Module 7 Raster operations

Introduction Geo-Information Science Practical Manual Module 7 Raster operations

7. INTRODUCTION 7-1 LOCAL OPERATIONS 7-2 Mathematical functions and operators 7-5 Raster overlay 7-7 FOCAL OPERATIONS 7-8 Focal (neighborhood) statistics 7-9 ZONAL OPERATIONS 7-11 Zonal statistics 7-11 Zonal geometry 7-11 GLOBAL OPERATIONS 7-13 Euclidean distance & Buffers 7-13 Creating raster data subsets 7-14 Reclassification of the Euclidean distance raster 7-16

7. Introduction The first two data handling classes, queries and transformations, were discussed in modules 5 and 6. This module and the next two modules deal with the third data handling class: operations. This module focuses on operations in raster environment, so called cell-based analysis. Raster operations are powerful tools in spatial modeling. ArcGIS offers the user a comprehensive toolset for cell-based GIS operations: ArcGIS Spatial Analyst. These operations can be divided into five types: local, focal, zonal and global operations and operations that perform a specific application (e.g. hydrologic runoff analysis functions and cost or resistance functions). The specific application operation type will not be discussed in this module. Cell-based operations use Map Algebra (Tomlin, 1990). Map Algebra is a computational language that models the surface of the earth as a multitude of independent, coincident dataset layers using operators or functions to one or more (coinciding) raster dataset layers (Bruns and Egenhofer, 1997); see examples below. The operations are performed on individual cell value(s) of the input layer(s) (Heywood et al., 2002). Map Algebra output is always a new raster layer. Note that in order to use Map Algebra with more than one input raster dataset, the geometry (cellsize, extent, orientation) of the input raster datasets the geometry must match. In this module the following GIS tools and operations are used: The Spatial Analyst Toolbox Local operations with the raster calculator and the combine function Focal operations: focal (neighborhood) statistics Zonal operations: zonal statistics and tabulate areas Global operations: Euclidean Distance (Buffers) Objectives After having completed this module this part you will be capable: to give definitions of the different groups of operations; to describe the possibilities of each group of operations; to perform various operations with ArcGIS using the Spatial Analyst Toolbox. ArcMap document: Raster operations.mxd Literature: Chang, 2010: Chapter 12 Raster Data Analysis (except 12.5.1) 7-1

Local operations Local operations compute a raster ouput dataset where the output value at each location (cell) is a function of the input value(s) at spatially coinciding location(s) in the input raster(s) (figure 1). Figure 1. Local operations affect only one cell. We will discuss four types of local operations in this module. There are more operations available in ArcGIS. You can find them in the Local toolset of the Spatial Analyst Tools in ArcToolbox. Feel free to explore them yourself if you desire. It is adivised to explore ArcGIS Desktop Help to gain more information about these operations. When you perform local operations you should realize that: if a cell in an input raster dataset has the value of NODATA, the value of the cell at the same location in the output raster is always NODATA (Figures 2-6)!! the cell values of the input raster dataset(s) are not added to the ouput table as attributes, except when using the combine function. You can imagine that this is not always desireable. More background information about how the value of NoData is treated during operations is given in the course Geo-information Tools (GRS 20806). 1. The first type of local operations calculate output values for each location as a function of the cell values in a single raster dataset, using mathematical functions. For example, the output value is the base e of the input value (figure 2). Mathematical functions (f) have the syntax: output raster = f(input). They are applied to the values in a single input raster. There are four groups of mathematical functions: Logarithmic; Arithmetic (add, substract, divide, multiply); Trigonometric (sin, cos, tan); Powers. These functions can be carried out with the following ArcGIS tools: Spatial Analyst toolbar: Raster Calculator. Spatial Analyst toolbox: Math toolset. Figure 2.The logarithmic function Exp (base e). Syntax: ouput raster = Exp(Inlayer1). 7-2

