This tool creates a new raster in which each grid cell is assigned the distance, in meters, to the nearest topographic obstacle in a specified direction. It is a modification of the algorithm described by Lapen and Martz (1993). Unlike the original algorithm, Fetch Analysis is capable of analyzing fetch in any direction from 0-360 degrees. The user must specify the name of an input digital elevation model (DEM) raster file, the output raster name, a hypothetical wind direction, and a value for the height increment parameter. The algorithm searches each grid cell in a path following the specified wind direction until the following condition is met:
Ztest >= Zcore + DI
Where Zcore is the elevation of the grid cell
at which fetch is being determined, Ztest is the
elevation of the grid cell being tested as a topographic obstacle,
D is the distance between the two grid cells in meters, and
I is the height increment in m/m. Lapen and Martz (1993)
suggest values for I in the range of 0.025 m/m to 0.1 m/m
based on their study of snow re-distribution in low-relief
agricultural landscapes of the Canadian Prairies. If the directional
search does not identify an obstacle grid cell before the edge of the
DEM is reached, the distance between the DEM edge and
Zcore is
entered. Edge distances are assigned negative values to differentiate
between these artificially truncated fetch values and those for which
a valid topographic obstacle was identified. Notice that linear
interpolation is used to estimate the elevation of the surface where
a ray (i.e. the search path) does not intersect the DEM grid precisely
at one of its nodes.
Ray-tracing is a highly computationally intensive task and therefore this tool may take considerable time to operate for larger sized DEMs. NoData valued grid cells in the input image will be assigned NoData values in the output image. The output raster is of the float data type and continuous data scale. Fetch Analysis images are best displayed using the blue-white-red bipolar palette to distinguish between the positive and negative values that are present in the output.
The following is an example of a Python script that uses this tool:
wd = pluginHost.getWorkingDirectory()
demFile = wd + "DEM.dep"
outputFile = wd + "output.dep"
azimuth = "215.0"
heightIncrement = "0.05"
args = [inputFile, outputFile, azimuth, heightIncrement]
pluginHost.runPlugin("FetchAnalysis", args, False)
This is a Groovy script also using this tool:
def wd = pluginHost.getWorkingDirectory()
def demFile = wd + "input.dep"
def outputFile = wd + "output.dep"
def azimuth = "215.0"
def heightIncrement = "0.05"
String[] args = [demFile, outputFile, azimuth, heightIncrement]
pluginHost.runPlugin("FetchAnalysis", args, false)