Label | Explanation | Data Type |
Input feature data | The input features containing the z-values to be interpolated into a surface raster. Each feature input can have a field specified that contains the z-values and one of six types specified.
There are nine types of accepted inputs:
| TopoInput |
Output surface raster | The output interpolated surface raster. It is always a floating-point raster. | Raster Dataset |
Output cell size (Optional) | The cell size of the output raster that will be created. This parameter can be defined by a numeric value or obtained from an existing raster dataset. If the cell size hasn't been explicitly specified as the parameter value, the environment cell size value will be used if specified; otherwise, additional rules will be used to calculate it from the other inputs. See the usage section for more detail. | Analysis Cell Size |
Output extent (Optional) | Extent for the output raster dataset. Interpolation will occur out to the x and y limits, and cells outside that extent will be NoData. For best interpolation results along the edges of the output raster, the x and y limits should be smaller than the extent of the input data by at least 10 cells on each side. The default extent is the largest of all extents of the input feature data.
| Extent |
Margin in cells (Optional) | Distance in cells to interpolate beyond the specified output extent and boundary. The value must be greater than or equal to 0 (zero). The default value is 20. If the Output extent and Boundary feature datasets are the same as the limit of the input data (the default), values interpolated along the edge of the DEM will not match well with adjacent DEM data. This is because they have been interpolated using one-half as much data as the points inside the raster, which are surrounded on all sides by input data. The Margin In Cells option allows input data beyond these limits to be used in the interpolation. | Long |
Smallest z value to be used in interpolation (Optional) | The minimum z-value to be used in the interpolation. The default is 20 percent below the smallest of all the input values. | Double |
Largest z value to be used in interpolation (Optional) | The maximum z-value to be used in the interpolation. The default is 20 percent above the largest of all input values. | Double |
Drainage enforcement (Optional) | The type of drainage enforcement to apply. The drainage enforcement option can be set to attempt to remove all sinks or depressions so a hydrologically correct DEM can be created. If sink points have been explicitly identified in the input feature data, these depressions will not be filled.
| String |
Primary type of input data (Optional) | The dominant elevation data type of the input feature data. Specifying the relevant selection optimizes the search method used during the generation of streams and ridges.
| String |
Maximum number of iterations (Optional) | The maximum number of interpolation iterations. The number of iterations must be greater than zero. A default of 20 is normally adequate for both contour and line data. A value of 30 will clear fewer sinks. Rarely, higher values (45–50) may be useful to clear more sinks or to set more ridges and streams. Iteration ceases for each grid resolution when the maximum number of iterations has been reached. | Long |
Roughness penalty (Optional) | The integrated squared second derivative as a measure of roughness. The roughness penalty must be zero or greater. If the primary input data type is Contour, the default is zero. If the primary data type is Spot, the default is 0.5. Larger values are not normally recommended. | Double |
Discretisation error factor (Optional) | The discrete error factor is used to adjust the amount of smoothing when converting the input data to a raster. The value must be greater than zero. The normal range of adjustment is 0.25 to 4, and the default is 1. A smaller value results in less data smoothing; a larger value causes greater smoothing. | Double |
Vertical standard error (Optional) | The amount of random error in the z-values of the input data. The value must be zero or greater. The default is zero. The vertical standard error may be set to a small positive value if the data has significant random (non-systematic) vertical errors with uniform variance. In this case, set the vertical standard error to the standard deviation of these errors. For most elevation datasets, the vertical error should be set to zero, but it may be set to a small positive value to stabilize convergence when rasterizing point data with stream line data. | Double |
Tolerance 1 (Optional) | This tolerance reflects the accuracy and density of the elevation points in relation to surface drainage. For point datasets, set the tolerance to the standard error of the data heights. For contour datasets, use one-half the average contour interval. The value must be zero or greater. The default is 2.5 if the data type is Contour and zero if the data type is Spot. | Double |