2. The second type of local operations calculate output values for each location as a function of cell values at spatially coinciding locations in two or more raster datasets, using arithmethic (mathematical) or logical operators. For example, the average of two values (Figure 3) or value input raster 1 > value input raster 2. These operations have the the syntax: output raster = (input1 opr input2). The opr refers to an operator that operates on two or more variables, the input raster datasets. Arithmetic operators. Arithmetic operators allow for the addition, subtraction, multiplication, and division of two rasters, numbers, or a combination of the two. Spatial Analyst toolbar: Raster Calculator. Figure 3. Using arithmetic operators to calculate the cell average of two raster datasets. Syntax: ouput raster dataset = (Indataset1 + Indataset 2) / 2. Logical operators. Logical operators evaluate the values of an input rasters using a conditional statement. Logical operators can be Boolean (AND, OR, etc.) or Relational (<, >, <>, etc.). One conditional statement can contain one or multiple Boolean and relational operators. The outcome of a logical operation is always TRUE or FALSE. Spatial Analyst toolbox: Math Logical. The logical toolset contains tools for Boolean end relational evaluation. The logical tools use one operator and have the syntax: output raster = (input1 logical opr input2). Figure 4. The Boolean AND tool finds cells that have non-zero values in both input raster datasets. Syntax: ouput raster dataset = (Indataset1 & Indataset 2). Spatial Analyst toolbar: Raster Calculator. With the raster calculator you can combine multiple Boolean and relational operators within one conditional statement. For example output raster dataset = (soil type = 1 AND elevation >=40). 7-3

3. Operations that calculate summary statistics for each location as a function of cell values at coinciding locations in two or more raster datasets using cell statistic functions (Figure 5). Spatial Analyst toolbox: Local Cell statistics Cell statistic functions have the syntax: output = f(input1, input2). You can calculate ten statistics: 1. Majority 2. Maximum 3. Mean 4. Median 5. Minimum 6. Minority 7. Range 8. Standard Deviation 9. Sum 10. Variety Figure 5. Calculating the mean statistic for three inpu raster datasets. Syntax: outgrid = mean(ingrid1, ingrid2, ingrid3). 4. The fourth type of local operations is the raster overlay. In an overlay the cell values of two or more input raster datasets are combined into one output raster dataset using the combine function of Spatial Analyst. The Combine function assigns a new unique value to each unique combination of values at each location. The original Value items, or the alternative field values if specified, are added to the output rasters' attribute table: one for each input raster (Figure 6). Spatial Analyst toolbox: Local Combine Figure 6. Overlay of two input raster datasets. Syntax: outgrid = combine(ingrid1, ingrid2, ingrid3). 7-4

1. Open ArcMap document Raster operations.mxd. First activate the Spatial Analyst extension. Click Tools in the menu bar, click Extensions and check Spatial Analyst. This extension allows you to use the Spatial Analyst tools for geoprocessing of raster datasets! a. Are local operations geometric (spatial) or thematic (non-spatial) operations? Explain your answer. b. What geometric criteria should be fulfilled in order to execute local operations that involve more than one dataset? Mathematical functions and operators The Raster Calculator of ArcMap can create simple mathematical expressions with a single function or complex mathematical expressions with many operators and functions. The output raster dataset is automatically named Calculation followed by a unique number. This name can be changed after the creation, by clicking in the name field of the raster dataset. Warning: the output raster dataset of the Raster Calculator is a TEMPORARY raster dataset, which is stored in the TEMP folder on your harddisk and NOT in your workspace. This raster dataset will be lost when you restart your ArcMap document. If you are satisfied with the output result of your operation, you can make the raster dataset permanent. You can do this by right-clicking the raster dataset and selecting Data Make Permanent. Give the raster dataset an appropriate name and save the file in your workspace folder. Make sure the type is set to ESRI GRID. INSTRUCTIONS: 1. Open the Spatial Analyst toolbar: in the menu bar select: View Toolbars Spatial Analyst. 2. Click the Spatial Analyst dropdown arrow, click Raster Calculator. 3. The raster calculator dialog box aids in the creation of an expression that produces a new output raster dataset. The expression can be based on a single raster dataset or multiple raster datasets. 4. There are seven sections in the Raster Calculator dialog box (Figure 7). 1. The layers box lists the available raster datasets in the active data frame; 2. Arithmetic operators; 3. A keypad of numbers; 4. Relational operators; 5. Boolean operators; 6. Mathematical functions; 7. The expression box. 5. Type your expression in the expression box or create your expression by clicking the operator buttons. You can insert raster datasets in your expression by double-clicking a raster dataset in the layers list. 6. To access recently entered expressions, right-click in the expression box and click Recent Expressions. Then copy and paste the expression into the expression box. 7. Click Evaluate. 7-5

