Debian GIS Remote Sensing packages

Dan Stahlkes GDAL-bidragede værktøjer er en samling af nyttige programmer til at udføre gængse rasteroperationer. De inkluderede værktøjer er: gdal_contrast_stretch, gdal_dem2rgb, gdal_get_projected_bounds, gdal_landsat_pansharpi, gdal_list_corners, gdal_merge_simple, gdal_merge_vrt gdal_raw2geotiff, gdal_trace_outline, gdal_wkt_to_mask, gdal_make_ndv_mask.

GDAL er et oversætterbibliotek for geospatiale raster-dataformater. Som et bibliotek præsenterer den en enkelt abstrakt datamodel til det kaldende program for alle understøttede formater. Det forbundne OGR-bibliotek (som lever indeni GDAL-kildetræet) tilbyder en lignende kapabilitet for enkle funktioner af vektordata.

GDAL understøtter +40 populære dataformater, inklusive almindeligt brugte (GeoTIFF, JPEG, PNG og flere) samt dem brugt i GIS og softwarepakker til fjernregistrering (ERDAS Imagine, ESRI arc/Info, ENVI, PCI Geomatics). Understøtter også mange formater til fjernregistrering og videnskabelig datadistribution såsom HDF, EOS FAST, NOAA L1B, NetCDF, FITS.

OGR-biblioteket understøtter populære vektorformater som ESRI Shapefile, TIGER-data, S57, MapInfo-fil, DGN, GML med flere.

Denne pakke indeholder redskabsprogrammer, baseret på GDAL/OGR-biblioteket: gdal_translate, gdalinfo, gdaladdo, gdalwarp, ogr2ogr, ogrinfo, ogrtindex.

GMTSAR is an open source Interferometric Synthetic Aperture RADAR (InSAR) processing system designed for users familiar with Generic Mapping Tools (GMT).

The code is written in C and will compile on any computer where GMT and NETCDF are installed.

The system has three main components:

• a preprocessor for each satellite data type (ERS-1/2, Envisat, ALOS-1, TerraSAR-X, COSMO-SkyMed, Radarsat-2, Sentinel-1A/B, and ALOS-2) to convert the native format and orbital information into a generic format;
• an InSAR processor to focus and align stacks of images, map topography into phase, and form the complex interferogram;
• a postprocessor, mostly based on GMT, to filter the interferogram and construct interferometric products of phase, coherence, phase gradient, and line-of sight displacement in both radar and geographic coordinates.

GMT is used to display all the products as pdf files and KML images for Google Earth. A set of shell scripts has been developed for standard 2-pass processing as well as geometric image alignment for stacking and time series.

GDAL er et oversætterbibliotek for geospatiale raster-dataformater. Som et bibliotek præsenterer den en enkelt abstrakt datamodel til det kaldende program for alle understøttede formater. Det forbundne OGR-bibliotek (som lever indeni GDAL-kildetræet) tilbyder en lignende kapabilitet for enkle funktioner af vektordata.

GDAL understøtter mange populære dataformater, inklusiv almindelig brugte (GeoTIFF, JPEG, PNG med flere) samt dem brugt i GIS og ekstern følsomhedsprogrampakker (ERDAS Imagine, ESRI Arc/Info, ENVI, PCI Geomatics). Understøtter også mange eksterne følsomheds- og videnskabelige datadistributionsformater såsom HDF, EOS FAST, NOAA L1B, NetCDF, FITS.

OGR-biblioteket understøtter populære vektorformater som ESRI Shapefile, TIGER-data, S57, MapInfo-fil, DGN, GML med flere.

Denne pakke indeholder filerne krævet for at udvikle et program som vil bruge GDAL/OGR'en (hoveder, statiske objekter, konfigurationsskript).

Open Source Software Image Map (OSSIM) er en højtydende motor for ekstern registrering, billedbehandling, geografisk informationssystem og fotogrammetri. Det har været under udvikling siden 1996.

Designet som en serie af højtydende programbiblioteker, er det skrevet i C++ med de seneste teknikker i objektorienteret programdesign.