Tolerance 2 (Optional) | This tolerance prevents drainage clearance through unrealistically high barriers. The value must be greater than zero. The default is 100 if the data type is Contour and 200 if the data type is Spot. | Double |
Output stream polyline features (Optional) | The output line feature class of stream polyline features and ridge line features. The line features are created at the beginning of the interpolation process. It provides the general morphology of the surface for interpolation. It can be used to verify correct drainage and morphology by comparing known stream and ridge data. The polyline features are coded as follows: 1. Input stream line not over cliff. 2. Input stream line over cliff (waterfall). 3. Drainage enforcement clearing a spurious sink. 4. Stream line determined from contour corner. 5. Ridge line determined from contour corner. 6. Code not used. 7. Data stream line side conditions. 8. Code not used. 9. Line indicating large elevation data clearance. | Feature Class |
Output remaining sink point features (Optional) | The output point feature class of the remaining sink point features. These are the sinks that were not specified in the sink input feature data and were not cleared during drainage enforcement. Adjusting the values of the tolerances, Tolerance 1 and Tolerance 2, can reduce the number of remaining sinks. Remaining sinks often indicate errors in the input data that the drainage enforcement algorithm could not resolve. This can be an efficient way of detecting subtle elevation errors. | Feature Class |
Output diagnostic file (Optional) | The output diagnostic file listing all inputs and parameters used and the number of sinks cleared at each resolution and iteration. | File |
Output parameter file (Optional) | The output parameter file listing all inputs and parameters used, which can be used with Topo to Raster by File to run the interpolation again. | File |
Profile curvature roughness penalty (Optional) | The profile curvature roughness penalty is a locally adaptive penalty that can be used to partly replace total curvature. It can yield good results with high-quality contour data but can lead to instability in convergence with poor data. Set to 0.0 for no profile curvature (the default), set to 0.5 for moderate profile curvature, and set to 0.8 for maximum profile curvature. Values larger than 0.8 are not recommended and should not be used. | Double |
Output residual point features (Optional) | The output point feature class of all the large elevation residuals as scaled by the local discretisation error. All the scaled residuals larger than 10 should be inspected for possible errors in input elevation and stream data. Large-scaled residuals indicate conflicts between input elevation data and streamline data. These may also be associated with poor automatic drainage enforcements. These conflicts can be remedied by providing additional streamline and/or point elevation data after first checking and correcting errors in existing input data. Large unscaled residuals usually indicate input elevation errors. | Feature Class |
Output stream and cliff error point features (Optional) | The output point feature class of locations where possible stream and cliff errors occur. The locations where the streams have closed loops, distributaries, and streams over cliffs can be identified from the point feature class. Cliffs with neighboring cells that are inconsistent with the high and low sides of the cliff are also indicated. This can be a good indicator of cliffs with incorrect direction. Points are coded as follows: 1. True circuit in data streamline network. 2. Circuit in stream network as encoded on the out raster. 3. Circuit in stream network via connecting lakes. 4. Distributaries point. 5. Stream over a cliff (waterfall). 6. Points indicating multiple stream outflows from lakes. 7. Code not used. 8. Points beside cliffs with heights inconsistent with cliff direction. 9. Code not used. 10. Circular distributary removed. 11. Distributary with no inflowing stream. 12. Rasterized distributary in output cell different to where the data stream line distributary occurs. 13. Error processing side conditions—an indicator of very complex streamline data. | Feature Class |
Output contour error point features (Optional) | The output point feature class of possible errors pertaining to the input contour data. Contours with bias in height exceeding five times the standard deviation of the contour values as represented on the output raster are reported to this feature class. Contours that join other contours with a different elevation are flagged in this feature class by the code 1; this is a sure sign of a contour label error. | Feature Class |
Available with Spatial Analyst license.
Available with 3D Analyst license.
Summary
Interpolates a hydrologically correct raster surface from point, line, and polygon data.
Usage
The best results will be obtained if all input data is stored in the same planar coordinate system and has the same z-units. Unprojected data (latitude-longitude) can be used; however, the results may not be as accurate, particularly at high latitudes.
