[GRASS-SVN] r60917 - grass/branches/releasebranch_7_0/vector/v.vol.rst
svn_grass at osgeo.org
svn_grass at osgeo.org
Sun Jun 22 00:31:07 PDT 2014
Author: neteler
Date: 2014-06-22 00:31:07 -0700 (Sun, 22 Jun 2014)
New Revision: 60917
Modified:
grass/branches/releasebranch_7_0/vector/v.vol.rst/v.vol.rst.html
Log:
v.vol.rst manual: fix section order
Modified: grass/branches/releasebranch_7_0/vector/v.vol.rst/v.vol.rst.html
===================================================================
--- grass/branches/releasebranch_7_0/vector/v.vol.rst/v.vol.rst.html 2014-06-22 02:06:11 UTC (rev 60916)
+++ grass/branches/releasebranch_7_0/vector/v.vol.rst/v.vol.rst.html 2014-06-22 07:31:07 UTC (rev 60917)
@@ -57,72 +57,11 @@
computed using the points in the given segment
and the points in its neighborhood. The minimum number of points taken
for interpolation is controlled by <b>npmin</b> , the value of which
-must
-be larger than <b>segmax</b> and less than 700. This limit of 700 was
+must be larger than <b>segmax</b> and less than 700. This limit of 700 was
selected to ensure the numerical stability and efficiency of the
algorithm.
-<h2>EXAMPLES</h2>
-<!-- TODO: find better data. This example is nonsensical :-) -->
-Spearfish example (we first simulate 3D soil range data):
-
-<div class="code"><pre>
-g.region -dp
-# define volume
-g.region res=100 tbres=100 res3=100 b=0 t=1500 -ap3
-
-### First part: generate synthetic 3D data (true 3D soil data preferred)
-# generate random positions from elevation map (2D)
-r.random elevation.10m vector_output=elevrand n=200
-
-# generate synthetic values
-v.db.addcolumn elevrand col="x double precision, y double precision"
-v.to.db elevrand option=coor col=x,y
-v.db.select elevrand
-
-# create new 3D map
-v.in.db elevrand out=elevrand_3d x=x y=y z=value key=cat
-v.info -c elevrand_3d
-v.info -t elevrand_3d
-
-# remove the now superfluous 'x', 'y' and 'value' (z) columns
-v.db.dropcolumn elevrand_3d col=x
-v.db.dropcolumn elevrand_3d col=y
-v.db.dropcolumn elevrand_3d col=value
-
-# add attribute to have data available for 3D interpolation
-# (Soil range types taken from the USDA Soil Survey)
-d.mon wx0
-d.rast soils.range
-d.vect elevrand_3d
-v.db.addcolumn elevrand_3d col="soilrange integer"
-v.what.rast elevrand_3d col=soilrange rast=soils.range
-
-# fix 0 (no data in raster map) to NULL:
-v.db.update elevrand_3d col=soilrange value=NULL where="soilrange=0"
-v.db.select elevrand_3d
-
-# optionally: check 3D points in Paraview
-v.out.vtk input=elevrand_3d output=elevrand_3d.vtk type=point dp=2
-paraview --data=elevrand_3d.vtk
-
-### Second part: 3D interpolation from 3D point data
-# interpolate volume to "soilrange" voxel map
-v.vol.rst input=elevrand_3d wcol=soilrange elev=soilrange zmult=100
-
-# visualize I: in GRASS GIS wxGUI
-g.gui
-# load: 2D raster map: elevation.10m
-# 3D raster map: soilrange
-
-# visualize II: export to Paraview
-r.mapcalc "bottom = 0.0"
-r3.out.vtk -s input=soilrange top=elevation.10m bottom=bottom dp=2 output=volume.vtk
-paraview --data=volume.vtk
-</pre></div>
-
-
<h3>SQL support</h3>
Using the <b>where</b> parameter, the interpolation can be limited to use
@@ -215,7 +154,6 @@
"box" given by minimum and maximum coordinates in the input vector map.
To remedy this, zoom into the area encompassing the input vector data points.
-
<p>For large data sets (thousands of data points), it is suggested to
zoom into a smaller representative area and test whether the parameters
chosen (e.g. defaults) are appropriate.
@@ -223,6 +161,67 @@
<p>The user must run <em>g.region</em> before the program to set the
3D region for interpolation.