8. The output raster dataset is added to the active data frame. 9. Make the output raster dataset permanent; store it in your workspace 1 2 3 4 5 6 7 Figure 7. The Raster Calculator. 2. Activate data frame Local. The dataset dem (digital elevation model) contains elevation values, expressed in meters. Create a new raster where elevation is expressed in centimeters. a. Write down the created expression which you formulated in the Raster Calculator dialog box. b. What is the name of this new raster dataset? Make the raster dataset permanent. Save it in your workspace folder and change the name to something more appropriate. 3. You can also select raster cells with the Raster Calculator using relational and Boolean operators in the expression. Note: when you press the = button in the raster calculator, a double equal to = = appears in the expression. This is normal raster calculator syntax. a. Create an expression in the raster calculator with which you select buildings (Lu_raster value 1) located on sites that have an elevation of more than 30 meters. Write down the expression. b. What is the meaning of the values 0 and 1 in the output raster dataset? 7-6

You have been asked by the municipality to select potential housing sites. These sites must fulfill one of the following conditions: (1) The sites must be located on a holtpodzolgrond (soil code gy30, value 4) but it is not allowed to clear forest. (2) Sites with another soil type are also suitable if the elevation is at least 9 meters. c. Write down the expression you created for this selection. d. What is the total area of the potential housing sites? e. You can consider the expression you used as a query: you made a selection. However, there is a difference between this selection and the queries you made in module 5. What is this difference? Raster overlay The output rasters you created during the previous exercise were binary: a raster cell did or did not fulfill the condition you stated in the expression. The attribute table of the output raster contains only the values 0 and 1. The original values of the soil code or land use code were lost which can be inconvenient if you want to do further analysis. A raster overlay by using the combine function avoids this problem. The original values of the input rasters are kept in the attribute table of the output raster. INSTRUCTIONS: 1. Open ArcToolbox. Click Spatial Analyst Tools Local Combine. 2. Click the dropdown arrow of the Input rasters box; click the rasters you want to combine. 3. In the Output raster box you specify the name and location of the output raster. 4. Click OK. Note: the values in the output attribute table are integer. Values that contain decimals (such as elevation values) will be rounded!! 4. Overlay the rasters soil_raster, lu_raster and dem using the combine function. a. Select from the attribute table pasture areas (value 5) on soils with soil code Rn95C (value 3). What is the elevation range of the selected raster cells? b. What part (in %) of the soils with soil code Rn95C is covered by pasture? 7-7

Focal operations Focal (neighborhood) operations create an output raster dataset in which the output value at each location is a function of the input value at that same location and the values of the cells in a specified neighborhood around the location (Figure 8). A neighborhood can be a rectangle, a circle, an annulus (a doughnut shape), and a wedge in any direction. The size of the neighborhood is userdefined. Figure 8. Focal operations affect the source cell and a user-defined neighborhood. Two important types of focal operations are focal statistics and focal filters. The focal filters are beyond the scope of this course. This subject is treated in the course Remote Sensing (GRS 20306). However, feel free to consult ArcGIS Desktop Help for more information about filters. In this module we will focus on the focal stastics, also referred to as neighborhood statistics. How does a focal operator work? We know that focal operators use the value of a source cell and the values of the cells in a user-defined neighborhood around the source cell to calculate a new cell value for the output raster cell at the same location as the source cell. Suppose we define a rectangular neighborhood focus of 5x5 raster cells (Figure 9) and a focal function, for example the neighborhood statistic focal sum. You can consider the neighborhood focus as a window that moves over your raster dataset layer. In this example the moving window is located at the top left corner of the raster dataset layer (Neighborhood A, figure 9). Figure 9. Processing by 5x5 raster cells neighborhood. 7-8

