Free geographical data processing software for linux

OGDI is the Open Geographic Datastore Interface. OGDI is an application programming interface (API) that uses a standardized access methods to work in conjunction with GIS software packages (the application) and various geospatial data products.
OGDI uses a client/server architecture to facilitate the dissemination of geospatial data products over any TCP/IP network, and a driver-oriented approach to facilitate access to several geospatial data products/formats.
Enhancements:
- This release fixes some significant bugs in the VRF (VPF) driver.

SoundTouch Sound Processing Library is an open-source audio processing library for changing the Tempo, Pitch and Playback Rates of audio streams or files:
- Tempo (time-stretch): Changes the sound to play at faster or slower speed than original, without affecting the sound pitch.
- Pitch (key) : Changes the sound pitch or key, without affecting the sound tempo or speed.
- Playback Rate : Changes both the sound tempo and pitch, as if an LP disc was played at wrong RPM rate.
Main features:
- Easy-to-use implementation of time-stretch, pitch-shift and sample rate transposing routines.
- High-performance object-oriented C++ implementation.
- Full source codes available for both the SoundTouch library and the example application.
- Clear and easy-to-use programming interface via a single C++ class.
- Supported audio data format : 16Bit integer or 32bit floating point PCM mono/stereo
- Capable of real-time audio stream processing:
- input/output latency max. ~ 100 ms.
- Processing 44.1kHz/16bit stereo sound in realtime requires a 133 Mhz Intel Pentium processor or better.
- Platform-independent implementation: The SoundTouch library can be compiled for any processor and OS platform supporting GNU C compiler (gcc) or Visual Studio, for example Win32, Linux, AIX.
- Additional assembler-level and Intel-MMX instruction set optimizations for Intel x86 compatible processors (Win32 & Linux platforms), offering several times increase in the processing performance.
- Compiled executable binaries available for Windows.
Enhancements:
- Add features/limitations/changes here

Data::Locations - magic insertion points in your data
Did you already encounter the problem that you had to produce some data in a particular order, but that some piece of the data was still unavailable at the point in the sequence where it belonged and where it should have been produced?
Did you also have to resort to cumbersome and tedious measures such as storing the first and the last part of your data separately, then producing the missing middle part, and finally putting it all together?
In this simple case, involving only one deferred insertion, you might still put up with this solution.
But if there is more than one deferred insertion, requiring the handling of many fragments of data, you will probably get annoyed and frustrated.
You might even have to struggle with limitations of the file system of your operating system, or handling so many files might considerably slow down your application due to excessive file input/output.
And if you dont know exactly beforehand how many deferred insertions there will be (if this depends dynamically on the data being processed), and/or if the pieces of data you need to insert need additional (nested) insertions themselves, things will get really tricky, messy and troublesome.
In such a case you might wonder if there wasnt an elegant solution to this problem.
This is where the "Data::Locations" module comes in: It handles such insertion points automatically for you, no matter how many and how deeply nested, purely in memory, requiring no (inherently slower) file input/output operations.
(The underlying operating system will automatically take care if the amount of data becomes too large to be handled fully in memory, though, by swapping out unneeded parts.)
Moreover, it also allows you to insert the same fragment of data into SEVERAL different places.
This increases space efficiency because the same data is stored in memory only once, but used multiple times.
Potential infinite recursion loops are detected automatically and refused.
In order to better understand the underlying concept, think of "Data::Locations" as virtual files with almost random access: You can write data to them, you can say "reserve some space here which I will fill in later", and continue writing data.
And you can of course also read from these virtual files, at any time, in order to see the data that a given virtual file currently contains.
When you are finished filling in all the different parts of your virtual file, you can write out its contents in flattened form to a physical, real file this time, or process it otherwise (purely in memory, if you wish).
You can also think of "Data::Locations" as bubbles and bubbles inside of other bubbles. You can inflate these bubbles in any arbitrary order you like through a straw (i.e., the bubbles object reference).
Note that this module handles your data completely transparently, which means that you can use it equally well for text AND binary data.
You might also be interested in knowing that this module and its concept have already been heavily used in the automatic code generation of large software projects.
Enhancements:
- Fixed test file "02___refcount.t" to auto-adjust the offset dealing with self-ties not incrementing
- the refcount in some Perl versions.
- Added a warning to "Makefile.PL" that Perl versions including and between v5.6.1 and v5.7.0 are not fully supported (test file "11_______dump.t" dumps core).