Dette bibliotek tilbyder avanceret funktionalitet for ekstern registrering, billedbehandling og geografisk rumlighed. Et hurtigt overblik over OSSIM-funktionalitet inkluderer ortho-berigtigelse, præcis terrænkorrektion, omhyggelige sensormodeller, meget store mosaikker og krydssensorfusioner, en bred vifte af kortprojektioner og datums, og et stort udvalg af kommercielle og offentlige dataformater. Arkitekturen i bibliotekets understøtter parallel behandling med MPI (ikke aktiveret), en dynamisk arkitektur for udvidelsesmoduler og dynamisk tilsluttede objekter tillader hurtige prototyper af brugerdefinerede kæder til billedbehandling.

Denne pakke indeholder udviklingsfilerne til at bygge programmer, der bruger biblioteket OSSIM.

Open Source Software Image Map (OSSIM) er en højtydende motor for ekstern registrering, billedbehandling, geografisk informationssystem og fotogrammetri. Det har været under udvikling siden 1996.

Designet som en serie af højtydende programbiblioteker, er det skrevet i C++ med de seneste teknikker i objektorienteret programdesign.

Dette bibliotek tilbyder avanceret funktionalitet for ekstern registrering, billedbehandling og geografisk rumlighed. Et hurtigt overblik over OSSIM-funktionalitet inkluderer ortho-berigtigelse, præcis terrænkorrektion, omhyggelige sensormodeller, meget store mosaikker og krydssensorfusioner, en bred vifte af kortprojektioner og datums, og et stort udvalg af kommercielle og offentlige dataformater. Arkitekturen i bibliotekets understøtter parallel behandling med MPI (ikke aktiveret), en dynamisk arkitektur for udvidelsesmoduler og dynamisk tilsluttede objekter tillader hurtige prototyper af brugerdefinerede kæder til billedbehandling.

Denne pakke inkluderer nogle grundlæggende værktøjer, som bruger OSSIM-biblioteket til at udføre nogle grundlæggende opgaver.

ORFEO Toolbox (OTB) er distribueret som et bibliotek i åben kildekode for billedbehandlingsalgoritmer. OTB er baseret på det medicinske billedbehandlingsbibliotek ITK og tilbyder bestemte funktioner for ekstern billedbehandling generelt og specielt for billeder i høj delvis opløsning.

Denne pakke indeholder programopstart for kommandolinjen, som kan afvikle ethvert OTB-program tilbudt af pakken libotb-apps.

ORFEO Toolbox (OTB) er distribueret som et bibliotek i åben kildekode for billedbehandlingsalgoritmer. OTB er baseret på det medicinske billedbehandlingsbibliotek ITK og tilbyder bestemte funktioner for ekstern billedbehandling generelt og specielt for billeder i høj delvis opløsning.

Denne pakke indeholder opstartsprogrammet for den grafiske brugerflade, som kan afvikle ethvert OTB-program leveret af pakken liboth-apps.

PyEPR tilbyder Pythonbindinger for ENVISAT Product Reader C API (EPR API) for læsning af satellitdata fra ENVISAT ESA-mission (European Space Agency).

PyEPR, samt EPR API'en for C, understøtter supports ENVISAT MERIS-, AATSR Level 1B- og Level 2- og også ASAR dataprodukter. API'en tilbyder adgang til data enten på en geofysisk (afkodede, klar til brug billedpunktsprøver) eller på et råt datalag. Den rå dataadgang gør det muligt at læse ethvert datafelt indeholdt i en produktfil.

Dette er Python 2-versionen af pakken.

Pakkens hovedformål er at konvertere satellitdata på lavt niveau til et format forstået af mpop (http://github.com/mraspaud/mpop). Det primære formål er at understøtte geostationære satellitdata (niveau 1.5) men der er også understøttelse for lænsing af nogle polarkredsende SAR-data.

En mere sofistikeret grænseflade til satellitdataobjekter er understøttet af mpop.

I øjeblikket håndteres data fra alle nuværende Meteosat Second Generation-satellitter (MSG), Meteosat 7, GOES 11-15, MTSAT's og GOMS alle hentet via EUMETCast.

Derudover håndterer mipp Synthetic Apperture Radar-data (SAR) fra Terrscan-X, Cosmo-Sky Med og Radarsat 2.

Denne pakke er en del af PyTroll-værktøjssættet.

Pakken Meteorological Post-Processing er et Pythonbibliotek for oprettelse af RGB-produkter for meteorologisk ekstern registrering. Som sådan kan pakken oprette RGB-kompositter direkte fra satellitinstrumentkanaler eller udnytte præberegnede PGE'er.

