Thank you Vincent: I will try with histogram
Ionut ----- Original Message ----- From: "Vincent Schut" <sc...@sarvision.nl> To: numpy-discussion@scipy.org Sent: Monday, July 19, 2010 12:00:38 PM GMT +02:00 Athens, Beirut, Bucharest, Istanbul Subject: Re: [Numpy-discussion] Crosstabulation 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: > 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 <friedrichromst...@gmail.com> > *To:* Discussion of Numerical Python <numpy-discussion@scipy.org> > *Sent:* Sun, July 18, 2010 12:09:04 AM > *Subject:* Re: [Numpy-discussion] Crosstabulation > > 2010/7/17 Robert Kern <robert.k...@gmail.com > <mailto:robert.k...@gmail.com>>: > > On Sat, Jul 17, 2010 at 13:11, Friedrich Romstedt > > <friedrichromst...@gmail.com <mailto:friedrichromst...@gmail.com>> wrote: > >> 2010/7/14 Ionut Sandric <sandricio...@yahoo.com > <mailto:sandricio...@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"? > > Friedrich > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org <mailto:NumPy-Discussion@scipy.org> > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
