ArcGIS Spatial Analyst - University of Idaho · • Raster data is a cell ... Digital elevation model ... about how to use Spatial Analyst for raster modeling using the raster calculator

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NR402GIS Applications in Natural Resources

ArcGIS Spatial Analyst

…working with RASTER data

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NR402 - GIS Applications in Natural Resources

What is raster data?What is raster data?

• Raster data is a cell-based representation of map features. Each cell has a value. A group of cells with the same value represent a feature.

• Examples – satellite imagery, aerial photography and ArcGIS grids

1. GRID 2. Aerial photo 3. Digital elevation model

In Lesson 2 you learned about the difference between vector and raster data. Vector data representations are points, lines and polygons, while raster data is composed of pixels (cells) of a certain size. So far in this class we have worked with the vector data tools, however today’s lesson and exercise will cover raster data tools. It is important to be aware of the fact different analysis tools in ArcGIS are used for vector and raster data.This slide shows three raster data layers. 1) an ArcInfo GRID displaying the landcover types of Latah county, Idaho. The brown pixels represent agricultural lands while the green and yellow pixels represent forested lands. 2) a black&white aerial photograph – if you zoom in far enough on any photograph you will see that it is made up of pixels. 3) a digital elevation model (DEM) for Latah county, Idaho where each pixel value represents the elevation at that particular location – in this DEM the light colors represent high elevation and the dark areas represent low elevation.

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Satellite image exampleSatellite image example

Clip of Landsat 7 scenes July 27, 2000 (left) and August 28, 2000 (right) displayed with a false color composite band combination. The images show the Craig Mountain Wildlife Management Area (65,000 ha) south of Lewiston, Idaho. The southern portion of the area burned in the Maloney Creek Fire in mid august 2000.

Satellite imagery is raster data. These are clips from Landsat 7 imagery at 30 meter pixel size.

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Aerial photo exampleAerial photo example

Aerial photographs is another example of raster data. Usually the pixel size is 1-2 meters.

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– 7.5 minute Topographic maps

Digital Raster Graphic (DRG’s)Digital Raster Graphic (DRG’s)

The commonly used 7.5 minute topographic maps (1:24,000 scale) are available in digital form for most areas in the USA. In GIS language they are referred to as Digital Raster Graphics (DRG’s). The DRG’s are spatially referenced which means that they have map coordinates. These digital maps can be used as a back-ground for your plot data or for creation of field maps.

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Count is the number of cells in a value category

Raster dataset (GRID) of the vegetation types on Craig Mountain

Raster dataset (GRID) of the vegetation types on Craig Mountain

This slide shows a raster dataset (GRID) of the vegetation types on Craig Mountain along with the associated tabular data. Raster (grid) tables are different than vector tables. Grid tables always contain at least two fields – VALUE and COUNT. The VALUE represent the different grid features. In this example grid VALUE 2001 represents the ‘Dry-land crop types’ on Craig Mountain. The COUNT column tells you that there are 845 pixels (cells) of this VALUE-type. The area of ‘Dry-land crop types’ (value = 2001) can be calculated if the pixel size is known. The pixel size for the Craig Mountain vegetation grid is 30 m and the area of ‘Dry-land crop types’ is therefore 30x30x845 square meters = 760500 square meters (= 76.05 hectares).Notice how the raster table is similar in structure to a vector SUMMARY table.

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Spatial Analyst menu - OptionsSpatial Analyst menu - Options

This slide shows you the menu options in Spatial Analyst. Throughout the rest of the lecture and in the exercise you will learn more about what these menu options has to offer. The last entry in the menu ‘Options’ is important. This is where you set up the conditions for your analysis such as the default directory for saving raster data created in Spatial Analyst. This is also where you define the analysis extent and cell size.

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OptionsOptions

Working directory

Analysis mask

There are three tabs under the ‘Options’ menu – General, Extent, Cell size

General: Here you specify the working directory for Spatial Analyst. It is important to specify a working directory, otherwise Spatial Analyst will save created raster datasets in a default location where they may be difficult to find later. Always specify a working directory that has no spaces in the name. Fore example name a folder ‘GIS_Data’ rather than ‘GIS Data’. Spaces in folder names will cause problems – please adopt the habit of never using spaces in folder or file names when working with GIS data.Under the General tab you can also specify an Analysis Mask. This is a raster dataset with the preferred analysis extent and shape.Extent: You can here specify the desired output extent for your analysis as an existing GIS layer or using map coordinates. This could be useful if you are working with state-wide data but only want to perform the analysis in one county. The boundary for this county could be set as the analysis extent. You can set the analysis extent to be the same as another data layer in the ArcMap project or to be the same as the current Display.CellSize: Here you specify the cell size for the outputs from your analyses. If not specified Spatial Analyst will ‘guess’ what cell size you want for your output layers – be aware – Spatial Analyst does not always guess right!

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Example: Distance from streams on Craig Mountain

DistanceDistance

The VALUE of each pixel represents the distance to the nearest stream in meters (assuming that you work in a metric coordinate system such as UTM).

