Thank you Vincent:
I will try with histogram
Ionut
----- Original Message -----
From: "Vincent Schut"
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: http://webhelp.esri.com/arcgisdesktop/9.2/index.cfm?TopicName=tabulate_area
Ionut
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. see: http://docs.scipy.org/doc/numpy/reference/generated/numpy.histogram2d.html Regards, Vincent Schut.
------------------------------------------------------------------------ *From:* Friedrich Romstedt
*To:* Discussion of Numerical Python *Sent:* Sun, July 18, 2010 12:09:04 AM *Subject:* Re: [Numpy-discussion] Crosstabulation 2010/7/17 Robert Kern
mailto:robert.kern@gmail.com>: On Sat, Jul 17, 2010 at 13:11, Friedrich Romstedt
mailto:friedrichromstedt@gmail.com> wrote: 2010/7/14 Ionut Sandric
mailto:sandricionut@yahoo.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"?
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Ionut Sandric