A Look Ahead at 2016
As much as I appreciate a good reflection on the past, after a week in the fresh (and cold!) mountain air I am excited to look ahead! 2016 is here and one thing is certain, as far as trends go I predict that the theme this year will be end-to-end integrated solutions. What that means is that we (software companies) need to continue to provide excellent analytics (ENVI) that work well in an environment with many moving parts (the enterprise) to solve a problem from start to finish – in a seamless manner (using both ours and others’ solution suites). Yes that’s a mouthful. But, I do believe that there is a clear need to be nimble, flexible, and deliberate when it comes to proposing and delivering tools to solve problems.
For example, if you haven’t already seen my colleague Barrett’s blog about a new web interface for Precision Agriculture you should take a look! This is a perfect example of a scalable solution to take any data (satellite, airborne, UAS), perform some analysis, and export results. Not only that – but customers are adding custom algorithms for inventory, prescriptive maps, and more within the same interface which by definition illustrates scalability!
Agriculture Toolkit for ENVI displayed with plant count inventory custom algorithm example image.
Speaking of algorithms, many applications for precision agriculture have been taking advantage of ENVI’s spectral indices (66 now!) for various analyses in some exciting new ways! For example, take a look at this Pleiades image courtesy of Airbus. This image has been calibrated corrected for atmosphere, and run through several of ENVI’s spectral indices. It is easier than ever before to not only apply a color table (top left) to an index to bring out features of interest, but also to combine indices with one another to generate false color composites. As you can see, the false color composite of three indices differentiates some features (red) that are not well defined in one index alone.
Pleiades image courtesy of Airbus Defense and Space. Left: Difference Vegetation Index with color table applied. Right: false color composite of Visible Atmospherically Resistant Index (R), Soil Adjusted Vegetation Index (G), and Sum Green Index(B).
Also worth mention if you’re planning to work with LiDAR this year are some great things adding to your ability to interact directly with the point cloud. Not only can you now color your points by classification code, but it is also easy to interact directly with the points by turning entire classes on or off for more immediate data insight, as well as controlling the density of points displayed. The latter is useful with new datasets such as Geiger Mode LiDAR that capture very high point density from very high altitudes. Additionally, users from anywhere can access tools like building extraction directly from within a web page, which means there is no need for all users to install and maintain software!
Geiger Mode LiDAR point cloud colored by classification code.
End-to-end complete workflows are the thing of the “now”, not the future. I look forward to working with you all this year!