This tool combines the functionality of the "Peuker Douglas," "D8 Contributing Area," "Stream Drop Analysis," and "Stream Definition by Threshold" tools in order to generate a stream indicator grid (1,0) where the streams are located using a DEM curvature-based method. With this method, the DEM is first smoothed by a kernel with weights at the center, sides, and diagonals. The Peuker and Douglas (1975) method (also explained in Band, 1986), is then used to identify upwardly curving grid cells. This technique flags the entire grid, then examines in a single pass each quadrant of 4 grid cells, and unflags the highest. The remaining flagged cells are deemed 'upwardly curved', and when viewed, resemble a channel network. This proto-channel network sometimes lacks connectivity, and/or requires thinning, issues that were discussed in detail by Band (1986). The thinning and connecting of these grid cells is achieved here by computing the D8 contributing area using only these upwardly curving cells. An accumulation threshold on the number of these cells is then used to map the channel network where this threshold is optionally set by the user, or determined via drop analysis.
If drop analysis is used, then instead of providing a value for the accumulation threshold, the accumulation threshold value is determined by searching the range between the Drop Analysis Parameters "Lowest" and "Highest", using the number of steps in the parameter "Number". For the science behind drop analysis, see Tarboton, et al. (1991, 1992), and Tarboton and Ames (2001). The value of accumulation threshold that is selected is the smallest value where the absolute value of the t-statistic is less than 2. This is written to the drop analysis table text file. Drop analysis is only possible when outlets have been specified, because if an entire grid domain is analyzed, as the threshold varies, shorter streams draining off the edge may not meet the threshold criterion and be excluded from the analysis. This makes defining drainage density problematic and it is somewhat inconsistent to compare statistics evaluated over differing domains.
There is no usage for this tool.
PeukerDouglasStreamDef (Input_Elevation_Grid,
Input_D8_Flow_Direction_Grid, Weight_Center, Weight_Side, Weight_Diagonal,
Accumulation_Threshold, Check_for_Edge_Contamination, {Input_Outlets},
{Input_Mask_Grid}, {Input_D8_Contributing_Area_for_Drop_Analysis},
Input_Number_of_Processes, Output_Stream_Source_Grid,
Output_Accumulated_Stream_Source_Grid, Output_Stream_Raster_Grid,
{Output_Drop_Analysis_Table},
Use_the_range_below_to_automatically_select_threshold_by_drop_analysis,
Minimum_Threshold_Value, Maximum_Threshold_Value, Number_of_Threshold_Values,
Use_Logarithmic_spacing_for_threshold_values)
Parameter | Explanation | Data Type |
---|---|---|
Input_Elevation_Grid | Dialog
Reference This input is a grid of elevation values. As a general rule, it is recommended that you use a grid of elevation values that have had the pits removed for this input. Pits are generally taken to be artifacts that interfere with the analysis of flow across them. This grid can be obtained as the output of the "Pit Remove" tool, in which case it contains elevation values where the pits have been filled to the point where they just drain. There is no python reference for this parameter. |
Raster Layer |
Input_D8_Flow_Direction_Grid | Dialog
Reference This input is a grid of flow directions that are encoded using the D8 method where all flow from a cells goes to a single neighboring cell in the direction of steepest descent. There is no python reference for this parameter. |
Raster Layer |
Weight_Center | Dialog
Reference This input is the center weight used by a kernel to smooth the DEM before the tool identifies upwardly curved grid cells. There is no python reference for this parameter. |
Double |
Weight_Side | Dialog
Reference This input is the side weight used by a kernel to smooth the DEM before the tool identifies upwardly curved grid cells. There is no python reference for this parameter. |
Double |
Weight_Diagonal | Dialog
Reference This input is the diagonal weight used by a kernel to smooth the DEM before the tool identifies upwardly curved grid cells. There is no python reference for this parameter. |
Double |
Accumulation_Threshold | Dialog
Reference This input is used as the accumulation threshold on the number of upwardly curved cells, that is used to identify the beginning of streams. This value must be provided unless drop analysis is used. There is no python reference for this parameter. |
Double |
Check_for_Edge_Contamination | Dialog
Reference This flag determines whether the tool should check for edge contamination. Edge contamination is defined as the possibility that a value may be underestimated due to grid cells outside of the domain not being considered when determining contributing area. This occurs when drainage is inwards from the boundaries or areas with no data values for elevation. The algorithm recognizes this possibility and reports no data for the contributing area value. It is common to see streaks of no data values extending inwards from boundaries along flow paths that enter the domain at a boundary. This is the desired effect, and indicates that values for these grid cells is unknown due to it being dependent on terrain outside of the available data. Edge contamination checking may be overridden in cases where you know it is not an issue, or want to ignore the problems, if for example, the DEM has been clipped along a watershed outline. There is no python reference for this parameter. |
Boolean |