+
+<h2>EXAMPLES</h2>
+
+<!-- TODO: find better data. This example is nonsensical :-) -->
+Spearfish example (we first simulate 3D soil range data):
+
+<div class="code"><pre>
+g.region -dp
+# define volume
+g.region res=100 tbres=100 res3=100 b=0 t=1500 -ap3
+
+### First part: generate synthetic 3D data (true 3D soil data preferred)
+# generate random positions from elevation map (2D)
+r.random elevation.10m vector_output=elevrand n=200
+
+# generate synthetic values
+v.db.addcolumn elevrand col="x double precision, y double precision"
+v.to.db elevrand option=coor col=x,y
+v.db.select elevrand
+
+# create new 3D map
+v.in.db elevrand out=elevrand_3d x=x y=y z=value key=cat
+v.info -c elevrand_3d
+v.info -t elevrand_3d
+
+# remove the now superfluous 'x', 'y' and 'value' (z) columns
+v.db.dropcolumn elevrand_3d col=x
+v.db.dropcolumn elevrand_3d col=y
+v.db.dropcolumn elevrand_3d col=value
+
+# add attribute to have data available for 3D interpolation
+# (Soil range types taken from the USDA Soil Survey)
+d.mon wx0
+d.rast soils.range
+d.vect elevrand_3d
+v.db.addcolumn elevrand_3d col="soilrange integer"
+v.what.rast elevrand_3d col=soilrange rast=soils.range
+
+# fix 0 (no data in raster map) to NULL:
+v.db.update elevrand_3d col=soilrange value=NULL where="soilrange=0"
+v.db.select elevrand_3d
+
+# optionally: check 3D points in Paraview
+v.out.vtk input=elevrand_3d output=elevrand_3d.vtk type=point dp=2
+paraview --data=elevrand_3d.vtk
+
+### Second part: 3D interpolation from 3D point data
+# interpolate volume to "soilrange" voxel map
+v.vol.rst input=elevrand_3d wcol=soilrange elev=soilrange zmult=100
+
+# visualize I: in GRASS GIS wxGUI
+g.gui
+# load: 2D raster map: elevation.10m
+# 3D raster map: soilrange
+
+# visualize II: export to Paraview
+r.mapcalc "bottom = 0.0"
+r3.out.vtk -s input=soilrange top=elevation.10m bottom=bottom dp=2 output=volume.vtk
+paraview --data=volume.vtk
+</pre></div>
+
<h2>BUGS</h2>
<b>devi</b> file is written as 2D and deviations are not written as attributes.
@@ -236,8 +235,8 @@
Goodchild, D.J. Maguire, D.W.Rhind (Eds.), Geographical Information
Systems: Principles, Techniques, Management and Applications, Wiley,
pp.481-492
-<p>Mitas L., Brown W. M., Mitasova H., 1997, <a
- href="http://www4.ncsu.edu/~hmitaso/gmslab/lcgfin/cg-mitas.html">Role
+<p>Mitas L., Brown W. M., Mitasova H., 1997,
+<a href="http://www4.ncsu.edu/~hmitaso/gmslab/lcgfin/cg-mitas.html">Role
of dynamic cartography in simulations of landscape processes based on
multi-variate fields.</a> Computers and Geosciences, Vol. 23, No. 4,
pp. 437-446 (includes CDROM and WWW: www.elsevier.nl/locate/cgvis)
@@ -248,16 +247,14 @@
(4),
special issue on Integrating GIS and Environmental modeling, 433-446.
<p> Mitasova, H., Mitas, L., Brown, B., Kosinovsky, I., Baker, T.,
-Gerdes, D. (1994): <a
- href="http://www4.ncsu.edu/~hmitaso/gmslab/viz/ches.html">Multidimensional
+Gerdes, D. (1994):
+<a href="http://www4.ncsu.edu/~hmitaso/gmslab/viz/ches.html">Multidimensional
interpolation and visualization in GRASS GIS</a>
-<p><a
- href="http://www4.ncsu.edu/~hmitaso/gmslab/papers/lmg.rev1.ps">Mitasova
+<p><a href="http://www4.ncsu.edu/~hmitaso/gmslab/papers/lmg.rev1.ps">Mitasova
H. and Mitas L. 1993</a>: Interpolation by Regularized Spline with
Tension: I. Theory and Implementation, <i>Mathematical Geology</i> 25,
641-655.
-<p><a
- href="http://www4.ncsu.edu/~hmitaso/gmslab/papers/hmg.rev1.ps">Mitasova
+<p><a href="http://www4.ncsu.edu/~hmitaso/gmslab/papers/hmg.rev1.ps">Mitasova
H. and Hofierka J. 1993</a>: Interpolation by Regularized Spline with
Tension: II. Application to Terrain Modeling and Surface Geometry
Analysis, <i>Mathematical Geology</i> 25, 657-667.
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