Raster Data Model & Analysis

Transcription

1 Topics: 1. Understanding Raster Data 2. Adding and displaying raster data in ArcMap 3. Converting between floating-point raster and integer raster 4. Converting Vector data to Raster 5. Querying Raster data 6. Creating a Histogram 7. Raster classification 8. Mapping Distance 9. Creating an allocation map 10. Zonal Statistics 11. Performing a Map Query and Map calculation 1. Understanding a raster dataset A raster dataset, like a map, describes the features and characteristics of an area and their relative positions. A single raster typically represents a single theme. Multiple raster datasets should be produced to fully depict an area. The Raster Data Structure A raster dataset is made up of cells/pixels. Cells are arranged in rows and columns, an arrangement that produces a Cartesian matrix. The rows of the matrix are parallel to the x-axis of the Cartesian plane, and the columns to the y-axis. Each cell/pixel is a square that represents a specific portion of an area. All cells in a raster must be the same size. The cells in a raster dataset can be any size that you desire, but they should be small enough to accomplish detailed analysis. Each cell has a unique row and column address. All locations in a study site are covered by the matrix. Raster data is generally divided into two categories: Thematic data and Image data Thematic data: The values in thematic raster data represent some measured quantity or classification of a particular phenomena, such as elevation, pollution concentration, or population. Image data: The values of cells in an image represent reflected or emitted light or energy, such as that of a satellite image or scanned photograph. The Spatial Analyst tools are primarily intended for use on thematic raster data. Raster Data Type: The data type in raster is either Integer (Discrete data) or Floating point (Continuous data) Discrete data Categorical data, sometimes called discrete data, most often represent objects. These objects usually belong to a class, a category or a group. A categorical object has known and definable boundaries. UNBC 2017 ~ 1 ~

2 An integer value is normally associated with each cell in a categorical grid, which defines the group, class or category the cell belongs to. All integer raster include a table called a value attribute table (VAT). The VAT always contains at least two items: VALUE and COUNT. VALUE is the value assigned to the cell in the grid, and COUNT is the total number of cells in the grid that are assigned the value. Any additional items representing other attributes of the group, class or category can be added or related to the VAT. Continuous data Continuous data are usually represented by a grid with floating-point values (referred to as a floating-point grid). The value for each cell in the grid is based on a fixed point, such as sea level; a compass direction or the distance of each location from a phenomenon in a specified measurement system (such as the noise in decibels at various sites near an airport). Floating-point grids do not have a VAT. 2. Adding and displaying raster data in ArcMap Create a new folder raster under your geog300 folder Open a new map file and add dem.tif and features from L:\labs\geog300\unbc Most functions applied on raster analysis are provided by the Spatial Analyst extension. Before doing any work, make sure you have Spatial Analyst extension enabled. Click Customize->Extension on the top menu bar. Make sure the check box is checked beside Spatial Analyst and 3D Analyst. Click Close Raster working environment NOTE: whenever you work with raster data, you need to set the raster working environment. This is a very important step, otherwise it may cause some issues when generating raster dataset. Setting the raster analysis environment enables you to control the output directory for your results, the analysis extent, and the cell size. It also enables you to specify an analysis mask and a snapping extent if appropriate. The major environment includes: Workspace: Analysis extent: Analysis Mask: Cellsize: the output raster directory the output raster extent Analysis mask the cell size of output raster Click Geoprocessing->Environments from the top menu bar to open the Environment Setting Expand Workspace to set the workspace to K:\geog300\raster Click Processing Extent and select Same as dem.tif for the output extent Click Raster Analysis and set cell size Same as dem.tif from the dropdown list. This will result all output raster data have the same cell size as dem.tif. Click OK to close the window. Right-click on dem.tif and choose Proprieties. In the Symbology tab, change the color ramp to a colorful color pattern. Click Apply. Query the raster value with Identify tool You can use button to query the raster cell value. dem.tif is a digital elevation mode and each cell value represents the elevation at the location Click the button and click a place in display area (within dem.tif area), the Identify Results window pops up showing stretch value and pixel value. The stretch value is the color value assigned to a cell for display and the pixel value is the real value of a cell. In the Identify window, set dem.tif for Identify from. This will make sure you are querying dem.tif layer. The pixel value is the elevation value UNBC 2017 ~ 2 ~