Den er designet for nem udvidelse, der kan understøtte meteorologisk satellit ved oprettelse af udvidelsesmoduler. I grunddistributionen er der understøttelse for Meteosat 7, 8, 9, MTSAT1R, MTSAT2, GOES 11, GOES 12, GOES 13 via brug af mipp og Noaa 15, 16, 17, 18, 19, og Metop A via brug af aapp og ahamap.

Genprojicering af data er også tilgængelig via brugen af pakken pyresample.

Denne pakke er en del af PyTroll-værktøjssættet.

Pycoast er en Pythonpakke til at tilføje kystlinjer, grænser og floder til rasterbilleder via data fra GSHHS- (tidligere kendt som GSHHS) WDBII-datasæt.

Denne pakke er en del af PyTroll-værktøjssættet.

Denne pakke indeholder pycoast for Python 2.

Pykdtree er en kd-tree-implementering for hurtige nærmeste nabosøgninger i Python. Formålet er at være den hurtigste implementering for gængs brug (små dimensioner og et lille antal naboer) for både trækonstruktion og forespørgsler.

Implementeringen er baseret på scipy.spatial.cKDTree og libANN ved at kombinere de bedste funktioner fra begge og fokusere på implementeringseffektivitet.

Grænsefladen svarer til scipy.spatial.cKDTree med undtagelse af, at kun euklidiske afstandsmåling er understøttet.

Forespørgsler kan valgfrit benytte flere tråde via brug af OpenMP.

Dette er Python 2-versionen af pakken.

Pythonpakke for beregning af orbitale parametre fra TLE-filer og udarbejdelse af diverse astronomiske beregninger.

Denne pakke er en del af PyTroll-værktøjssættet.

Dette er Python 2-versionen af pakken.

Pyresample er en Pythonpakke for nysampling (reprojektion) for jordobserverende satellitdata. Pakken håndterer både nysampling af gitteropdelte data (f.eks. geostationære satellitter) og swath-data (satellitter i kredsløb om polen).

Pyresample kan bruger flere processorkerner for nysampling. Pyresample understøtter maskerede tabeller.

Dette er Python 2-versionen af pakken.

NCO er et programpakke kendt som operatører. Operatørerne er uafhængige, kommandolinjeprogrammer der kan køres i en POSIX-skal. Operatører tager en eller flere netCDF-filer som inddata, udføre handlinger (f.eks. gennemsnit, hyperslabbing), og laver en netCDF-uddatafil. NCO blev oprindelig udviklet til at manipulere og analysere klimadata. Programmet virker dog på alle datasæt i netCDF-formatet.

Du kan bruge ncview til at få et hurtigt og nemt, trykknapsudseende af dine NetCDF-filer. Du kan vise simple film over dataene, se langs med forskellige dimensioner, tage et kig på de aktuelle dataværdier, ændre farvekort, vende dataene om og andre simple visuelle handlinger.

Indeholder programmerne ncdump og ncgen, som konverterer NetCDF-filer til ASCII og tilbage igen. NetCDF (network Common Data Form) er en brugerflade for videnskabelig dataadgang og et frit distribueret programbibliotek, som tilbyder en implementering af brugerfladen. Biblioteket netCDF definerer også et maskinuafhængigt format til repræsentation af videnskabelige data. Tilsammen understøtter brugerfladen, biblioteket og formatet oprettelsen, adgangen og delingen af videnskabelige data.

DORIS is an Interferometric Synthetic Aperture Radar (InSAR) processor developed by the Delft Institute of Earth Observation and Space Systems of Delft University of Technology.

Interferometric products and endproducts such as Digital Elevation Models and displacement maps can be generated with this software from Single Look Complex data. Data from the satellites ERS, ENVISAT (first ENVISAT interferogram, DEM, and perspective view, JERS (first JERS interferogram), and RADARSAT (first RADARSAT interferogram) can be processed with the Doris software.

Two-dimensional phase unwrapping is the process of recovering unambiguous phase data from a 2-D array of phase values known only modulo 2pi rad.

There are many applications, like Magnetic Resonance Imaging (MRI), Synthetic Aperture Radar (SAR), fringe pattern analysis, tomography and spectroscopy, which as part of their fundamental operation depend upon the extraction of a phase signal from their input image. Usually the phase is available in a form that suffers from 2-pi phase jumps due to the use of the mathematical arctangent function, which produces an inherently wrapped output. This wrapped phase is unusable until the phase discontinuities are removed.

