Commercial imagery resolution is down to 30 centimeters.With modern interpolation techniques, you can produce images with a 15-centimeter resolution equivalent. You canidentify features in pastures that otherwise would not have been visible. Counting livestock is important on several levels — for animal disease control and for inventory.
Super-resolution originates from the computer vision domain.The quality of an image is defined by its resolution. Super-resolution gives you a better image by applying an algorithm — to get a higher resolved image. It’s like upsampling, just smarter.
Google Earth Engine is acloud computing platform for scientificanalysis andvisualization of geospatial data sets. It isfree to use for research, education, and nonprofit. Google Earth Engine is essentially streaming data. You don’t need to go online to download the data — you just need a browser, and you can access the entire Google Earth Engine data catalog and a bunch of tools to do the analysis and visualization.
Instead of one long antenna that sends one big pulse at one time and then collects the pulses that come back, SAR have a much smaller antenna that sends lots of pulses in quick succession over time as the satellite goes through space.It “listens” to the pulses that come back to it when it moves through its orbit.That’s why the name synthetic is applied to the radar.
SBAS stands for Satellite-Based Augmentation System to standard GPS or GNSS signals. It’s a service that improves the quality of positioning from GPS — from multiple meters down to sub-meter level.SBAS uses similar technologies to other high-precision correction services people might be familiar with. It leverages an entire network of continuously operating reference stations around the ground area.
Commercial satellite providers produce somewhere between 100 and 200 terabytes of imagery a day ̶ a monstrous amount of information. Sentinel 2 has five years of daily refresh data. We have 40+ years of Landsat data. It’s a massive amount, particularly in the temporal dimension, where you can do longitudinal studies. Apache Spark and Raster Frames might just be the tools we need to handle this much data.