Information about the structure of the landscape is obtained by overlaying a set of sampling areas on top of a specified part (the sampling frame of a map layer, and then calculating specific structural measures for the part of the map layer that corresponds to the area in each sampling area.
To setup a sampling frame click on SAMPLING FRAME in the main menu. The program will ask "Will the sampling frame (total area within which sampling units are distributed) be the whole map? (y/n) [y]" Just hit a carriage return to accept the default, which is to use the whole map. You do not need to setup a sampling frame if you want to use the whole map, as this is the default. To setup a different sampling frame type "n" in response to this question. Then use the mouse and a rubber band box to outline a rectangular sampling frame on screen. This box will be moved to the nearest row and column of the map. You will be asked last whether you want to "Refresh the screen before choosing more setup?" If you don't like the sampling frame you just setup, answer yes to this question, then click on SAMPLING FRAME again to redo this part of the setup. This sampling frame will be used in all subsequent setup procedures unless you change it. You can change it at any time by simply clicking on SAMPLING FRAME again.
A sampling area may be one of four things. First, it is possible to treat the entire map layer as the one (and only) sampling area. Second, if the map layer can be divided into meaningful geographical regions, then it is possible to treat the regions themselves as sampling areas. The third option is that the sampling areas may be sampling units of fixed shape and size (also called scale) that are placed within the map layer as a whole. The fourth and final option is that the sampling area may be moved systematically across the map as a moving window.
If regions are to be used as the sampling areas , then the user can use r.le.setup to draw regions or any existing map of regions can simply be used directly. To draw regions and create a new regions map in r.le.setup select "REGIONS" from the first r.le.setup menu, and the user is asked to do the following:
1. "ENTER THE NEW REGION MAP NAME:". Only a new raster map name is acceptable. The user can type LIST to find out the existing raster map names in this location and mapset. 2. "PLEASE OUTLINE REGION # 1". The user should move the mouse cursor into the graphic monitor window and use the mouse buttons as instructed: Left button: where am I.to display the current coordinates of the cursor. Middle button: Mark start (next) point. to enter a vertex of the region boundary. Right button: Finish region-connect to 1st point to close the region boundary by setting the last vertex to be equal to the first one. 3. A "REGION OPTIONS:" menu is displayed and the user should use the mouse to select one of the options:
"DRAW MORE": repeat the above process and setup another region. "START OVER": abandon the previous setup and start all over again. "DONE-SAVE": save the regions outlined so far and exit this procedure. "QUIT-NO SAVE": quit the procedure without saving the regions.
The user can also use the GRASS r.digit or v.digit programs to digitize circular or polygonal regions and to create a sampling regions map without using r.le.setup. Or, as mention above, an existing raster map can be used as a regions map.
If sampling units are to be used as the sampling areas (Fig. 2), then choose "SAMPLING UNITS" from the first r.le.setup menu. The program checks the r.le.para subdirectory for an existing "units" file from a previous setup session and allows the user to rename this file (to save it) before proceeding. The r.le.setup program will otherwise overwrite the "units" file. Then the following choice is displayed followed by a series of other choices:
Which do you want to do? (1) Use the keyboard to enter sampling unit parameters (2) Draw the sampling units with the mouse Enter 1 or 2:
If the choice is made to define sampling units using the keyboard, the following series of questions must be answered:
How many different SCALES do you want (1-15)?
Sampling units must be placed spatially into the landscape. There are five options for doing this :
Sampling units are placed in the landscape by randomly choosing numbers that specify the location of the upper left corner of each sampling unit, subject to the constraint that successive sampling units not overlap other sampling units or the edge of the landscape, and that they must be entirely within the area defined by the mask (see r.mask command) if one exists.
Sampling units are placed side by side across the rows. The user will be able to enter a row and column to indicate where the upper left corner of the systematic contiguous framework should be placed. Rows are numbered from the top down beginning with row 1 of the sampling frame. Columns are numbered from left to right, beginning with column 1 of the sampling frame. A random starting location can be obtained by using a standard random number table to choose the starting row and column. The r.le.setup program does not avoid placing the set of sampling units over areas outside the mask. The user will have to make sure that sampling units do not extend outside the mask by choosing a particular starting row and column or by drawing a sampling frame before placing the set of sampling units.
The user must specify the starting row and column as in #2 above and the amount of spacing (in pixels) between sampling units. Horizontal and vertical spacing are identical. Sampling units are again placed side by side (but spaced) across the rows. As in #2 the program does not avoid placing sampling units outside the masked area; the user will have to position the set of units to avoid areas outside the mask.
The strata are rectangular areas within which single sampling units are randomly located. The user must first specify the starting row and column as in #2 above. Then the user must specify the number of strata in the horizontal and vertical directions. As in #2 the program does not avoid placing sampling units outside the masked area; the user will have to position the set of units to avoid areas outside the mask.
Centered over sites
The user must specify the name of a sitefile containing point locations. A single sampling unit is placed with its center over each site in the site file. This is a useful approach for determining the landscape structure around points, such as around the location of wildlife observations.
