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GIS Lecture 3. Introduction to Raster GIS Data Structure and Raster Data Processing

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GIS Lecture 3.

Introduction to Raster GIS Data

Structure and Raster Data Processing

Data Conversion/Entry (GIS, Databases) November 6 – 10, 2006

Freetown, Sierra Leone

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Raster Data Structure

Raster Data Storage and Representation

Raster Operations and Functions

Comparison of Raster and Vector Data Models

Typically Encountered Raster Datasets

Lecture Overview

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Raster Data Structure

Raster data model represents the spatial data as a regular grid of cells (pixels).

• Each cell represents an area of the land surface.

• The location of each cell is defined by its row and column numbers.

• Each cell contains a single value.

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Characteristics of Raster Data Structure

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Comparing Raster and Vector Data

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(Aronoff, 1991)

In a raster image each cell (pixel) represents an area on

the ground of a specific size, that depends on the resolution.

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Comparing

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RASTER IMAGE STRUCTURE

Sample Landsat Infrared Image 1 byte/pixel = 8 bit = 0-255 gray scale values

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Information in the computer is stored in binary code (sequences of 1 and 0 values, “on” and “off”).

A bit (binary digit) can be either 0 or 1 and represents an exponent of the base 2:

20 21 22 23 24 25 26 27 28 1 2 4 8 16 32 64 128 256

A byte (8 bits): standard unit of measurement of computer data and computer memory.

A single bit map ( 21 = 2) is a very simple map where only two categories are represented (e.g. land/water, yes/no, true/false).

A byte map is an image file in which each cell has a value

within the range 0 - 255 (28 = 256) (e.g. many satellite sensors, including Landsat and SPOT record in 8 bit data).

Computer Storage of Raster Data

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8 BIT IMAGE GREY SCALE

255 (WHITE) 0 (BLACK)

2

8

= 256 GREY TONES

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Bit Resolution in Raster

Landsat TM (Band 4) - 8 bit (byte) image

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FULL 8 BIT (BYTE) RANGE - 2

8

TONES

Image Histogram

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Raster Soils Map

• 6 Units are represented: how many bits would be

sufficient to store this map? Is 8-bit required?

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BIT RESOLUTION

1 BIT 21 = 2 TONES 2 BITS 22 = 4 TONES

3 BIT 23 = 8 TONES 4 BITS 24 = 16 TONES

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Data Types

Depending on the phenomenon that we want to represent in our map, we will use different data types:

Bit (0, 1)

- e.g. bit-maps.

Byte (positive integer values between 0 and 255)

- e.g. byte-maps or byte-images, such as Landsat and SPOT.

Integer (a number having non fractional part also known as whole number, such as: 1, 2, 3, ..)

- e.g. soil classes.

Real (any number having fractional part: e.g. 2.65, 1.423) - e.g. rainfall or temperature measurements,

Digital Elevation Models (DEMs).

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ILWIS Coordinate System for Sierra Leone DEM

Latitude – Longitude

Datum and Ellipsoid

Ellipsoid Parameters

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ILWIS Raster Properties Window SRTM, DEM for Sierra Leone

What file size

(uncompressed) is required for this Sierra Leone DEM?

4554 lines by 4501 Pixels 2 bytes/pixel

Answer:

No. of Pixels = 4554*4501

= 20,497,554 Pixels Disk Storage =

20,497,554 Pixels * 2 bytes/Pixel = 40,995108 bytes

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ILWIS Georeference for Sierra Leone DEM

Number of

Lines and

Columns

Bounding

Coordinates

Pixel Size

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file title : Stouffville Landcover data type : byte

file type : binary columns : 512 rows : 512 ref. system : utm ref. units : m unit dist. : 1

min. X : 641550 max. X : 646670 min. Y : 870380 max. Y : 875500 pos'n error : unknown resolution : unknown min. value : 1

max. value : 25

value units : unspecified value error : unknown flag value : none flag def'n : none legend cats : 26

category 0 : No data

category 1 : Agriculture - Bare Fields category 2 : Agriculture - with Crops category 3 : Deciduous Forests

Raster Header from an IDRISI file

Question 1: What would you expect for a file size?