Input_Outlets (Optional) | Dialog
Reference This optional input is a point feature defining the outlets of interest. If this input is used, the tool will only evaluate the area upslope of these outlets. If drop analysis is being used, this file must be provided. There is no python reference for this parameter. |
Feature Layer |
Input_Mask_Grid (Optional) | Dialog
Reference This optional input is a grid that is used to mask the domain of interest and output is only provided where this grid is valid, i.e. does not contain a no-data value and whose value is greater than 0. A common use of this input is to use a D-infinity contributing area grid as the mask so that the delineated stream network is constrained to areas where D-infinity contributing area is available, replicating the functionality of an edge contamination mask. There is no python reference for this parameter. |
Raster Layer |
Input_D8_Contributing_Area_for_Drop_Analysis (Optional) | Dialog
Reference This input is a grid of contributing area values for each cell that were calculated using the D8 algorithm. The contributing area for a cell is the sum of its own contribution plus the contribution from all upslope neighbors that drain to it, measured as a number of cells or the sum of weight loadings. This grid can be obtained as the output of the "D8 Contributing Area" tool. If drop analysis is being used, this file must be provided as it is used to evaluate drainage density. There is no python reference for this parameter. |
Raster Layer |
Input_Number_of_Processes | Dialog
Reference This input indicates the number of stripes that the domain will be divided into and the number of MPI parallel processes that will be spawned to evaluate each piece of the domain. There is no python reference for this parameter. |
Long |
Output_Stream_Source_Grid | Dialog
Reference This output is an indicator grid (1,0) of upward curved grid cells according to the Peuker and Douglas algorithm, and if viewed, resembles a channel network. This proto channel network generally lacks connectivity and requires thinning, issues that were discussed in detail by Band (1986). There is no python reference for this parameter. |
Raster Dataset |
Output_Accumulated_Stream_Source_Grid | Dialog
Reference This output grid is the accumulated area in the D8 direction of just the upwardly curved grid cells that were determined according to the Peuker and Douglas algorithm. This accumulation serves to thin and connect the proto channel network defined in the output strean source grid. There is no python reference for this parameter. |
Raster Dataset |
Output_Stream_Raster_Grid | Dialog
Reference This output is an indicator grid (1,0) that indicates the location of streams, with a value of 1 for each of the stream cells and 0 for the remainder of the cells. There is no python reference for this parameter. |
Raster Dataset |
Output_Drop_Analysis_Table (Optional) | Dialog
Reference This output is a comma delimited text file with the following header line: Threshold, DrainDen, NoFirstOrd, NoHighOrd, MeanDFirstOrd, MeanDHighOrd, StdDevFirstOrd, StdDevHighOrd, T The file then contains one line of data for each threshold value examined, and then a summary line that indicates the optimum threshold value. This technique looks for the smallest threshold in the range where the absolute value of the t-statistic is less than 2. For the science behind the drop analysis see Tarboton et al. (1991, 1992), Tarboton and Ames (2001). This output is only generated if drop analysis is used. There is no python reference for this parameter. |
File |
Use_the_range_below_to_automatically_select_threshold_by_drop_analysis | Dialog
Reference This flag indicates whether drop analysis should be used to determine the optimal accumulation threshold value. Otherwise, the accumulation threshold parameter above will be used. There is no python reference for this parameter. |
Boolean |
Minimum_Threshold_Value | Dialog
Reference This value is the lowest end of the range searched for possible threshold values using drop analysis. This technique looks for the smallest threshold in the range where the absolute value of the t-statistic is less than 2. For the science behind the drop analysis see Tarboton et al. (1991, 1992), Tarboton and Ames (2001). There is no python reference for this parameter. |
Double |
Maximum_Threshold_Value | Dialog
Reference This value is the highest end of the range searched for possible threshold values using drop analysis. This technique looks for the smallest threshold in the range where the absolute value of the t-statistic is less than 2. For the science behind the drop analysis see Tarboton et al. (1991, 1992), Tarboton and Ames (2001). There is no python reference for this parameter. |
Double |
Number_of_Threshold_Values | Dialog
Reference The number of steps to divide the search range into when looking for possible threshold values using drop analysis. This technique looks for the smallest threshold in the range where the absolute value of the t-statistic is less than 2. For the science behind the drop analysis see Tarboton et al. (1991, 1992), Tarboton and Ames (2001). There is no python reference for this parameter. |
Double |
Use_Logarithmic_spacing_for_threshold_values | Dialog
Reference This flag indicates whether a logarithmic or linear spacing should be used when looking for possible threshold values using drop ananlysis. There is no python reference for this parameter. |
Boolean |
There are no code samples for this tool.
There are no tags for this item.
There are no credits for this item.
There are no use limitations for this item.