The Databionic MusicMiner is a browser for music based on data mining techniques. You can create MusicMaps to visualize the similarity of songs and artists. Explore your music and create playlists based on the paradigm of geographical maps!
Main features:
- Automatic parsing of a folder tree with music files (MP3, OGG, WMA, M4A, MP2, WAV).
- Automatic description of digital audio files by sound.
- Creation of MusicMaps to navigate the sound space based on the paradigm of geographical maps.
- Visual creation of playlists.
- Similarity search in music collection based on sound.
- Customizable hierarchichal browsing of the database by e.g. genre/artist/album or year/artist.
- Flexible database including the seperate storage of several artists per song, albums and playlists as part of a playlist.
- Import and export of meta information based on XML.
Enhancements:
- This release offers better sound descriptors resulting from more experiments with audio features.
- The processing of audio files is more robust, the import of meta information is much faster, and more audio formats are supported.
- MusicMiner now also runs on OS X with some manual setup work described in a howto.

Radar Tools in short RAT is a small collection of tools for processing SAR (synthetic aperture radar) remote sensing data, packed together in a nice graphical user interface.
Our motivation to start the development of RAT is that modern remote sensing software like Erdas Image or ENVI include only some basic SAR functionality. Advanced algorithms have to be implemented by oneself.
So we descided to start the development of RAT. RAT should bring modern SAR algorithms to a wider user-base by simplifying in particular the data handling and processing of complex SAR data.
RAT is planned as an ongoing community effort, i.e. there will be no final version with a certain functionality. It is our idea to include more and more SAR tools in future and to make them freely available to the scientific community.
We of course also hope for external contributions. Because of this, the programming interface of RAT is kept quite simple and adding own functions is quite easy. Function templates are included in the distribution and a step-by-step description of how to program a RAT module will appear soon in the documentation.
Main features:
General features
- Cross-platform (Unix, Windows, Linux & Mac OSX)
- Free software, no commercial software license needed (when using the IDL-VM version)
- Availability of the complete source code
- Modular design, easy to extend by own functions
- Small memory footprint even when processing large images (vertical tiling)
- No limitation on the image size
- Keep track of data representation changes during image processing
- Optimised preview on screen while calculations are done in full resolution
- Native import routines for E-SAR (DLR) and ENVISAT-IMS (ESA) data
- Export possibility to generic graphic formats (png, jpg & tiff)
- Undo function for the last processing step
Generic image manipulation
- Resize, presumming & cut region
- Zooming of an area of interest
- Mirror vertical and horizontal
- Binary transforms
Single channel SAR
- SAR speckle filtering (Boxcar, Median, Gauss, Kuan, Frost, MAP Lee, refined Lee, Lee-Sigma)
- Edge detection (RoA, MSP-RoA, Sobel, Roberts)
- Co-occurance texture features, variation coefficient
- Point and distributed target analysis
- Generic slant-to-ground range projection
SAR polarimetry
- Polarimetric point target analysis
- Polarimetric speckle filtering (Boxcar, Lee, refined Lee)
- Polarimetric CFSAR edge detection
- Calculation of interchannel ratios, correlation & phase differences
- Formation of covariance and coherency matrix, span calculation
- Polarimetric basis transforms (linear -> circular ....)
- Decompositions (Pauli, Freman-Durdan, Moriyama, Entropy/Alpha, Eigenvalue, Sphere-Diplane-Helix....)
- Polarimetric classification (Entropy/Alpha/Anisotropy, Wishart, No. of scatterers, physical, Lee category preserving...)
- Polarimetric calibration: imbalance, symmetrisation & crosstalk (Quegan method)
SAR interferometry
- Image pair coregistration (coarse, subpixel & spatially varying)
- Interferogram formation
- Flat-earth removal
- Phase-unwrapping (least-squares only)
- Phase noise filter (Boxcar, Goldstein & GLSME)
- Coherence estimation (Boxcar, Gauss, Region Growing)
- Shaded relief calculation
Polarimetric SAR interferometry
- Formation of POLINSAR covariance and coherency matrices
- Coherence estimation & optimisation
- Extraction of optimised ESPRIT phases
- POLINSAR speckle filtering (Boxcar, Gauss & Lee)
- Coherence analysis in the complex unitary plane

App::ErrorCalculator is a Perl module that contains calculations with Gaussian Error Propagation.

SYNOPSIS

# You can use the errorcalculator script instead.

require App::ErrorCalculator;
App::ErrorCalculator->run();

# Using the script:
# errorcalculator

errorcalculator and its implementing Perl module App::ErrorCalculator is a Gtk2 tool that lets you do calculations with automatic error propagation.

