Raster data analysis.......

1. Raster Data Analysis
PRESENTED BY: ABDUL RAZIQ
AMEER MUAVIA
KHIZAR NAWAZ

2. Raster Data:
 Definition:
 A graphic representation of features and attributes.
 Made of grid which contain information.
 Cell size:
 Cells may be of any size.
 What does cell size tell us?
 coarser or finer the pattern or features are that appear in raster.

3. Raster Grid:
 It was usually square but may be of different shape.
 Each group of cells could either call as a layer of a cells.
 Various layers are overlying each other
 Entities represented by grid:
 Grid made of cell.
 Values applied to cells.

4. Representation Of Data:
 In Vector Data Model:
 Features themes use coordinate and lines to represent geographic features.
 Representation of Raster data:
► Raster grid use cell to represent geographic spatial features.

5. Raster Data Includes:
 Images.
 Scanned maps.
 Air photo.
 Satellite Images.
 Grids DEM.

6. Raster Data Analysis
 Buffering
 Reclassification
 Hill shades
 Interpolation
 Surface calculation

7. Buffering:
 Buffering is the result of classifying cells according to whether the cells lie
inside or outside the buffer
 Output cells are either assigned an in value or an out value.
 In value cells are whenever the cell-to-cell distance is less than the
specified buffer distance,
 While out value cells are further than the buffer distance .
 There are many occasions when buffering is required.
 One example of using a buffer is showing greenway areas around lakes.
 Another example of using a buffer is showing areas along highways where
the traffic noise is above a certain level .

8. Reclassification:
 It is a process of reassigning a values or list of values.
 Reason:
 set specific values to exclude no data from analysis.
► Change values in response to new information or classification schemes.
► To replace one set of values with an associated set
► Example:
► To replace values representing soil types with pH values.
 Assign values of preference, priority, sensitivity, or similar criteria to a
raster.

9. Hill shade:
► By placing an elevation raster on top of a hill shade raster and adjusting
the transparency of the elevation raster.
► To create a visually appealing relief map of a landscape.
Shadows with high sun angle Shadows with low sun angle

10. Interpolation:
 Interpolation is the process of estimating unknown values between
known values.
 It can be used to predict unknown values for any geographic point data,
 such as elevation, rainfall, chemical concentrations, and noise levels
 Why inter
 that spatially distributed objects are spatially correlated; in other words,
things that are close together tend to have similar characteristics.

11. Input elevation point data Interpolated elevation surface

12. Surface calculation:
 Cell by cell evaluation of Mathematical functions

13. Tools For Raster Analysis:
 Map algebra
 Hill shades
o Slopes
o Aspects
► Raster modeling
► Raster and vector integration
o Raster to polygon conversion
o Contour generation
o Surface interpolation from point data

14. Raster Data Analysis Operations:
 Local (cell-by-cell) operations
 Neighborhood operations
 Zonal operations
 Raster distance measure operations - similar to buffering

15. Local Operations
 Cell-by-cell based,
 Creates a new raster from either a single or multiple input raster.
 Includes Reclassification and Map Algebra.

16. Neighborhood operations:
 Neighborhood operations are a method of analyzing data in a GIS environment.
 They are especially important when a situation requires the analysis of relationships
 between locations, rather than interpret the characteristics at individual locations.

17. Zonal Operations:
 Uses groups of cells that have the same value or like features
 Can be contiguous or non contiguous
 For single raster zonal
 Operations measure the geometry of each zone (area, perimeter,
thickness, centroid)
 For two raster (an input raster and a zonal raster) a summary of values
for the input values in
 each zone of the zonal raster is generated in an output raster (summary
statistics and measures)

19. How does it work?
 An imaginary grid is placed over an area,
 Each cell in the grid is given a numeric code.
 Number was given to descried the dominant attributes in the data
 Each cell may be
 Qualitative
 Numeric
 A feature identifier