3 Open the properties window of dem.tif. Under Symbololgy tab, click Classified in the Show box at left. Change the number of classes to 10 and click Apply. The dem.tif is displayed in classified mode. Query dem.tif with button again. You should see class value displayed. This is because the dem.tif is classified on display You can also use the map tips to display the elevation automatically whenever your mouse cursor is over a pixel. Right-click dem.tif and choose Properties. Click Display tab. Make the 'Show Map tips' is checked. Click OK. Now put your mouse cursor over a place in the display area of dem.tif, elevation value shows up. You can also examine the statistics information of a raster dataset. Right-click dem.tif and choose Properties->Source. Here you can find all information about this raster. 3. Converting between floating-point raster and integer raster Tabular queries are useful in some cases to extract information from a dataset. But tabular queries can be only performed on integer raster dataset. To take the advantage of tabular queries, conversion from floating-point values to integer values is needed to create a raster theme with a VAT table (Value Attribute Table). In ArcToolbox, click Spatial Analyst->Map Algebra->Raster Calculator The Raster Calculator window pops up. Here you can build map algebra expression to overlay rasters on cell based calculation. The left part of the window lists all raster layers available, the middle part is for numbers and operators and the right part is a list of functions that can be applied on raster calculation Double-click the function Int from the function list and then double click dem from the layers list. You should see an expression like the following: Int( dem.tif ) This function will convert the floating point (continuous data) dem.tif to an integer dem. Set the Output Raster to K:\geog300\raster\dem_int. The result will be saved as dem_int in your local folder. Click OK. As the integer raster has a VAT table associated, so the raster can be queried based on attributes. Open the attribute table of dem_int and examine the content. It should come with Value and Cont fields. The Value field indicates the elevation value and the Cont field provides the total number of cells with the value. Be aware that this conversion may incur a loss of information. Be very careful when converting floating-point to integer value, especially if your original values are between 0 and 1. You will lose most of your information. If your data represent values for which decimal places contain important information and you convert to integer values, you will lose that important information. Also building a VAT for an integer raster that has so many unique values is a slow process. Before converting a floating point raster to an integer raster, you should check the histogram of the raster to see if it is suitable to convert to integer data. Right-click dem_int and choose Properties. Click the Source tab, here you can find all the statistical information on this raster including cell size, rows, columns, max, min, mean and standard deviation values. UNBC 2017 ~ 3 ~

4 4. Converting Vector data to Raster Vector data can be converted to a raster dataset using the attributes. Remember that one raster dataset can only represent one type of information (theme: such as age, temperature, elevation, etc). Let's convert fcover to raster using fcover-id as the raster cell value. You can convert fcover using any attribute in the table as the raster cell value. The reason we choose fcover-id is that we can join the fcover attribute table to the raster VAT table after conversion so we can query the raster using the attributes from original fcover dataset. Add fcover from L:\labs\geog300\unbc In the ArcToolbox, click Conversion Tools->To Raster->Polygon to Raster. Input Features fcvoer Value Field fcover_id Output Raster K:\geog300\raster\fc_ras Click OK to run the tool. Turn off fcover in the table of content. The raster dataset fc_ras represents the fcover-id which is the polygon id from original fcover dataset. Right-click fc_ras and choose Open Attribute Table to examine the VAT table. Two data fields are created in the table: Value and Count. The Value data field stores the value from fcover-id (fcover) and the Count field tells you the total number of cells having that value. Now do the following conversions yourself and save the output in your local folder raster Convert fcover to raster (fc_sp1) using the primary species (SPEC_CD_1) Convert fcover to raster (fc_age) using the stand age (STAND_AGE) Convert fcover to raster (fc_ht) using the stand height (STAND_HEIG) 5. Query raster data based on attributes Now right-click dem_int and choose Open Attribute Table. Click the first dropdown button at upper left and choose Select by In the query builder window, build a query like the following. This query will select all the elevation cells greater or equal to 800. Click Apply. The selected cells are highlighted. Value >= 800 elevation >= 800 fc_ras classified based on fcover_id Now turn off dem.tif, dem _int. Turn on fc_ras to view the forest coverage. The cell value in fc_ras represents the fcover_id (polygon ID). The data type is integer. Change the Symbology of fc_ras. Open the Properties window. Click Symbology tab. Click Unique Values in the Show box. Choose a color ramp. Click Add all Value button to add values. Click Apply. You should see that the cells with the same color form up the polygon. UNBC 2017 ~ 4 ~