The central cell in the window is the source or processing cell. A new value is calculated for each processing cell based on the chosen function. The newly calculated cell value is stored in the output raster, at the same location. Then the window moves one cell further to the right (neighborhood B, Figure 9). The processing cell has also moved one cell further to the right (Figure 9). The calculation is repeated for this new processing cell. The result is again stored in the output raster dataset. Then the window moves again one cell further to the right.and so on, until it reaches the last cell of the input raster dataset layer. Figure 10 illustrates the calculation of a neighborhood statistic focal sum. The upper part of Figure 10 shows the function for a 3x3 rectangular neighborhood. The processing cell has value 2. The same cell in the output raster will get the value of the sum of the processing cell value plus the values of the neighboring cells; in this case the sum equals 21. So a value of 21 is assigned to the cell in the output raster at the same location as the processing cell in the input raster. The lower part of Figure 10 shows the result for an entire raster dataset. Figure 10. Illustration of the calculation of the neighborhood statistic focal sum. If a cell with the value of NoData is present in the neighborhood, it will be ignored in the processing, on contrary with NoData cells in local operations. However, if the entire neighborhood consists of cells of NoData, the output cell value will be NoData!! It is beyond the scope of this course to explain why ArcMap treats the value of NoData different during focal operations than during local operations. The course Geo-information Tools (GRS 20806) will elaborate on the treatment of NoData values during processing. Focal (neighborhood) statistics INSTRUCTIONS: 1. Open ArcToolbox. Click the Spatial Analyst Tools Neighborhood Focal Statistics. 2. Choose the Input raster dataset you want to calculate a statistic for. 7-9

3. Specify the name and location of the output raster in the Output raster box. 4. Click the Neighborhood dropdown arrow to select a neighborhood shape. The available neighborhoods are Annulus, Circle, Rectangle and Wedge. 5. Specify height and width of the neighborhood. Set Units to Cell. 6. From the Statistic type dropdown list, choose a statistic. The available statistics are Minimum, Maximum, Range, Sum, Mean, Standard Deviation, Variety, Majority, Minority and Median. 7. Click OK. 5. Activate data frame Focal. a. Calculate for raster dataset dem the neighborhood statistic mean. Use the following setting: - Name the raster dataset focal_mean. Save it in your workspace. - Use a rectangular neighborhood. - The neighborhood size: 9x9 cells. b. Choose the same symbology for the output raster as the elevation raster. Explain the effects of this focal mean operation. c. Calculate the neighborhood statistic maximum for raster dataset lu_raster. Use the same neighborhood settings described above. d. Do the calculated values have any meaning? Use the word data scale or measurement scale in your answer. 7-10

Zonal operations A zone is where all cells in a raster have the same value, regardless of whether or not they are contiguous. A zone represents one thematic class, for example buildings of thematic raster dataset land use. Zonal functions are similar to focal functions except that the definition of the neighborhood in a zonal function is the configuration of the zones of the input dataset and not a specified neighborhood shape. ArcMap offers a variety of zonal operations which can be found in Spatial Analyst toolbox (Zonal toolset) of ArcToolbox. In this module we will discuss two zonal operations: Zonal Statistics and Zonal Area. Zonal statistics The Zonal Statistics function calculates statistics for each zone (see Module 2 for a definition fo Zone ) defined by a zone dataset, based on values from another dataset (the value raster) found within a zone (Figure 11). This could be average population density per zone of pollution or most common vegetation type per zone of elevation. The output of this operation can be presented in a (dbf) table or as raster dataset. During this course only tabular output is created. The zone dataset can be vector or raster data. The value raster must be a raster dataset. With an integer input value raster the statistics are: area, minimum, maximum, range, mean, standard deviation, sum, variety, majority, minority, and median. If the input values are of floating-point data type, the zonal calculations for majority, median, minority and variety are not available. 4 2 1 Zonal mean 3 3 3 5 5 3 4 4 4 a b 2 5 5 c 4 4 3 Figure 11. The zone dataset (a) defines zones, in this case there are two zones. Zones can for example be land use types. The value raster (b) contains the input values used in calculating the output for each zone. These can for example be elevation values. The zonal function mean would return output (c). The average elevation value is calculated for each zone (check this). All cells in the output raster that belong to the same zone receive the same value, in this case the average elevation within each zone. Note that in this example raster output is given. In the following exercises tabular output is created. INSTRUCTIONS: 1. Open ArcToolbox. Click Spatial Analyst Tools Zonal Zonal Statistics as Table. 2. Click the Input raster or feature zone data dropdown arrow and choose the vector or raster dataset that defines the zones. Statistics will be calculated for each zone of this raster dataset, based on the information in the value raster (step 4). 3. Click the Zone field dropdown arrow and choose the field containing the attribute values which define the zones. 4. Click the Value Raster dropdown arrow and choose the input raster. This raster supplies the values that are used to calculate statistics for each zone of the zone dataset (step 2). 5. Specify the name and location (your workspace) of the output table. 6. Click OK. 7. To view the table, click the Source tab at the bottom of the table of contents. 7-11