The user is prompted to enter a ratio that defines the shape of the sampling units. Sampling units may have any rectangular shape, including square as a special case of rectangular. Rectangular shapes are specified by entering the ratio of columns/rows (horizontal dimension/vertical dimension) as a real number. For example, to obtain a sampling unit 10 columns wide by 4 rows long specify the ratio as 2.5 (10/4).
Recommended maximum SIZE is m in x cell total area.
What size (in cells) for each sampling unit of scale n?
The nearest size is x cells wide X y cells high = xy cells Is this size OK? (y/n) [y] Maximum NUMBER of units in scale n is p? What NUMBER of sampling units do you want to try to use?
Is this set of sampling units OK? (y/n) [y]
The choice is made to define sampling units using the mouse, then the following menu for use with the mouse is displayed:
Outline the standard sampling unit of scale n. Left button: Check unit size Middle button: Move cursor Right button: Lower right corner of unit here
Outline more sampling units of scale n? Left button: Exit Middle button: Not used Right button: Lower right corner of next unit here
Using this procedure a rectangular "window" or single sampling area is moved systematically across the map to produce a new map (Fig. 2,3). This sampling procedure can only be used with the measures that produce a single value or with a single class or group when measures produce distributions of values (Table 1). The first class or group specified when defining class or group limits (section 2.3.2.) is used if distributional measures are chosen with the moving window sampling method. In this case, the user should manually edit the r.le.para/recl_tb file so that the desired group is listed as the first group in this file.
Sampling begins with the upper left corner of the window placed over the upper left corner of the sampling frame. It is strongly recommended that the user read the section on the GRASS mask (section 2.2.2) prior to setting up the moving window, as this mask can be used to speed up the moving window operation. The value of the chosen measure is calculated for the window area. This value is assigned to the location on the new map layer corresponding to the center pixel in the window if the window has odd (e.g. 3 X 3) dimensions. The value is assigned to the location on the new map layer corresponding to the first pixel below and to the right of the center if the window has even dimensions (e.g. 6 X 10). If this pixel has the value "0," which means "no data" in GRASS, then this pixel is skipped and a value of "0" is assigned to the corresponding location in the new map. The window is then moved to the right (across the row) by one pixel, and the process is repeated. At the end of the row, the window is moved down one pixel, and then back across the row. This option produces a new map layer, whose dimensions are smaller by approximately (m-1)/2 rows and columns, where m is the number of rows or columns in the window.
If the "MOVE-WINDOW" option in the main menu is selected, first the program checks for an existing "move_wind" file, in the r.le.para subdirectory, containing moving window specifications from a previous session. The user is given the option to avoid overwriting this file by entering a new file name for the old "move_wind" file. Users should be aware that moving window analyses are very slow, because a large number of sampling units are, in effect, used. See the appendix on "Time needed to complete analyses with the r.le programs" for some ideas about how moving window size and sampling frame area affect the needed time to complete the analyses.
The r.le programs r.le.dist and r.le.patch allow the attribute categories in the input map to be reclassed into several attribute groups, and reports the analysis results by each of these attribute groups. It is necessary to setup group limits for all measures that say "by gp" when typing "r.le.dist help" or "r.le.patch help" at the GRASS prompt. The same reclassing can be done with the measurement indices (e.g., size), except that each "cohort" (class) of the reclassed indices is called an index class instead of a group. It is also necessary to setup class limits for all measures that say "by class" when typing "r.le.dist help" or "r.le.patch help" at the GRASS prompt.
Group/class limits are setup by choosing "GROUP/CLASS LIMITS" from the main menu upon starting r.le.setup, or you can create the files manually using a text editor. The program checks for existing group/class limit files in subdirectory r.le.para and allows the user to rename these files prior to continuing. If the files are not renamed the program will overwrite them. The files are named recl_tb (attribute group limits), size (size class limits), shape_PA (shape index class limits for perimeter/area index), shape_CPA (shape index class limits for corrected perimeter/area index), shape_RCC (shape index class limits for related circumscribing circle index), and from_to (for the r.le.dist program distance methods m7-m9).
Attribute groups and index classes are defined in a different way. In the r.le programs attribute groups are defined as in the following example:
1, 3, 5, 7, 9 thru 21 = 1 (comment) 31 thru 50 = 2 (comment) end
The GRASS reclass convention is adopted here with a little modification (see "r.reclass" command in the GRASS User's Manual). The difference is that r.le only allows one rule for each group while the GRASS r.reclass command allows more than one. The definition of "from" and "to" groups is simply the extension of the GRASS reclass rule. The advantage of using the GRASS reclass convention is that the user can generate a permanent reclassed map, using GRASS programs, directly from the r.le setup results.
The r.le measurement index classes are defined by the lower limits of the classes, as in the following example:
0.0, 10.0, 50.0, 200.0, -999
if v >= 0.0 and v < 10.0 then v belongs to index class 1; if v >= 10.0 and v < 50.0 then v belongs to index class 2; if v >= 50.0 and v < 200.0 then v belongs to index class 3; if v >= 200.0 then v belongs to index class 4;
Last changed: $Date: 2002/01/25 05:45:34 $