5 The values in Value field indicate the polygon ID (fcover_id) in the vector fcover and the values in Count Field tells you the total number of cells with the value in Value field. There is not much useful information that describes each polygon. We have the attribute table for fcover that can be joined to this VAT to bring in some valuable information. Remember how to join two tables together? Join the attribute table of fcover to fc_ras table using the join field Value in fc_ras and fcover_id in fcover Right-click on fc_ras and choose Open the attribute table. Examine the attributes in the table. All attributes from fcover are appended into the fc_ras VAT table. This table can now be used for query. In the attribute table of fc_ras, click the first dropdown button at upper left and choose Selection By Attributes. Build an attribute query expression to locate the areas with Spruce as the leading species. You may see a table name showing as prefix of the field for the joined table (fcover) fcover.spec_cd_1= S This will select all the cells with Spruce as leading species. The selected cells are highlighted in cyan color in both the table and the display window. 6. Creating a Histogram Histograms graphically display the spread of a cell value within the selected cells of a grid theme. Now turn on the Spatial Analyst toolbar by clicking Customize->Toolbar->Spatial Analyst Clear the selection on dem if necessary Open the Properties of dem_int. Under Symbology tab, choose Classified in Show box. Set Value for Value field. Set 30 for the classes. Click Classify button and set Natural Break for Method. Click OK. On the Spatial Analyst toolbar, click the dropdown arrow and choose dem_int for Layer. Click the Histogram button on the Spatial Analyst menu bar to create histogram After a minute or two, the histogram for all cells in the theme will be displayed. The number of columns in the histogram is the same as the number of classes in the grid theme's legend. The histogram shows elevation classes on the X axis and the number of cells within those classes on the Y axis. The Class-label shows the range of values in that class (which is the same thing shown on the legend for the X axis) and the COUNT of cells in that class (which is the same thing shown on the Y axis). Histograms are useful for browsing the range and distribution of data in a grid. Do the values of a grid follow a normal distribution, or is there some other type of pattern? What might that tell you about your data, and what implications does it have for further analysis? 7. Raster Reclassification In some cases, we do not need very detailed information. Instead, we are interested in categories of the values falling in. In this case, we can classify the raster into groups (categories) First we will change the symbology of dem_int to 7 classes with 50 as the interval UNBC 2017 ~ 5 ~

6 Right-click dem_int and open the properties window. Click Symbology tab and click classified in the Show box at left. Change the class to 7 and click Classify button right beside Here we can change the range values for each class. Click and highlight the top value in the Break Values box and type in 600. Then highlight the second value and type in 650. Type in the rest of range values 700, 750, 800, 850 and 900. Click OK to close the properties window. We only changed the display of the dataset, no permanent raster is generated with the classification values In ArcToolbox, click Spatial Analyst->Reclass->Reclassify. Input Raster dem_int Reclass field VALUE Output Raster K:\geog300\raster\dem_int7 Click OK. You may see that all reclassified classes are listed here. If not, click the Classify button and assign the range values. The Old Values field shows the range of values of regional raster and the New Values indicate the values that will be assigned to each class. The resulting raster will have the new value for each cell that falls into the range values. You can change the range values if necessary. Right-click dem_int7 and Open the Properties window. Click Symbology tab and choose Unique value in the Shows box and click OK. Each color corresponds to a class Add slope and aspect you created in DEM lab from your local folder. Reclassify slope into 10 classes with interval of 5. Save the output raster as slp_class10 Reclassify aspect into 10 classes with interval of 40. Save the output raster as asp_class10 Each number value represents a range value of slope and aspect respectively. Reclass of Slope Range Values Reclass of Aspect Range Values UNBC 2017 ~ 6 ~