6. Activate data frame Zonal. Calculate elevation statistics for every soil zone (soil type). Use SOILCODE as Zone field. Chart the mean statistic. a. What does a record in the statistic table represent? b. What is the average elevation of the gy30 (value 4) soil? c. What data scale or measurement scale should data have to calculate statistics? Calculate landuse statistics for every soil zone. Use again SOILCODE as Zone field. d. What does a record in the statistic table represent? e. Which of the attributes of the statistic table gives relevant information? Explain your answer. Zonal geometry The Zonal Geometry tool calculates several geometric properties of zones, including the area. The output is in form of a (dbf) table. INSTRUCTIONS: 7. 1. Open ArcToolbox. Click Spatial Analyst Tools Zonal Zonal Geometry as Table. 2. Click the Input raster or feature zone data dropdown arrow and choose the dataset that contains the zones you want to calculate the areas for. 3. Click the Zone field dropdown arrow and choose the field that contains the values of the zones. 4. Specify name and location of the output table. 5. Specify the processing cell size (optional) and click OK. 6. Pay attention to data management. The output tables often provide more information than you are interested in. Delete the fields that contain information that is not directly relevant for your application (see Module 2 how to delete fields)! 7. You can join the attribute table that contains the area values to the original raster dataset. Calculate the areas of the land use zones ( Lu_raster ) by using Zonal Geometry as Table and join the output table to original raster dataset. a. On which field do you have to base the join? b. What is the area covered with buildings (value 1)? c. What % of the buildings (value 1) is located on soil Holtpodzolgrond (value 4)? Hint: first use the combine function to overlay the land use raster with the soil raster. 7-12

Global operations Global functions compute an output raster dataset in which the output value at each cell location is potentially a function of the cells combined from the various input raster datasets. There are two main groups of global functions: the Euclidean and cost (or weighted distance) functions. In this module we will only treat the Euclidean distance function. The other Euclidean functions (allocation and direction) and the cost functions are beyond the scope of this course. These functions will be treated in the followup course Geo-Information Tools (GRS 20806). According map algebra, Euclidean distance is calculated from the center of the source cells to the center of each of the surrounding cells (Figure 12) that contains the value of NoData. Each cell in the output raster contains a distance value which is the distance to its nearest source cell. Source cells are given the value of zero. Be aware that the output raster is a continuous dataset with floating-point distance values. Figure 12. Calculating the Euclidean distance from a raster cell to its nearest source cell. In this module we focus on the use the Euclidean distance function for proximity analysis. Proximity analysis is used to determine the proximity of spatial features within a dataset layer or between two dataset layers. A widely applied proximity function in GIS analysis is the buffer. Buffers can be applied to both raster and vector data. The output dataset that contains the buffer zone can also be raster or vector. Euclidean distance & Buffers When you create buffer zones you select raster cells based on a specified distance from the source cells. The principle of buffering is simple. 1. Select the cells or features that will function as source. 2. Calculate the Euclidean distance to the source cells. 3. Select the raster cells based on a user-defined distance criterion. For example, if you want to create a buffer zone of 50 meters around a road, select the raster cells that have a distance value 50 meters. Note that if you calculate the Euclidean distance to vector features, a transformation must take place because the Euclidean distance function can only be applied to raster cells. However, you do NOT have to do this yourself. The transformation is done automatically by ArcMap during the process of Euclidean distance calculation!!! INSTRUCTIONS: Part 1: Euclidean distance calculation 1. Display the dataset that contains the source cells or source features. 2. Select the zone(s) or feature(s) of interest. If you do not select particular feature or zone, all will be used for as sources for Euclidean distance calculation. 7-13

