Mon Jul 19 04:00:38 CDT 2010
On 07/19/2010 09:55 AM, sandric ionut wrote:
> Hi Friedrich:
> For land-use a class would be for example forest, other would be orchard
> etc. For Slope gradient I would have values which <3 and between 3 and 7
> etc. So, I will have 2 raster data with, let's say, 3 classes each:
> forest, orchards and built-up area and for slope gradient: 0-3, 3-15,
> 15-35. The cross-tabulation analysis should give me a table like:
> forest orchards built-up
> 0-3 10 &n bsp; 20 15
> 3-15 5 10 20
> 15-35 5 15 15
> where the numbers represents all the common cells, for example: 10 cells
> with forest correspond to 10 cells with 0-3 slope gradient interval and
> so on
> (by cells I mean the pixel from a raster data)
> The analysis is better illustrated here:
Ha, we're messing up lingo's here :-) Need to switch to GIS (geographic
information systems) dialect.
- DEM = digital elevation map, usually a 2d array ('raster') with
elevation values (for a certain area on earth)
- slope gradient = the slope (literally, not as in math speak) of the
surface depicted by the elevation map. Mostly defined as the maximum
slope within a certain moving window; several competing methods to
estimate/calculate slope exist.
- land use/cover class: raster (array) where each cell ('pixel') has an
integer value, which maps to some well defined land use at that location
(e.g. 0 means sea, 1 means forest, 2 means agriculture, etc)
- crosstabulation usually means some kind of 2d histogram, where the
total number of raster cells with a certain value (e.g. depicting 'land
use class') 'within' a range of values of another raster with the same
shape (and matching locations). Like: how many cells of forest lie
withing a slope range of 0-10 degrees?
Right. On to the answers. I think you should look into
numpy.histogram2d, where you can do exactly what you want. Your land use
array is x, your slope gradient array = y, then you define the bins as
your class numbers (for x) and your slope gradient ranges (for y), and
you will get a pixel count for each bin combination.
> *From:* Friedrich Romstedt <firstname.lastname@example.org>
> *To:* Discussion of Numerical Python <email@example.com>
> *Sent:* Sun, July 18, 2010 12:09:04 AM
> *Subject:* Re: [Numpy-discussion] Crosstabulation
> 2010/7/17 Robert Kern <firstname.lastname@example.org
> > On Sat, Jul 17, 2010 at 13:11, Friedrich Romstedt
> > <email@example.com <mailto:firstname.lastname@example.org>> wrote:
> >> 2010/7/14 Ionut Sandric <email@example.com
> >> I'm afraid also Zach does not understand what you are talking about
> >> ... So my first question (please bear with me) would be: What's a dem?
> > Digital Elevation Map.
> >> (n/a in my dictionary) And sorry for the cross-talk on the other
> >> first post by you ...
> >> And by slope gradient you mean second derivative?
> > No, the first derivative. "Slope gradient" is a reasonably common,
> > albeit somewhat redundant, idiom meaning the gradient of an elevation
> > map.
> Thanks Robert, that clarifies a lot.
> But still I don't understand how the crosstabulation shall work. What
> are the "classes"?
> NumPy-Discussion mailing list
> NumPy-Discussion@scipy.org <mailto:NumPy-Discussion@scipy.org>
> NumPy-Discussion mailing list
More information about the NumPy-Discussion