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Copyright © John Lindsay, 2015

Data Analysis Part 2

John Lindsay

Fall 2015

- It is possible to build complex queries involving combinations of query questions
in the raster data model by using
**reclass**,**map algebra and/or Boolean logical operations**, and other spatial analysis operations (e.g.**distance**,**buffering**, and**area**calculations). - It is possible to perform any spatial query using either the raster or vector data model, but it generally involves more steps using the raster approach

- In a raster model, buffer creation is a two-step procedure:
- The distance from each cell to the target cell(s) is calculated
- Using resulting map is reclassified so that cells with values less than the buffer distance are given the same code

- Most modern GIS estimate the Euclidean distance of each raster grid cell to the nearest target cell
- Based on the highly efficient, 4-pass distance transform of Shih and Wu (2003)

- Some do not and some offer alternatives based on
spread functions which iteratively calculatedistance through grid cells .

- Why use
spread to calculate distance?- Until Shih and Wu (2003) spread has been far more efficient to estimate than Euclidean distance
- Spread is a powerful function for performing weighted distance operations, e.g. Least-cost analysis (more to come on this later)

- Spread is less accurate but more powerful

- How are discrete spatial entities represented in raster?
- Point is a single cell
- Line is a cell-wide string of cells
- Area is a contiguous group of cells

- Raster map overlay works on a cell-by-cell basis
- Operations are performed on individual cells from two or more input layers to produce a new layer

- Equal to, not equal to, greater than, less than, greater than or equal to, less than or equal to (= , <>, >, < , >= , <=)
- > and < operators are like a simple reclassification
- Input images are not necessarily Boolean images but the output image is always a Boolean

- MIN('Map1', 'Map2') & MAX('Map1', 'Map2', 'Map3')
- Assigns each cell in the output image the minimum (or maximum) value for the corresponding cells in the input maps
- You may have two or more input maps

- Map addition, subtraction, multiplication, and division
- One-map/one-constant operations vs. two-map ops
- 'Map1' + 10
- 'Map1' - 'Map2'

- Why might you want to multiply or divide all the values in an image by a constant (e.g. 'Map1' / 3.281)?

- Complex mathematical combinations are possible
- e.g. Ln['catchmentAreaMap' / tan('slopeMap')]
- Must be careful not to divide by zero!

- Grid cell resolution...how to cope with incompatible resolutions of input images?
- Scale of input data, i.e. dichotomous (Boolean), nominal (categorical), ordinal, interval, ratio
- Rarely perform a single operation; most GIS analyses require several operations performed in series with several intermediate steps