SNAPHU is an implementation of the Statistical-cost, Network-flow Algorithm for Phase Unwrapping particularly suitable for SAR interferometry applications. This algorithm poses phase unwrapping as a maximum a posteriori probability (MAP) estimation problem, the objective of which is to compute the most likely unwrapped solution given the observable input data. Because the statistics relating the input data to the solution depend on the measured quantity, SNAPHU incorporates three built-in statistical models, for topography data, deformation data, and smooth generic data. The posed optimization problem is solved approximately with use of network-flow techniques.

As SNAPHU uses an iterative optimization procedure, its execution time depends on the difficulty of the interferogram. In single-tile mode the required memory is on the order of 100 MB per 1000000 pixels in the input interferogram.

GSDView open source edition is a lightweight viewer for geo-spatial data and products written in Python and Qt4. GSDView is modular and has a simple plug-in architecture. It is mainly intended to be a graphical front-end for the GDAL library and tools.

The MapReady Remote Sensing Tool Kit accepts level 1 detected SAR data, single look complex SAR data, and optical data from ASF and some other facilities. It can terrain correct, geocode, apply polarimetric decompositions to multi-pol SAR data, and save to several common imagery formats including GeoTIFF. Other software included in the package are an image viewer, metadata viewer, a projection coordinate converter, and a variety of command line tools.

Open Source Software Image Map (OSSIM) is a high performance engine for remote sensing, image processing, geographical information systems and photogrammetry. It has been actively developed since 1996.

Designed as a series of high performance software libraries, it is written in C++ employing the latest techniques in object-oriented software design.

The library provides advanced remote sensing, image processing, and geo-spatial functionality. A quick summary of OSSIM functionality includes ortho-rectification, precision terrain correction, rigorous sensor models, very large mosaics, and cross sensor fusions, a wide range of map projections and datums, and a large range of commercial and government data formats. The architecture of the library supports parallel processing with mpi (not enabled), a dynamic plugin architecture, and dynamically connectable objects allowing rapid prototyping of custom image processing chains.

This package contains the OSSIM graphical interface.

Open Source Software Image Map (OSSIM) is a high performance engine for remote sensing, image processing, geographical information systems and photogrammetry. It has been actively developed since 1996.

Designed as a series of high performance software libraries, it is written in C++ employing the latest techniques in object-oriented software design.

The library provides advanced remote sensing, image processing, and geo-spatial functionality. A quick summary of OSSIM functionality includes ortho-rectification, precision terrain correction, rigorous sensor models, very large mosaics, and cross sensor fusions, a wide range of map projections and datums, and a large range of commercial and government data formats. The architecture of the library supports parallel processing with mpi (not enabled), a dynamic plugin architecture, and dynamically connectable objects allowing rapid prototyping of custom image processing chains.

This package contains the OSSIM data shared between packages.

Open Source Software Image Map (OSSIM) is a high performance engine for remote sensing, image processing, geographical information systems and photogrammetry. It has been actively developed since 1996.

Designed as a series of high performance software libraries, it is written in C++ employing the latest techniques in object-oriented software design.

The library provides advanced remote sensing, image processing, and geo-spatial functionality. A quick summary of OSSIM functionality includes ortho-rectification, precision terrain correction, rigorous sensor models, very large mosaics, and cross sensor fusions, a wide range of map projections and datums, and a large range of commercial and government data formats. The architecture of the library supports parallel processing with mpi (not enabled), a dynamic plugin architecture, and dynamically connectable objects allowing rapid prototyping of custom image processing chains.

This package contains the OSSIM planet utilities.

Open Source Software Image Map (OSSIM) is a high performance engine for remote sensing, image processing, geographical information systems and photogrammetry. It has been actively developed since 1996.

Designed as a series of high performance software libraries, it is written in C++ employing the latest techniques in object-oriented software design.

The library provides advanced remote sensing, image processing, and geo-spatial functionality. A quick summary of OSSIM functionality includes ortho-rectification, precision terrain correction, rigorous sensor models, very large mosaics, and cross sensor fusions, a wide range of map projections and datums, and a large range of commercial and government data formats. The architecture of the library supports parallel processing with mpi (not enabled), a dynamic plugin architecture, and dynamically connectable objects allowing rapid prototyping of custom image processing chains.

This package contains the OSSIM planet Qt utility.

Open Source Software Image Map (OSSIM) is a high performance engine for remote sensing, image processing, geographical information systems and photogrammetry. It has been actively developed since 1996.

