Sensors and More Sensors
oIt's that time of year again when many of us around our office find ourselves busy getting ready for the Esri User Conference (UC). While this time of year is most certainly stressful, I always enjoy preparing for the Esri UC because it gives me the opportunity to take stock of what I have noticed going on in our industry. There's a lot going on in the worlds of remote sensing and geography right now, but from my perspective, one of the most exciting things is the rapid proliferation of spaceborne and airborne sensors. Rising demand for remotely sensed data coupled with falling costs for building and deploying spaceborne and airborne sensors means that we have a lot more data to work with.
With spaceborne sensors, there seems to be a divergence in the commercial market. Some companies are deploying larger satellites carrying multiple sensors capable of capturing images with higher spatial and higher spectral resolution than ever before. Other companies are deploying a constellation of much smaller satellites with high spatial resolution multispectral sensors in order to capture as much of the earth's surface as possible at any given time. Having such a constellation of satellites also allows for rapid revisit times which can be very beneficial for many applications, such as agricultural crop monitoring. The good news for us, the users of remotely sensed data, is that we benefit from both of these approaches.
The image above, captured by WorldView-3 from DigitalGlobe shows a Short Wave Infrared (SWIR) band combination of Cuprite, Nevada. The high spatial resolution SWIR bands available from WorldView-3 are unique in the commercial remote sensing industry and can be used for a myriad of applications, including material identification, land use classification, and mining.
The image above shows an Optimized Soil Adjusted Vegetation Index (OSAVI) calculated from multiple Pleiades images from Airbus Defense and Space. The Pleiades satellites offer high spatial resolution multispectral imagery. The Airbus Defense and Space constellation of satellites allows for rapid revisit times, which is ideal for such uses as monitoring crop health throughout a growing season.
This year, the Federal Aviation Administration (FAA) selected six test sites for Unmanned Aerial Systems (UAS) and also began granting exemptions to a range of companies flying UAS. There is no doubt that the emerging UAS market will make a huge impression on the remote sensing industry. We are already beginning to see the use of UAS data for such applications as natural disaster monitoring, wildlife observation, precision agriculture, surveying, and more. In the image below, a point cloud has been generated from high spatial resolution multispectral images captured by a UAS. This point cloud can further be used to generate a Digital Elevation Model (DEM) and contour lines for the area of acquisition. This is pretty cool stuff and it's just one of the many applications for UAS data.
Speaking of point clouds, there have also been some advancements in the realm of LiDAR. Geiger-mode LiDAR is an interesting new commercial technology that enables the collection of data at higher resolutions and from higher elevations than traditional linear-mode LiDAR collection. Harris recently introduced the world's first commercial Geiger-mode LiDAR sensor. This interesting method of LiDAR point cloud collection means that we can collect higher resolution point clouds over broader areas at a much cheaper cost than traditional LiDAR collection methods. The point cloud in the image below was captured by a Geiger-mode LiDAR sensor. It might be a little hard to see, but I circled the point cloud density in the image below. In the most dense areas of the scene, the point cloud density is almost 200 points per square meter, with an average density throughout the scene of around 75 points per square meter. That's pretty dense!
There are, of course, too many new sources of remotely sensed data to mention in this blog post, but that's sort of my point. I have said nothing of publicly-funded earth observing sensors, such as the Advanced Baseline Imager (ABI) being built for the next generation of Geostationary Operational Environmental Satellites (GOES), or the Magnetosphere Multiscale Mission, which will investigate how the Sun's and Earth's magnetic fields connect and disconnect. This is all really cool stuff, but perhaps too much to go into detail here.
With all of these sensors producing all of this data comes the need to store, process, and make sense of it all. This is where I like to play and I am excited about some of the new tools we will be showing at this year's Esri UC - from new methods of processing and visualizing data in our ENVI desktop software to new ways to process data in enterprise and web-based environments. If you happen to be headed to this year's Esri UC, please stop by the Harris booth to say hello.