If more than one input point falls within an output cell,Topo to Raster will use the average value for the interpolation (only the first 100 points that fall within a cell will be considered and the rest will be ignored). If too many points are encountered by the algorithm, an error may occur, indicating the point dataset has too many points. The maximum number of points that can be used is NRows * NCols, where NRows is the number of rows in the output raster and NCols is the number of columns.
When the input feature data type is Contour, the algorithm first generates a generalized morphology of the surface based on the curvature of the contours. The algorithm then implements the contours as a source of elevation information. Contours are best suited for large-scale data where the contours and corners are reliable indicators of streams and ridges. At smaller scales it can be just as effective, and less expensive, to digitize corner points of contours and use them as an input point feature class.
The Output cell size parameter can be defined by a numeric value or obtained from an existing raster dataset. If the cell size hasn’t been explicitly specified as the parameter value, it is derived from the Cell Size environment if it has been specified. If the parameter cell size or the environment cell size have not been specified, but the Snap Raster environment has been set, the cell size of the snap raster is used. If nothing is specified, the cell size is calculated from the shorter of the width or height of the extent divided by 250 in which the extent is in the output coordinate system specified in the environment.
If the cell size is specified using a numeric value, the tool will use it directly for the output raster.
If the cell size is specified using a raster dataset, the parameter will show the path of the raster dataset instead of the cell size value. The cell size of that raster dataset will be used directly in the analysis, provided the spatial reference of the dataset is the same as the output spatial reference. If the spatial reference of the dataset is different than the output spatial reference, it will be projected based on the specified Cell Size Projection Method value.
Representing braided streams or using arcs to represent two sides of a stream may not produce reliable results. Stream data always takes priority over point or contour data; therefore, elevation data points that conflict with descent down each stream are ignored. Stream data is a powerful way of adding topographic information to the interpolation, further ensuring the quality of the output DEM.
For data formats that support Null values, such as file geodatabase feature classes, a Null value will be ignored when used as input.
Typical values for the Tolerance 1 and Tolerance 2 settings are:
- For point data at 1:100,000 scale, use 5.0 and 200.0.
- For less dense point data up to 1:500,000 scale, use 10.0 and 400.0.
- For contour data with contour spacing of 10, use 5.0 and 100.0.
Tolerance 2 should be at least 6 times greater than Tolerance 1.
To make experimentation with the inputs and parameters easier, use the Topo to Raster dialog box to create an output parameter file, which can be modified in any text editor and used as input to the Topo to Raster by File tool.
This tool is a memory-intensive application and it is therefore not possible to create large output rasters. When large output is required, use the Margin parameter to produce smaller output rasters. For more details on how to do this, the creating and mosaicking rasters section of the How Topo to Raster works help.
Parameters
arcpy.ddd.TopoToRaster(in_topo_features, out_surface_raster, {cell_size}, {extent}, {Margin}, {minimum_z_value}, {maximum_z_value}, {enforce}, {data_type}, {maximum_iterations}, {roughness_penalty}, {discrete_error_factor}, {vertical_standard_error}, {tolerance_1}, {tolerance_2}, {out_stream_features}, {out_sink_features}, {out_diagnostic_file}, {out_parameter_file}, {profile_penalty}, {out_residual_feature}, {out_stream_cliff_error_feature}, {out_contour_error_feature})
Name | Explanation | Data Type |
in_topo_features topo_input | The input features containing the z-values to be interpolated into a surface raster. Each feature input can have a field specified that contains the z-values and one of six types specified.
There are six types of accepted inputs:
Multiple input feature datasets should be enclosed by double quotes. The individual inputs are separated by a semicolon, with a space between each component. See the first Code Sample below for an example. | TopoInput |
out_surface_raster | The output interpolated surface raster. It is always a floating-point raster. | Raster Dataset |
cell_size (Optional) | The cell size of the output raster that will be created. This parameter can be defined by a numeric value or obtained from an existing raster dataset. If the cell size hasn't been explicitly specified as the parameter value, the environment cell size value will be used if specified; otherwise, additional rules will be used to calculate it from the other inputs. See the usage section for more detail. | Analysis Cell Size |
extent (Optional) | Extent for the output raster dataset. Interpolation will occur out to the x and y limits, and cells outside that extent will be NoData. For best interpolation results along the edges of the output raster, the x and y limits should be smaller than the extent of the input data by at least 10 cells on each side. The default extent is the largest of all extents of the input feature data.
