Andrea Antonello a écrit :
It's basically just rasters, but I think can additionally can have
multiple dimensions. It's not my area of expertise.
Multiple dimensions in the sense of voxels?
It may also be time axis. Any valid CRS (org.opengis.referencing.crs.CoordinateReferenceSystem) can
be used, so axis may be depth, time, pressure, etc.
Yeah, our coverage API is just coming to maturity. And I think it still
does not do much raster analysis at all. We're working on data loading
and rendering first, and sticking it all behind standards based
interfaces. So this actually sounds like an area where our communities
can learn a lot from one another.
There is some very basic processing tools. Resampling (or reprojection), convolution, gradient
magnitude, and the usual basic operators like addition, subtraction, log, exp...
For example with very large datasets
(which are more and more common today) we are going to have problems because
of to high amount of memory requests.
Geotools coverage module is build on top of Java Advanced Imaging. Actually the above-cited
convolution, log, exp, etc. operators are just wrappers around the JAI's operators. Simone's work is
continuing in the directory of leveraging JAI capabilities. By the way, JAI is also used at Nasa.
Home page and success stories:
http://java.sun.com/products/java-media/jai/
Available JAI operations (usable in Geotools if a wrapper exists):
http://java.sun.com/products/java-media/jai/forDevelopers/jai-apidocs/javax/media/jai/operator/package-summary.html
Current development (including link to demos):
http://jai-core.dev.java.net/
JAI uses tile caches for managing large images. The image "seems" to hold fully in memory (from the
programmer point of view), but actually part of the image (tiles) can be discarted at any time and
recomputed more than once on demand, or flushed to disk. The JAI's API give us great control on tile
cache mechanism. The inconvenient is that JAI's API is complex and take time to master. Some time I
have the feeling that JAI was a good old Fortran library translated to Java.
An example: to create a map of the total contribution area (the area that
drains water in every pixel) you have to follow the flowdirections of the
elevation model. In every pixel the algorythm look for the next pixel, which
means that this could go diagonal throught the data matrix, i.e. I can't just
read row by row and evaluate.
In JAI, you can perform yours work as is the whole image was holding in memory. Reading and flushing
tiles to disk can be performed by JAI tile cache mechanism without the need for the operator
developper to care (but the image operation may be more efficient if he care).
Geotools mostly relies on JAI for 2D operation. The steps are:
1) Developper write their operation as a JAI operation.
2) Then, wraps the JAI operation in a GridCoverage operation.
This is why Geotools grid coverage framework seems to provide no raster analysis framework at all.
Actually it does provide a very minimalist one, or to be more accurate it inherit it from JAI.
However the Geotools - JAI mapping mechanism need to be improved (I believe that it is part of
Simone's work).
JAI is 2D only. Geotools handle the 3D case as a stack of 2D rasters, the 4D case as a stack of 3D
coverages (which are themselves stacks of 2D rasters), etc. It is suffisient for basic need, but may
not be suffisient for more elaborated operations.
Martin.
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