Answer:

1 (byte/pixel)*(512*512 pixels) = 262,144 bytes

Question 3: What is the

dynamic range? Is 8-bit

required?

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file title : Stouffville DEM data type : integer

file type : binary columns : 512 rows : 512 ref. system : utm ref. units : m

unit dist. : 1.0000000

min. X : 641550.0000000 max. X : 646670.0000000 min. Y : 870380.0000000 max. Y : 875500.0000000 pos'n error : unknown

resolution : unknown min. value : 250

max. value : 350

value units : unspecified value error : unknown

flag value : none flag def'n : none legend cats : 0

Raster Header from an IDRISI file

Question 1: What would you expect for this file size?

Note: the Idrisi integer data type = 2 bytes (16 bits = 2

16

).

Question 2: If data type

had been bit, what would

you expect for file size?

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Example of Raster Properties for ArcGIS How much disk storage does this file take?

How much disk storage is required for this file?

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How much disk storage does this file take ?

How much disk storage is required for this file?

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Example of Raster Extents from ArcGIS With a 10 metre resolution –

How many cells are there in this image?

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Storage Options for Raster Data

1. Uncompressed:

• Full Raster Arrays (e.g. .tiff files. e00, asc, etc.) 2. Compressed Fully Recoverable:

• Run - Length Encoding (e.g. .zip files)

• Standard Run-Length Encoding

• Value Point Encodin

• Quadtrees (e.g. .TDYAC-SPANS)

3. Image Compressed - Non Fully Recoverable.

You can really get 40:1 ratios with these compression techniques, but at an image cost. (e.g. .jpeg, .jpg, Mr.

Sid)

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1. Simple data structure.

2. Easy and efficient overlay operations.

3. High spatial variability is efficiently represented.

4. Compatible with Remote Sensing imagery.

5. Same grid cells for several attributes.

6. Can be used for efficient

manipulation and enhancement of digital images.

7 Good for representing transitions.

Comparison of Raster and Vector Data Model

Advantages of Raster: Advantages of Vector:

1. More compact data structure than the raster model.

2. It provides efficient encoding of topology, and, as a result, more efficient implementation of

operations that require

topological information, such as network analysis.

3. Better suited to supporting graphics.

4. Accurate map output.

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Disadvantages of Raster:

1. Requires more disk space (storage and processing).

2. Topological relationships are more difficult to represent.

3. Difficult to accurately specify locations.

4. Difficult to represent the exact area, perimeter or shape of a feature.

5. Inferior output quality

Comparison of Raster and Vector Data Model

Disadvantages of Vector:

1. More complex data structure than raster model.

2. Overlay operations are more difficult to implement.

3. High spatial variability is inefficiently represented.

4. Manipulation and enhancement of digital images cannot be

effectively done in the vector space.

5. Not compatible with RS imagery.

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RADAR

Landsat

DEM Slope

Geology

Landcover

Raster GIS Analysis and Modelling

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A Comparison of Raster, Vector and TIN Data Structures For Representing Elevation

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Taken from: Aronoff, 1991

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Raster Analysis Functions

• Retrieval Operations

• Recoding, (Re)Classification and Rescaling

• Overlay Operations

• Neighbourhood Operations

• Connectivity Functions

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• Example using a simple linear function:

Example Interpolation from Point Data

1 3 4 6

2

2 4 5

1 3 6

4

1 3 4 6

2

2 4 5

1 3 6

4

2 5

1 1 1

1

2 2 2

5

5 5 5 3

3 3

3

4

4 4

6 6 6

6

Known values Known and predicted values

Interpolation

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100m 120m 140m

160m

Example Interpolation from contour lines

A contour line is a sequence of points that have the same elevation value (e.g. 100 m).

The interpolation create a grid of values and calculate the unknown value for each cell

(e.g. 130 m). 130m

Creation of a raster map from an isoline map.

