If you need to visualize and analyze images from satellite sensors like SeaWiFS, CZCS, MODIS-Terra, MODIS-Aqua, GLI, OCTS, MERIS, NOAA AVHRR, MOS, AMSR-E, QuikSCAT, SSMI and projects like GlobColour in different formats (HDF, N1, CoastWatch, Terascan, ERDAS - LAN, NSIDC, NAVOCEANO, NGSST, etc.) in the Microsoft® Windows environment then you can use the easy to use but powerful Windows Image Manager = WIM.

Remote sensing professionals from universities, government agencies, environmental monitoring agencies, military R&D organizations, exploration and other business operations as well as casual users like geographers, oceanographers, marine biologists, fishermen in over 30 countries (see WIM User's list) are usiing WIM for its easy-to-use features (see WIM functions ).
W
IM runs under the current Windows operating systems.

If you are new to WIM, you may want to view the Introduction or browse through the User's Manual. You can download different satellite images from many sources (see a limited list of satellite data ).

WIM is NOT a tool for editing bitmap-type images (e.g. JPEG, GIF, PNG, TIFF, etc.).
With WIM you can easily read scientific datasets (SDS) in Hierarchical Data Format (HDF4), netCDF and Terascan datasets, use special functions for SeaWiFS, OCTS, CZCS, MODISA and MERIS ocean color imagery, National Snow and Ice Data Center's polar datasets, PO-DAAC and NAVOCEANO MCSST and Pathfinder global SST products, create overlays of coastlines and depth contours, and much more. Serious WIM users prefer to use WAM (=WIM Automation Module) to provide speed and power.  It is recommended to upgrade to the latest WIM/WAM as we upgrade often. Instructions how to install WIM and get started are given here.
Check out What's New in the latest version and the release history.
To download a free evaluation version click here. For more information please send
e-mail to
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WIM functions can be automated with the WIM Automation Module (WAM)
Some examples of WIM and WAM applications are available here.


Parts of WIM were developed by Artur Laksberg.

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