| Extent |
Margin margin (Optional) | Distance in cells to interpolate beyond the specified output extent and boundary. The value must be greater than or equal to 0 (zero). The default value is 20. If the {extent} and Boundary feature dataset are the same as the limit of the input data (the default), values interpolated along the edge of the DEM will not match well with adjacent DEM data. This is because they have been interpolated using one-half as much data as the points inside the raster, which are surrounded on all sides by input data. The {margin} option allows input data beyond these limits to be used in the interpolation. | Long |
minimum_z_value (Optional) | The minimum z-value to be used in the interpolation. The default is 20 percent below the smallest of all the input values. | Double |
maximum_z_value (Optional) | The maximum z-value to be used in the interpolation. The default is 20 percent above the largest of all input values. | Double |
enforce (Optional) | The type of drainage enforcement to apply. The drainage enforcement option can be set to attempt to remove all sinks or depressions so a hydrologically correct DEM can be created. If sink points have been explicitly identified in the input feature data, these depressions will not be filled.
| String |
data_type (Optional) | The dominant elevation data type of the input feature data.
Specifying the relevant selection optimizes the search method used during the generation of streams and ridges. | String |
maximum_iterations (Optional) | The maximum number of interpolation iterations. The number of iterations must be greater than zero. A default of 20 is normally adequate for both contour and line data. A value of 30 will clear fewer sinks. Rarely, higher values (45–50) may be useful to clear more sinks or to set more ridges and streams. Iteration ceases for each grid resolution when the maximum number of iterations has been reached. | Long |
roughness_penalty (Optional) | The integrated squared second derivative as a measure of roughness. The roughness penalty must be zero or greater. If the primary input data type is CONTOUR, the default is zero. If the primary data type is SPOT, the default is 0.5. Larger values are not normally recommended. | Double |
discrete_error_factor (Optional) | The discrete error factor is used to adjust the amount of smoothing when converting the input data to a raster. The value must be greater than zero. The normal range of adjustment is 0.25 to 4, and the default is 1. A smaller value results in less data smoothing; a larger value causes greater smoothing. | Double |
vertical_standard_error (Optional) | The amount of random error in the z-values of the input data. The value must be zero or greater. The default is zero. The vertical standard error may be set to a small positive value if the data has significant random (non-systematic) vertical errors with uniform variance. In this case, set the vertical standard error to the standard deviation of these errors. For most elevation datasets, the vertical error should be set to zero, but it may be set to a small positive value to stabilize convergence when rasterizing point data with stream line data. | Double |
tolerance_1 (Optional) | This tolerance reflects the accuracy and density of the elevation points in relation to surface drainage. For point datasets, set the tolerance to the standard error of the data heights. For contour datasets, use one-half the average contour interval. The value must be zero or greater. The default is 2.5 if the data type is CONTOUR and zero if the data type is SPOT. | Double |
tolerance_2 (Optional) | This tolerance prevents drainage clearance through unrealistically high barriers. The value must be greater than zero. The default is 100 if the data type is CONTOUR and 200 if the data type is SPOT. | Double |
out_stream_features (Optional) | The output line feature class of stream polyline features and ridge line features. The line features are created at the beginning of the interpolation process. It provides the general morphology of the surface for interpolation. It can be used to verify correct drainage and morphology by comparing known stream and ridge data. The polyline features are coded as follows: 1. Input stream line not over cliff. 2. Input stream line over cliff (waterfall). 3. Drainage enforcement clearing a spurious sink. 4. Stream line determined from contour corner. 5. Ridge line determined from contour corner. 6. Code not used. 7. Data stream line side conditions. 8. Code not used. 9. Line indicating large elevation data clearance. | Feature Class |