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Assume resolution of 1m

2.8 2.4 2 2.4 2.8 2.4 1.4 1 1.4 2.4 2 1 0 1 2 2.4 1.4 1 1.4 2.4 2.8 2.4 2 2.4 2.8

Starting cell

Measuring Euclidean Distance in Raster Space

- Count the number of cells to travel - Multiply #cells x resolution

- All cells adjacent and in line with target are assigned value 1

- Diagonal distances produce right angled triangles

(Pythagorean Theorem):

count each cell and multiply by (resolution x 1.414)

- In case of multiple routings:

consider always the shortest distance.

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Deriving A Slope Map from a Digital Elevation

Model.

DEM

Derived Slope Map

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Neighbourhood Operations Topographic Functions

• Topography refers to the distribution of elevation across a land surface.

• In a GIS the topography is represented by digital elevation data (Digital Elevation Model).

• Topographic functions are used to calculate parameters that describe the topography of a local terrain.

The two most commonly used terrain parameters are: slope and aspect.

• These parameters are useful in analysis where topography is important: e.g. soil erosion, watershed drainage modelling, hill shading, sun exposure.

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RASTER FILTERING: THE MOVING WINDOW

A 3 by 3 Moving Window (Kernel)

Operating Position in Filtered Image

Original Image Filtered Image

C1 C2 C3 C4 C5 C6 C7 C8 C9

KERNEL COEFFICIENTS

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FILTERING EXAMPLE- High Pass (Sharpening)

No 3 by 3

Filter

5 by 5 7 by 7

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EXAMPLE OF CALCULATING RASTER FLOW DIRECTION FOR HYDROLOGY ANALYSIS

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FLOW ACCUMULATION

Flow accumulation is the accumulated weight of all the cells that flow into each subsequent downslope cell.

The flow direction data set is used to create the flow accumulation data set.

The FLOW ACCUMULATION command creates a grid of

accumulated flow to each cell, by accumulating the number of

cells that flow into each downslope cell. The accumulated flow

is based upon the number of cells flowing into each cell in the

output grid.

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Deriving Hydrology Networks for a Raster DEM Example Sierra Leone – SRTM -DEM

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Image Pyramids

Most such technologies for displaying very large images will include the use of intermediate level images or pyramids to allow much faster display of images,

including zooming in or out and panning the image.

• If we compute intermediate levels of

zoom and save extra images that takes time. If we compute and store very many intermediate levels of zoom that will also increase the

storage size required for images

• The need for extra storage space also is not usually a burden, since most people would happily see an image increase in storage space by, say, 50% if thereafter display was virtually instantaneous instead of

taking minutes for each change in zoom

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Sample Raster Data Sets

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Airborne Geophysical Data

Gravity/ Magnetics / Radiometrics /Electromagnetics

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Lake Bathymetry Data

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DEM Derived/Modeled Products

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Satellite Imagery Hurricane Isabel

off the Bahamas

Satellite: Aqua

Resolution: 2 Km

Date: Sept. 16, 2003

Time: 17.40

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Satellite Imagery from the Terra Satellite

MODIS Instrument - For Sierra Leone

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Landsat Satellite Imagery for Sierra Leone

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Global Land Cover Database for Sierra Leone

(50)

Modeled Population Distribution for Sierra Leone

http://www.fao.org/geonetwork/srv/en/metadata.show?id=1261&currTab=simple

(51)

Global Sea Surface Temperature

From MODIS, Satellite Imagery

(52)

Time Series of 32 Day Cloud-Free

MODIS Composite Images for Africa

(53)

Modeled Cattle Distribution for Sierra Leone GLiPHA Data Source

http://www.fao.org/ag/aga/glipha/index.jsp

(54)

http://www.jpl.nasa.gov/radar/sircxsar/interferometry.html

The Shuttle RADAR Topographic has one Transmitter but two Receivers Enabling Height

Determination

(55)

Shuttle Radar Topographic Mission (SRTM) DEM

For Sierra Leone

References

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