A ‘Distance’ layer can be created in Spatial Analyst. The input is here a point or line vector dataset and the output is a raster dataset where each pixel has the value of the distance to the vector feature. The layer in this slide represents distance to streams and was created from the stream layer (vector lines) for Craig Mountain. This is similar to a buffer operation in the vector-world.

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•Inverse Distance Weighting• Spline• Kriging

InterpolationInterpolation

Depth soundingspoint layer

Interpolated surface

Simple interpolations can be performed in Spatial Analyst. This example shows depth soundings (as a point layer) for a small section of the Columbia River. Interpolation or kriging techniques can be applied to create a continuous surface for the river bottom. The Geostatistical Analyst is an extension in ArcGIS that is particularly suited for estimating surfaces from point or line data.

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Craig Mountain Wildlife Management Area

Coeur d’Alene

MoscowLewiston

Boise

Snake River Salm

on R

iver

Digital Elevation Models and Surface AnalysisDigital Elevation Models and Surface Analysis

A Digital Elevation Model (DEM) is a model of the earth’s topography. Each pixel in this raster dataset represents the elevation (in meters of feet) for that particular location.

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Aspect

Slope

Hillshade

Surface attributesSurface attributes

Surface attribute such as slope, aspect, hillshade, and contours can be derived from a digital elevation model in Spatial Analyst.

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Zonal StatisticsZonal Statistics

• Statistics are calculated for each zone in a zone dataset based on values from another dataset

• Example: Calculate mean elevation within forest stands

Zone dataset: forest stands (poly or raster)Value dataset: elevation

Under the zonal statistics option you can calculate statistics such as mean, standard deviation, range etc., for each zone in a zone dataset based on values from another dataset. For example, you can calculate the mean elevation (value dataset) within forest stands (zones).

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Zone Layer

Value Layer

The output table can be joined to the zone layer to display a statistic per zone

Zonal Statistics ExplainedZonal Statistics Explained

The ‘Zone’ layer can be a vector or a raster dataset while the ‘Value’ layer must be a raster dataset. The output is a table of the statistics for each zone.

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Zonal StatisticsZonal Statistics

Zones can be continuous or non-continuous• The zone layer can be raster or vector • The value layer must be a RASTER • Many statistics are computed: mean,

median, standard deviation, min, max, variety, majority, range

• Selected statistic can be charted

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ReclassifyReclassify

Reclassify is another tool in Spatial Analyst. In a reclassification procedure the current values in a raster data table are replaced by new, user defined, values. For example an elevation grid ranging from 500-3500 m could be reclassified into 3 elevation classes:Class 1: 500-1500Class 2: 1500-2500Class 3: 2500-2500Such a reclassification would create a new grid with only three values, 1, 2, and 3.

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VALUE NEW VALUE

1 1

2 1

3 2

4 2

Input1 Input2

1 1 2

4 3 32 1

1 1 12 2 2

1 1 1

Reclassify – Example 1Reclassify – Example 1

Reclassification of a categorical variable

In this example categorical data is reclassified from values 1, 2, 3, and 4 to values 1 and 2 only. All cells that previously were value 1 and 2 in the input grid will be 1 in the output. All cells that previously were value 3 and 4 in the input gird will be 2 in the output grid.

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VALUE NEW VALUE

1-10 1

10-20 2

20-30 3

Input Output

1 5 2

12 1 3 132 1

1 1 12 2 2

1 1 1

Reclassify – Example 2Reclassify – Example 2

Reclassification of a continuous variable

In example 2 continuous data is reclassified from values 1-30 into 3 new values (1,2,3). All cells that were in the value range 1-10 in the input grid will be 1 in the output grid. All cells that were in the value range 10-20 in the input grid will be 2 in the output grid. All cells that were in the value range 20-30 in the input grid will be 3 in the output grid (there are no data in this class).

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Input1 Input2

Output = (Input1 + Input2) / 2

1 1 0

2 3 30 1

1 2 02 3 3

1 1 1

1.0 1.5 0.0

2.0 3.0 3.0

0.5 1.0

Grid algebra in the Raster CalculatorGrid algebra in the Raster Calculator

Input1 Input2

The Raster calculator in Spatial Analyst can be used to perform grid algebra, i.e. add, subtract, multiply or divide grids on a cell by cell basis. This example shows how the two input grids are added and then divided by 2 to create an output grid.

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Mathematical functions in Spatial AnalystMathematical functions in Spatial Analyst

Arithmetic operators: *, /, -, +• Trigonometric functions: sin, cos, tan, asin,

acos, atan• Power functions: sqrt, sqr, power• Logarithmic and exponential functions

The mathematical functions in Spatial Analyst are not limited to arithmetic operators but also include trigonometric functions, power functions, logarithmic functions and exponentials.

This concludes Lesson 7. In Exercise 7 you will practice using some of the tools we have been talking about in this presentation and in Lesson 8 you will learn more about how to use Spatial Analyst for raster modeling using the raster calculator in applications to natural resource problems.

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ArcGIS Spatial Analyst - University of Idaho · • Raster data is a cell ... Digital elevation model ... about how to use Spatial Analyst for raster modeling using the raster calculator