Start the script, enter a function into the function entry field, select an input file, select an output file and hit the Run Calculation button to have all data in the input field processed according to the function and written to the output file.
Functions should consist of a function name followed by an equals sign and a function body. All identifiers (both the function name and all variables in the function body) should start with a letter. They may contain letters, numbers and underscores.

The function body may contain any number of constants, variables, operators, functions and parenthesis. The exact syntax can be obtained by reading the manual page for Math::Symbolic::Parser. Arithmetic operators (+ - * / ^) are supported. The caret indicates exponentiation. Trigonometric, inverse trigonometric and hyperbolic functions are implemented (sin cos tan cot asin acos atan acot sinh cosh asinh acoth). log indicates a natural logarithm.

Additionally, you may include derivatives in the formula which will be evaluated (analytically) for you. The syntax for this is: partial_derivative(a * x + b, x). (Would evaluate to a.)

In order to allow for errors in constants, the program uses the Math::SymbolicX::Error parser extension: use the error(1 +/- 0.2) function to include constants with associated uncertainties in your formulas.

The input files may be of any format recognized by the Spreadsheet::Read module. That means: Excel sheets, OpenOffice (1.0) spreadsheets, CSV (comma separated values) text files, etc.

The program reads tabular data from the spreadsheet file. It expects each column to contain the data for one variable in the formula.

a, b, c
1, 2, 3
4, 5, 6
7, 8, 9

This would assign 1 to the variable a, 2 to b and 3 to c and then evaluate the formula with those values. The result would be written to the first data line of the output file. Then, the data in the next row will be used and so on. If a column is missing data, it is assumed to be zero.

Since this is about errors, you can declare any number of errors to the numbers as demonstrated below:

a, a_1, a_2, b, b_1
1, 0.2, 0.1, 2, 0.3
4, 0.3, 0.3, 5, 0.6
7, 0.4, 0,1, 8, 0.9

Apart from dropping c for brevity, this example input adds columns for the errors of a and b. a has two errors: a_1 and a_2. b only has one error b_1 which corresponds to the error a_1. When calculating, a will be used as 1 +/- 0.2 +/- 0.1 in the first calculation and b as 2 +/- 0.3 +/- 0. The error propagation is implemented using Number::WithError so thats where you go for details.

The output file will be a CSV file similar to the input examples above.

Seismic Toolkit 0.69a is designed to be a tool for processing and displaying seismic signal data in a graphical interface. Plot SAC ASCII and SAC_BIN data format, with zoom,unzoom, plot channel by channel, or plot all channel (until 2000, tested with 125).

Filtering the data: all filters are causal recursive IFR (Infinite Impulse Response) written using the bilinear Z-transform in the time domain. Their conception using a few number of coefficients gives them very fast with a low memory cost.

The adaptation factor of frequency warrants no deformation in the frequency domain of the transfer function. The main filters used are the following: Butterworth High-Pass and Low-Pass (n order), Farrer 10s-6s Low-Pass (a combination of rejector and Low-Pass specially designed for removing oceanic noise), Integrator, Derivator, Integrator with cut-off frequency, Derivator with cut-off frequency, Trend removing, Rejector (n-order), Envelop with Hilbert (not recursive at all), compensator of (n-order), Polynomial filter (n-order, not recursive at all ).

Major Functions:

1. Data plotting : channel by channel, all channels, zoom, unzoom, unfilter, instantaneous time and amplitude information with mouse pointer.
2. Fourier domain: Power Spectral Density (PSD) in linear-linear, log-log axes; independent windows for each channel, instantaneous frequency and amplitude information with mouse pointer, zoom, unzoom of spectra. Dirac, Hilbert transform, Time-Frequency representation (tested until 1 million of points per channel on 3 channels.
3. Polarization : easy and fast particule motion representation in both horizontal plane and incidence plane, with automatic computation of best direction with eigen vectors of the covariance matrix. Display of linearity and planearity coefficient.
   

Enhancements:

• New package (.deb) for Debian - Ubuntu
• New package (.dmg) for MAC OSX 10.4 (Tiger)
• Add function Derivator _Fc (a derivator with a cutting frequency
• Impose : setlocale(LC_ALL,"C") to avoid regional setting as decimal separator;

Commonly referred to as GRASS, this is a Geographic Information System (GIS) used for geospatial data management and analysis, image processing, graphics/maps production, spatial modeling, and visualization. GRASS is currently used in academic and commercial settings around the world, as well as by many governmental agencies and environmental consulting companies.

GRASS GIS is free software released under the GNU/GPL license.