out_sink_features (Optional) | The output point feature class of the remaining sink point features. These are the sinks that were not specified in the sink input feature data and were not cleared during drainage enforcement. Adjusting the values of the tolerances, tolerance_1 and tolerance_2, can reduce the number of remaining sinks. Remaining sinks often indicate errors in the input data that the drainage enforcement algorithm could not resolve. This can be an efficient way of detecting subtle elevation errors. | Feature Class |
out_diagnostic_file (Optional) | The output diagnostic file listing all inputs and parameters used and the number of sinks cleared at each resolution and iteration. | File |
out_parameter_file (Optional) | The output parameter file listing all inputs and parameters used, which can be used with Topo to Raster by File to run the interpolation again. | File |
profile_penalty (Optional) | The profile curvature roughness penalty is a locally adaptive penalty that can be used to partly replace total curvature. It can yield good results with high-quality contour data but can lead to instability in convergence with poor data. Set to 0.0 for no profile curvature (the default), set to 0.5 for moderate profile curvature, and set to 0.8 for maximum profile curvature. Values larger than 0.8 are not recommended and should not be used. | Double |
out_residual_feature (Optional) | The output point feature class of all the large elevation residuals as scaled by the local discretisation error. All the scaled residuals larger than 10 should be inspected for possible errors in input elevation and stream data. Large-scaled residuals indicate conflicts between input elevation data and streamline data. These may also be associated with poor automatic drainage enforcements. These conflicts can be remedied by providing additional streamline and/or point elevation data after first checking and correcting errors in existing input data. Large unscaled residuals usually indicate input elevation errors. | Feature Class |
out_stream_cliff_error_feature (Optional) | The output point feature class of locations where possible stream and cliff errors occur. The locations where the streams have closed loops, distributaries, and streams over cliffs can be identified from the point feature class. Cliffs with neighboring cells that are inconsistent with the high and low sides of the cliff are also indicated. This can be a good indicator of cliffs with incorrect direction. Points are coded as follows: 1. True circuit in data streamline network. 2. Circuit in stream network as encoded on the out raster. 3. Circuit in stream network via connecting lakes. 4. Distributaries point. 5. Stream over a cliff (waterfall). 6. Points indicating multiple stream outflows from lakes. 7. Code not used. 8. Points beside cliffs with heights inconsistent with cliff direction. 9. Code not used. 10. Circular distributary removed. 11. Distributary with no inflowing stream. 12. Rasterized distributary in output cell different to where the data stream line distributary occurs. 13. Error processing side conditions—an indicator of very complex streamline data. | Feature Class |
out_contour_error_feature (Optional) | The output point feature class of possible errors pertaining to the input contour data. Contours with bias in height exceeding five times the standard deviation of the contour values as represented on the output raster are reported to this feature class. Contours that join other contours with a different elevation are flagged in this feature class by the code 1; this is a sure sign of a contour label error. | Feature Class |
Code sample
This example creates a hydrologically correct Grid surface raster from point, line, and polygon data..
import arcpy
from arcpy import env
env.workspace = "C:/data"
arcpy.ddd.TopoToRaster("C:/data/spots.shp spot_meters PointElevation; C:/data/contours.shp spot_meters Contour; C:/data/cliff.shp # Cliff",
"c:/output/toporast", 32, "740825 4309275 748825 4317275",
"20","","","ENFORCE","CONTOUR","40","","1","0")
This example creates a hydrologically correct Grid surface raster from point, line, and polygon data.
# Name: TopoToRaster_3D_Ex_02.py
# Description: Interpolates a hydrologically correct surface
# from point, line, and polygon data.
# Requirements: 3D Analyst Extension
# Import system modules
import arcpy
from arcpy import env
# Set environment settings
env.workspace = "C:/sapyexamples/data"
# Set local variables
inPointElevations = "C:/data/spots.shp spot_meters PointElevation"
inContours = "C:/data/contours.shp spot_meters Contour"
inFeatures = (inPointElevations + ";" + inContours)
outRaster = "C:/output/topoout"
# Execute TopoToRaster
arcpy.ddd.TopoToRaster(inFeatures, outRaster)