Designed as a series of high performance software libraries, it is written in C++ employing the latest techniques in object-oriented software design.

The library provides advanced remote sensing, image processing, and geo-spatial functionality. A quick summary of OSSIM functionality includes ortho-rectification, precision terrain correction, rigorous sensor models, very large mosaics, and cross sensor fusions, a wide range of map projections and datums, and a large range of commercial and government data formats. The architecture of the library supports parallel processing with mpi (not enabled), a dynamic plugin architecture, and dynamically connectable objects allowing rapid prototyping of custom image processing chains.

This package contains the OSSIM core plugins.

The Polarimetric SAR Data Processing and Educational Tool aims to facilitate the accessibility and exploitation of multi-polarised SAR datasets including those from ESA Third Party Missions (ALOS PALSAR), Envisat ASAR Alternating Polarisation mode products, RADARSAT-2 and TerraSAR-X.

A wide-ranging tutorial and comprehensive documentation provide a grounding in polarimetry and polarimetric interferometry necessary to stimulate research and development of scientific applications that utilise such techniques; the toolbox of processing functions offers users the capability to implement them.

PolSARpro is developed under contract to ESA by a consortium comprising IETR at the University of Rennes 1, The Microwaves and Radar Institute (HR) of DLR and AEL Consultants, together with Dr Mark Williams. The initiative is a direct result of recommendations made at the POLInSAR Workshops held at ESRIN in January 2003, 2005 and 2007.

ADORE is a shell environment designed to simplify and streamline SAR interferometry with the DORIS InSAR processor. It is an attempt to simplify processing of different interferometric stacks like, single-master-stack, or short-baselines. It is highly configurable and provides sensible default options. Each DORIS step can be run individually.

BEST is a collection of executable software tools that has been developed to facilitate the use of ESA SAR data.

The purpose of the Toolbox is not to duplicate existing commercial packages, but to complement them with functions dedicated to the handling of SAR products obtained from the ASAR (Advanced Synthetic Aperture Radar) onboard Envisat and the AMIs (Active Microwave Instrument) onboard ERS 1/2.

BEST (Basic Envisat SAR Toolbox) is a collection of executable software tools that has been designed to facilitate the use of ESA (the European Space Agency) SAR data. It operates according to user-generated parameters files.

BESTGUI allows you to easily generate the parameters files for the BEST tools and launch the processing from the GUI. It provides:

• enhanced menus and toolbars
• persistent preferences
• smart environment handling
• colorized output log
• progress bars for processing completion
• the ability of stopping a running task from the GUI (stop button)
• a dialog for the AoI specification
• output preview for all (and not only) the tools that have an image as output

EOLi (Earth Observation Link) is the European Space Agency's client for Earth Observation Catalogue and Ordering Services. Using EOLi, you can browse the metadata and preview images of Earth Observation data acquired by the satellites ENVISAT, ERS, Landsat, IKONOS, DMC, ALOS, SPOT, Kompsat, Proba, JERS, IRS, Nimbus, NOAA, SCISAT, SeaStar, Terra/Aqua.

Scientific Users with a registered account can order or download products of various processing levels.

The software consists of a program lodr to list the content of the Orbital Data Records (ODRs), a subroutine library getorb.a that can be ported to some other program to interpolate the orbits and any given moment, and an example program getorb to demonstrate the use of the getorb.a library.

IMCORR takes two images and a series of input parameters and attempts to match small subscenes (called 'chips') from the two images. The program uses a fast fourier transform based version of a normalized cross-covariance method.

The most common use of this type of algorithm in image processing is to accurately locate tie-point pairs in two images to coregister them. However, if the images are already coregistered by other means, the algorithm may be used to find the displacements of moving features, provided that the features show little change in their appearance, and that the motion is strictly translational.

The correlation, peak finding, and error estimation routines in IMCORR are derived from FORTRAN subroutines from the Land Analysis System software (LAS) written at NASA Goddard Space Flight Center and USGS Eros Data Center.

IMCORR consists of a C code wrapper which makes the use of the routines more straightforward and automated for velocity-mapping applications.

Opticks is an expandable remote sensing and imagery analysis software platform that is free and open source. Unlike other competing tools, you can add capability to Opticks by creating an extension. Opticks provides the most advanced extension capability of any other remote sensing tool on the market.