3. Open ArcToolbox. Click Spatial Analyst Tools Distance Euclidean distance. 4. Select the Input raster or feature source data. This is the dataset that contains the source cells or features!! 5. Specify name and location in the Output distance raster box. 6. A Maximum distance can be specified, this is however not required. 7. Define Output cell size. Leave the Output direction raster box empty. This output cellsize does not only determine the cell size of the new raster dataset. If features from a vector dataset are used as input they are transformed to a raster dataset with the defined cell size. 8. Click OK. A raster that contains the Euclidean distances to the source cells or features is calculated. Part 2: Creating buffer zones from the Euclidean distance raster 9. Select Raster Calculator from the Spatial Analyst dropdownmenu 10. Create a query expression to select a range of distance values, which defines the buffer zone. 11. Click OK. 8. Activate data frame Global. Create a new dataset Dist_roads that contains Euclidean distance values to all road features. Do not specify a maximum distance and choose 10 m as output cell size. a. How many distance classes are distinguished in the new raster dataset Dist_roads? The number of classes is determined by an ArcMap default setting. Change the symbology with the Symbology editor. Choose map type Stretched and a color ramp to visualize the Euclidean distance raster. b. Does the Euclidean distance raster contain discrete or continuous data? Explain your answer. Use the Raster Calculator to create a buffer zone of 100 meters around the roads. c. Calculate the the area of the buffer zone? Creating raster data subsets In the previous exercise you saw that the output raster is a rectangle. The extent (borders) of the rectangle is determined by the extent of the input raster: the upper border of the output coincides with the top coordinate of the input raster, the lower border with the bottom coordinate of the input raster, etc. Datasets can, however, have different extents. When you build a GIS application it is convenient to work with datasets that have the same extent. You can control how the extent of the output raster is determined with setting the Output Extent and Mask. These two processing settings allow the user to take a geometric subset from a raster dataset. Note that the output extent and mask settings have effect on all raster operations. However, they are frequently used during buffer and reclass operations. We will therefore discuss these settings in this context. During the course Geo-information Tools (GRS 20806) the mask and output extent are discussed in more detail. 7-14

INSTRUCTIONS (Output Extent): 9. 1. Click the Tools in the menu bar. Click Options Geoprocessing Environments General settings. 2. Click the Output Extent dropdown arrow and select an extent. Note that this is an ArcMap setting. It does not change the extent of datasets that have already been created. Only datasets that are created after you changed the output extent setting, will have the specified extent. Set the Output extent to Same as Layer lu_raster. a. Create a new dataset Dist_extent that contains Euclidean distance values to all road features. Do not specify a maximum distance and choose 10 m as output cell size. b. Give the NoData values of dataset lu_raster a color. You can see that the extent of the distance raster coincides with the extent of dataset lu_raster. You created a distance raster that has the same extent as dataset Lu_raster. However, the land use dataset has an irregular shape. Parts of the distance raster fall outside the borders of the Lu_raster dataset. If you want your distance raster to have a specific spatial area, for example, the same area as the Lu_raster dataset, you have to set the Mask. The mask identifies those locations within the output extent that will be included during geoprocessing. This can be an area, like in this case, but it can also be a selection of cells or features. Cells that fall outside the mask will be assigned the value of NoData. INSTRUCTIONS (Mask): 10. 1. Click the Tools in the menu bar. Click Options Geoprocessing Environments Raster analysis settings. 2. Click the Mask dropdown arrow and select a dataset that will be used as mask. 3. You can also set the output cell size. This cell size is automatically chosen for all raster output datasets. Set the Mask to lu_raster. a. Create a new dataset Dist_mask that contains Euclidean distance values to all road features. Do not specify a maximum distance and choose 10 m as output cell size. b. Display the Dist_mask dataset in the view window and compare it with the dataset Dist_extent to see the result of a mask. 7-15

Reclassification of the Euclidean distance raster Reclassifying data simply means replacing cell values with new cell values. There are many reasons why you might want to reclassify your data. Some of the most common reasons are: to replace values based on new information; to group certain values together; to reclassify values to a common scale and; to set specific values to NoData or to assign a value to cells with NoData. There are several approaches to reclassify your data; by individual values, by ranges, by intervals or area, or through an alternative value. You can reclassify the continuous Euclidean distance raster to a discrete raster. INSTRUCTIONS: 1. Open ArcToolbox. Click Spatial Analyst Tools Reclass Reclassify. 2. Click the Input raster dropdown arrow and click the input raster. 3. Click the Reclass field dropdown arrow and click the field that contains the values you want to reclasify. 4. You can reclassify manually: set ranges for the Old values and assign a New value to each range, or you can use reclassification options under Classify button. 5. Click the Classify button. 6. Click the Method dropdown arrow and select a method: Equal interval: set the number of classes you want, ArcMap determines the interval size. Defined interval: set the interval size, ArcMap determines the number of output classes. 7. Specify a name for the output raster dataset. 8. Click OK. Be aware that you lose the original distance values during reclassification. They are replaced by a new value. 11. a. Reclassify raster dataset Dist_mask into distance classes of 50 meters. Name the dataset Recl_dist and save the dataset in your workspace. b. How many classes are distinguished? 7-16