On Sat, Dec 14, 2013 at 7:17 AM, Paolo Cavallini <[email protected]> wrote: > Il 13/12/2013 20:18, Radim Blazek ha scritto: > >>> Can you describe some examples where 2-98% is a problem (data type, >>> number of bands, map content, features/phenomena represented by those >>> 2+2%,...) so that we can think about it better? > > Example #1 (less problematic): dtm and their legend are always shown > wrong; newbies do not understand why > Example #2 (more serious): rasterizing sparse vectors (e.g. rivers) > results in a black rectangle, as the number of pixels with valid data is > <2%.
We can try to distinguish discrete from continuous data by number of values, but what will be the threshold? 2, 10, 50, 100...? > In fact, I think we should help users more, e.g. by applying non linear > colour scaling (log, exp) in case of very skewed raster values > distribution: if data are more or less normally distributed, no cut is > applied, and linear scaling is used; if they are badly skewdw or with > outliers, apply a non linear colour scaling. With some thinking, this > should solve most if not all user cases, without asking a normal user to > understand much about raster stats. Can you define precisely "more or less normally distributed"? In general, applying more sophisticated/sensitive decision can catch correctly more cases but it will become more difficult to be communicated to a user. Until we hide it under single "intelligent" style option. > However, in my case the general setting "use min/max" does not seem to > be working. Contrast enhancement "Stretch to min/max" is not applied to new raster layer? For me it works. Radim > Thanks for your thoughts. > > -- > Paolo Cavallini - www.faunalia.eu > QGIS & PostGIS courses: http://www.faunalia.eu/training.html _______________________________________________ Qgis-developer mailing list [email protected] http://lists.osgeo.org/mailman/listinfo/qgis-developer