7 8. Mapping Distance In this part of lab, we will explore more raster based analysis Open a new map file and add creeks, fcover, dem and samples from L:\labs\geog300\unbc. Turn off fcover and dem.tif for now Make sure you have Spatial Analyst extension enabled. Turn on the Spatial Analyst toolbar if necessary Set the raster analysis environment as the following: Workspace: Processing Extent: Raster Cell Size: K:\geog300\raster Same as fcover Same as dem.tif The distance mapping functions are global functions. It computes an output raster dataset where the output value at each location is potentially a function of all the cells in the input raster datasets. By mapping distance, you can find information such as the distance to the nearest hospital from a certain area, an emergency helicopter or find all fire hydrants within 500 meters of a burning building. Alternatively, you could find the shortest (or least-cost) path from one location to another based on some cost factor. We will examine some Euclidean functions. Euclidean Distance calculates, for each cell, the Euclidian distance to the closest source. In another words, it measures the straight line distance from each cell to the closest source. Euclidean direction calculates, for each cell, the direction, in degrees, to the nearest source. This function assigns each cell the value of the source to which it is closest. The nearest source is determined by the Euclidean Distance. Euclidean allocation calculates, for each cell, the nearest source based on Euclidean distance The Euclidean Distance function This function measures the straight line distance from each cell to the closest source (the source identifies the objects of interest such as wells, roads, or a school). The distance is measured from cell center to cell center. In ArcToolbox, click the Spatial Analyst->Distance-> Euclidean Distance Input Raster creeks Output Raster K:\geog300\raster\dist_creeks Leave everything else as it is and click OK. You can easily query the raster now. Here the cell values are the straight distance to the closet source (creeks). Assume that we are looking for the areas within 100 metres distance of creeks In ArcToolbox, click Spatial Analyst->Map Algebra->Raster calculator. Double click dist_creeks from the Layers list and click <= operator and type in 100. You will have a raster expression like the following: dist_creeks <= 100 Set the output raster to creeks100 in your local raster folder The cells within 100 meters of creeks will be assigned value of 1 and the rest of cells will have the value of 0 UNBC 2017 ~ 7 ~

8 9. Creating an allocation map Euclidean allocation function assigns each cell with the value of the source to which it is closest. The nearest source is determined by the Straight Line Distance. This function can used to assign space to objects such as trade area, service area, school catchments area etc. Assume that the sampling locations (samples) are treated as service centres and we want to determine the service area of each service centre based on the shortest distance to the service centers. Turn off all the layers. Add samples from L:\geog300\unbc. In ArcToolbox, click the Spatial Analyst->Distance-> Euclidean Allocation Set the parameters as the following Input Raster: Source Field: Output Allocation raster: Output distance raster: Output direction raster: samples ID alloc_samples dist_samples dir_samples Click OK. Three output rasters will be generated: distance to samples (dist_samples), direction to samples (dir_samples) and alloc_samples dist_samples dir_samples alloc_samples Examine alloc_samples. The allocation area of each service centre can be clearly seen by color. The area of each allocated area can be calculated in either raster data or vector data format. Calculate the area of an allocation map in the raster data A raster VAT table is created when you apply the allocation function. The Value field contains the source ID and the Count Field tells you the total number of cells that are allocated to the source. The area for each service centre can be calculated by the following formula: The area for each source = the total number of cells x cell size x cell size Open the attribute table of alloc_samples. There should be six records as there are six sample locations. The cells with the same value determine an allocation area. Now calculate the area for the upper right allocated area indicated by ID 6. Check the total number of cells with value of 6. That is The cell size is 5 (you specified in the environment) A new field AREA can be added in the VAT table and calculate the area for each service centre with the field calculator. Add a new field AREA in the VAT with double type, 15 for precision and 1 for scale. UNBC 2017 ~ 8 ~

