Curvature Watersheds Viewsheds Curvature: concave versus convex, profile versus planform Profile Planform DEM Curvature 10
Slope Models Hydrology Route Planning Slope Stability Avalanche Prediction Habitat Use Fire Behaviour many more 11
Hillshade Models: solar radiation Vegetation Modelling Heating efficiency Anything linked to sun energy N A viewshed is the geographical area visible from a location. It includes all surrounding points that are in line-of-sight with that location and excludes points that are beyond the horizon or obstructed by terrain and other features (e.g. buildings, trees). Viewsheds 12
Viewshed Analysis Wind farms? Cutblocks? Fire Towers Hiking Viewpoints etc.. Project example 13
Advanced project: Viewshed analysis: line of sight Watershed Analysis Assigns each pixel to the point to which it will flow, creating watersheds 14
Raster Advantages A simple data structure High spatial variability is efficiently represented (e.g. relief) Overlay operations are simple Only raster can easily store images Raster Disadvantages Data structure is not compact Not intuitive for discrete data Limited in attribute management: - each pixel has one data value Map output can appear 'blocky' What if what did happen Flooded PG image by Shane to 760m elevation, flooded pixel by pixel Glacial Lake PG ~ 10,000 BP 15