Features:

• Supports the following file formats: NITF 2.0/2.1, GeoTIFF, ENVI, ASPAM/PAR, CGM, DTED, Generic RAW, ESRI Shapefile, HDF5, AVI, MPEG, JPEG, GIF, PNG, BMP
• Zoom, pan, rotate spatially large datasets
• Quickly layer GIS features, annotations, results, and other information over your data to provide context
• Many image display controls such as colormap, histogram, transparency, etc
• Support for datasets larger than four gigabytes
• Analysts can quickly combine steps using graphical wizards
• Support for processing data in it's native interleave of BIP, BSQ or BIL
• Get extensions to drop in new capability

Points2Grid generates Digital Elevation Models (DEM) using a local gridding method. The local gridding algorithm computes grid cell elevation using a circular neighbourhood defined around each grid cell based on a radius provided by the user. This neighbourhood is referred to as a bin, while the grid cell is referred to as a DEM node.

Up to four values - minimum, maximum, mean, or inverse distance weighted (IDW) mean - are computed for points that fall within the bin. These values are then assigned to the corresponding DEM node and used to represent the elevation variation over the neighbourhood represented by the bin. If no points are found within a given bin, the DEM node receives a value of null.

The Points2Grid service also provides a null filing option, which applies an inverse distance weighted focal mean via a square moving window of 3, 5, or 7 pixels to fill cells in the DEM that have null values.

GIAnT is a suite of Python libraries and scripts that implement various published time-series InSAR algorithms in a common framework. GIAnT was developed for

  1, Rapid generation of time-series products from interferogram.
  2. Direct comparison of time-series InSAR products using different
     algorithms.
  3. Cal-Val for time-series InSAR.

The toolbox currently includes implementations of SBAS, N-SBAS and MInTS algorithms. The toolbox also includes support for using weather model data for stratified troposphere corrections and GPS data for orbital error corrections.

The Next ESA SAR Toolbox (NEST) is a user friendly open source toolbox for reading, post-processing, analysing and visualising the large archive of data (from Level 1) from ESA SAR missions including ERS-1 & 2, ENVISAT and in the future Sentinel-1. In addition, NEST supports handling of products from third party missions including JERS-1, ALOS PALSAR, TerraSAR-X, Radarsat-2 and Cosmo-Skymed.

NEST helps the remote sensing community by supporting the handling of various SAR products and complimenting existing software packages. NEST has been built using the BEAM Earth Observation Toolbox and Development Platform and it covers the functionality of the older Basic Envisat SAR Toolbox BEST. NEST is currently undergoing development with periodic new releases. The major new functionality in NEST over BEST is an integrated viewer and orthorectification and mosaicking of SAR images.

NEST is extensible with an API that allows users to easily create their own plugin Readers, Processors and Writers. NEST is open source under the GNU General Public License (GNU GPL). If you are interested in contributing by developing a reader or writer for a product please contact us.

NEST is being developed by Array Systems Computing Inc. of Toronto Canada under ESA Contract number 20698/07/I-LG. InSAR functionalities are being developed by a joint effort of PPO.labs, Delft University of Technology and Array.

PyAPS is a python implementation of stratified tropospheric correction methods using inputs from global atmospheric models (GAM).

The package currently works with ERA-Interim Reanalysis, NARR and MERRA data, but can be easily extended to support more weather models.

Generic Python BUFR file reader based on the ECMWF BUFR library. File support is similar to the ECMWF BUFR library and the package currently only supports read-only mode.

This module is part of the Pytroll project.

ROI_PAC allows researchers in the area of topography and surface change to apply Interferometric Synthetic Aperture Radar (InSAR) methods.

InSAR is the synthesis of conventional SAR techniques and interferometry techniques that have been developed over several decades in radio astronomy and radar remote sensing, and in recent years has opened entirely new application areas for radar in the earth system sciences, including topographic mapping and geodesy [v. e.g., Thompson et al. 1986, Massonnet and Feigl 1998, Rosen et al. 2000].

ROI_PAC uses raw radar data, ancillary information from telemetry and navigation solutions, and digital elevation models (DEM; externally provided or interferometrically derived) to produce a variety of derived data products, including the full resolution images, interferograms, phase images measured as principal value and continuously "unwrapped," DEMs, and error estimates.

The Varres package implements a curvature-based quadtree-like interferogram resampler.

The original matlab package has been extended to include support for using a predefined map for resampling and estimation of an approximate covariance matrix for the samples.