9 Right-click on the field AREA and choose Field Calculator. Give the following formula in the lower box to calculate the area for each source. [COUNT] * 5 * 5 (cell size is 5) Click OK. You will have area value for each service centre in the VAT table. The unit is square meter. Calculate the area of an allocation map in vector data You can also calculate the areas for allocation map in a vector data. To do this, you need first convert the raster to vector data. In ArcToolbox, click Conversion Tools->From Raster->Raster to Polygon Set the parameters as the following: Input Raster: alloc_samples Field: VALUE Output Polygon Feature: K:\geog300\raster\alloc_vector Add an AREA field and calculate the area with Calculate Geometry tool 10. Zonal Statistics Zonal Statistics function lets you calculate statistic information on the input raster for each zone defined by a zone dataset A zone is all the cells in a raster that have the same value, regardless of whether or not they are contiguous. However, both raster and feature datasets can be used as the zone dataset. So, for example, residential is a zone of a land use raster dataset or a road feature dataset can be the zone for an accident dataset. Zonal statistical functions perform operations on a per-zone basis; a single output value is computed for every zone in the input zone dataset Now turn off all layers but fcover. Turn on dem. In ArcToolbox, click Spatial Analyst->Zonal->Zonal Statistics as Table Set the parameters as the following Input Raster or Feature zone data: fcover Zone Field: fcover_id Input Value Raster: dem Output Table: fc_dem.dbf (in your local folder) Check Ignore NoData in calculations and click OK. The resulting statistics table fc_dem.dbf will be added to ArcMap. This is a table not a spatial data, so you have to join this table to the fcover feature to find out all statistics information for each polygon. The table contains all the statistics information on elevation (dem) for each fcover polygon. Join fc_dem.dbf to fcover based the join field fcover_id UNBC 2017 ~ 9 ~

10 Examine the attribute table of fcover to see what's happened there. Right-click fcover and choose Open Attribute Table. Scroll to the right, you should see some new data fields added showing as: min minimum value of elevation for each polygon max maximum value of elevation for each polygon range the range value of elevation for each polygon mean the average value of elevation for each polygon std the standard deviation value of elevation for each polygon sum the summary value of elevation for each polygon These data fields can be used to query fcover on elevation. For example, we may be interested in the polygons whose average elevation is less than 800 meters. This can be easily done with Selection by Attributes 1. Select by attribute on fcover to locate all the polygons with average elevation less and equal to 800 Now add slopes you created in your DEM lab to ArcMap. Perform Zonal Statistics analysis on slope with fcover polygon as zone boundary. 11. Performing a Map Query and Map calculation Map Query Many raster analytical operations are performed by using the Raster Calculator. Click Geoprocessing->Environments->Raster Analysis. Clear the Raster Mask field if any Add fc_age, fc_ht and fc_sp1 from your local raster folder if necessary Add aspect and slope from your local dem folder Because dem is in floating-point, an attributes query is not possible; instead, a Map Query must be used to view a subset of cells. In ArcToolbox, click Spatial Analyst->Map Algebra ->Raster Calculator. ("dem" > 800) & ("dem" < 850) Set the output raster to K:\geog300\raster\dem800_850 and click OK The cell values between 800 and 850 in dem are coded as value of 1 and the rest cell values are coded of 0 in dem800_850. A map query is similar to a normal feature attribute query. It can be performed on either floating-point or integer rasters. The output is always a new raster, rather than a selected set. The output is a boolean entity, in which out cells are coded True(1) (meet the condition), False(0) (not meet the condition), or No Data. Unlike feature queries, map queries are not limited to single themes. Map queries can select cells that match a broad range of criteria, including multiple raster themes. For example, it is possible to select a group of cells whose values are within a range of elevation, within a range of slope, and also are within a range of aspect values Map calculation ("dem">700) & (("slope">5) & ("slope"<10)) & (("aspect">45) & ("aspect"<125)) Arithmetic expression can be applied on raster operations as well. For example, the radian is the standard unit of angular measure, used in many areas of mathematics, physics and engineering. It describes the plane angle subtended by a circular arc as the length of the arc divided by the radius of the arc. In some cases, we need the angle presented in radian for some special purpose. UNBC 2017 ~ 10 ~

