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Scalable Image Analysis for Tomorrow and Beyond


Live in the now or plan for tomorrow? Aren’t we often told to do both? I’ve been thinking quite a bit about the moment and the future as they relate to several topics on my front burner lately. As we released ENVI 5.2 this week – these thoughts are largely relevant. New technology to offer a migration path from the desktop to the cloud is here, as are tools for spatio-temporal analysis and full motion video. It seems as though many aspects of image analytics are changing at once. So it seems appropriate to focus my blog this week on the migration path itself and how some of these technologies are positioning businesses to leap into the future. Here are some related questions I have entertained recently: 

  • What can I do in the cloud that I can’t do at the desktop? Or alternatively – can I do everything I can do at the desktop inthe cloud?  This is probably the single most often asked question lately. The answer is largely – it depends. For the most part, yes - ENVI analytics you enjoy today can be accessed via API that enables cloud processing. But digging a bit deeper one should most definitely look at the new ENVI Task. These tasks take powerful analytics that were already available –and expose them in a new – and in my opinion – much easier paradigm to implement. What that means? Prototypes that used to take me an hour or two to write now take me 10’s of minutes. I’m sure you will notice the same. If you don’t – please give me a call.

  • What exactly is time-enabled data and what can I do with it that is new? I love this question because I am so excited about spatio-temporal analysis. The time enabled data I have seen come across my desk lately tend to come in three different forms. The first is the obvious – data that have time metadata enabling one to sort through an image collection chronologically. Visualizing information over a period of time is a powerful tool. Think about watching a field go from planting to maturity, or think about looking at the speed at which a flood can wreak havoc over a mountainside.  Another less obvious capability accessible with spatio-temporal analysis tools is the ability to sort information in and order you wish. Animating through a data collection in a certain order can shed light information that might otherwise be missed. For example, imagine the ability to take several non-chronological frames over an area of interest and animate through the frames in sequence – perhaps missing irrelevant information in-between.  With this capability, situational awareness takes on a new meaning.

  • And finally, one of the most popular uses of animating through a stack of data is to look at analysis products. For example – periodic MODIS temperature data can be analyzed to derive draught conditions over a particular area. This can be done with every platform revisit– in this case every 8 days. Viewing information such as draught conditions, vegetation health, water indices, or burn inform