Satellite Remote Sensing of the Oceans
As I have mentioned, IDL is our favorite package for dealing with satellite images even though many are available. Most tend to be inflexible and tailor-made for doing specific types of image analysis. IDL can do most of the same operations more cheaply and flexibly while allowing you to interact with the data and merge data from several sources. However, IDL is a programming language in its own right, so there is a learning curve inherent to using it.
The choice of other system components is not as critical as choosing the video card, motherboard, processor and monitor. When it comes to backing up our data, an Exabyte drive suits us nicely for backing up anything less than 5GB in size.
Again, IDL is the main processing software for this type of work. Many users feel they are comfortable using LaTeX under Linux too, although this appears to be a point of contention. Most of us are still locked into using MS Word for want of a cheap Linux word processor that is Word compatible and can handle multiple data formats and equations. We are now looking at some alternatives like Applixware.
Linux has reduced the computing cost of the Oceanography Department's satellite remote sensing group in terms of both time and money. Its stability has been its greatest asset in converting die-hard Windows fanatics into potential Linux gurus. For many of us Linux has enabled us to embark on a voyage of discovery into the computing world. We now have a deeper understanding of how our PCs work as Linux has brought us closer to the machine. We are currently reviewing the hardware and software requirements of the group for the next couple of years. We plan to continue using Linux well into the next millennium and are quite happy with the decision.
The SAR images in this article were obtained free from the European Space Agency.
Getting Started with DevOps - Including New Data on IT Performance from Puppet Labs 2015 State of DevOps Report
August 27, 2015
12:00 PM CDT
DevOps represents a profound change from the way most IT departments have traditionally worked: from siloed teams and high-anxiety releases to everyone collaborating on uneventful and more frequent releases of higher-quality code. It doesn't matter how large or small an organization is, or even whether it's historically slow moving or risk averse — there are ways to adopt DevOps sanely, and get measurable results in just weeks.
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