11 Now let's convert azimuth degree to radians. The formula is: 1 = / 180 radian With Raster Calculator, create a new raster radians in your local folder raster Build the query expression something like the following and save the output as radian in your local folder "aspect" * / 180 The raster operators and functions Arithmetic operators allow for the addition, subtraction, multiplication, and division of two rasters, numbers, or a combination of the two. Relational operators evaluate specific relational conditions. If a condition is TRUE, the output is assigned 1; if a condition is FALSE, the output is assigned 0. Boolean operators use Boolean logic (TRUE or FALSE) on input rasters on a cell-by-cell basis. Output values of TRUE are written as 1 and FALSE as 0. Bitwise operators compute on the binary representation of the input values. Arithmetic Operators Description + Addition - Subtraction * Multiplication / Division Relational Operators Description == Relational Equal To > Relational Greater Than < Relational Less Than >= Relational Greater Than or Equal To <= Relational Less Than or Equal To ^= Relational Not Equal To Bitwise Operators Description && Bitwise And Bitwise Or!! Bitwise exclusive Or << Bitwise LeftShift >> Bitwise RightShift ^^ Bitwise Not Boolean Operators And (&) Or ( ) XOr (!) Not (^) Description Finds where values are true (nonzero) in the cells of both input rasters (shown in graphic below) Finds where nonzero values are present in the cells of one or both input rasters Finds where nonzero values are present in the cells of one input raster or another input raster, but not both Finds where nonzero values are not present in the cells of a single input raster Assignment 5: Raster analysis (5%) due Thursday Oct. 26 at 12pm Part A: Let's do some exercises with the raster datasets generated from this lab: fcover, creeks, dem.tif, slope, aspect, fc_sp1, fc_age, fc_ht, dist_creeks Set working environment as the following: Workspace: your local folder Analysis extent: Same as fcover Cellsize: Same as dem.tif 1. If you do not have the datasets listed above, then generate slope and aspect from dem.tif. Convert fc_sp1, fc_age, fc_ht from fcover. Generate a distance map dist_creeks from creeks 2. With raster calculator, create a raster dataset to locate the area that meet the conditions for each exercise below. 3. Write down the raster expression applied for each exercise and calculate the total area. UNBC 2017 ~ 11 ~

12 Exercise 1: Locate the area that meet the following criteria and save the output as ex1. Within 50 meters distance of water source (creeks) Have Spruce as the leading species Exercise 2: Locate the area that meet the following criteria and save the output as ex2. Within 100 meters distance of water source (creeks) Spruces as the leading species Stand age greater than 130 years old Exercise 3: Locate the area that meet the following criteria and save the output as ex3. Slope less than 5 degrees Face south (135<aspect <225) Stand age greater than 100 years old Exercise 4: Locate the area that meet the following criteria and save the output as ex4. Spruces OR Douglas Fir as the dominant species Stand height over 20 metres Within 50 metres distance of creeks. Part B: The city of Prince George has four fire stations to serve the entire city area. Assume that we want to know the fire response area for each fire hall based on the straight distance. This can be done with Allocation function discussed in this lab. Perform an Allocation analysis for fire halls with Id as the Source field and calculate the total area in hectares for each fire station it servers. Produce a map showing the service area together with fire_halls, pg_boundary. Label each fire hall with its location. The map should come with proper title, legend, scale, the total service area for each fire station and your name. Deliverable: Data required: L:\labs\geog300\pgcity: fire_halls, pg_boundary Working environment: Workspace: your local folder Processing extent: Same as pg_boundary Raster Analysis -Cell size: 10 Raster Analysis -Mask: pg_boundary Make a title page with the course name, assignment number, your lab session, your name and studentid. Provide raster expression applied for each exercise(ex1 Ex4) and the total area in hectares. Insert all maps to WORD file Save the file as lastname_firstname_geog _a6. the file to your TA with subject Geog300 A6 NOTE: Please name the file correctly. Assignment is due Thursday Oct 26 at 5pm NO late assignment is accepted ~~~~~~~~~~~~~ The End ~~~~~~~~~~~~~ UNBC 2017 ~ 12 ~