Despite what you may have heard, there’s A LOT more to GIS than “maps and data”: That’s why we’ve put together this comprehensive list of GIS definitions: We give you stunning visualizations so you can have 20/10 vision of each definition term.From A to Z, GIS professionals, students and everyone with an interest can sharpen their GIS knowledge with these GIS dictionary definitions and meanings.
Category: Remote Sensing
You’ve probably heard about machine learning (ML). But you’re not exactly sure how to use it in the context of GIS.
Simply, machine learning makes sense out of noisy data finding patterns that you’d never think existed. In other words, it’s software that writes software. Instead of applying a pre-built function, ML gains experience through repeated seen conditions and builds a model to apply in new situations. For example, Google might use Bayesian classification to filter spam emails. Alternatively, Facebook might use it for facial recognition and automatically identify faces in images. And ML can even render Nicholas Cage in every movie ever made.
As a modern-day city dweller, you may not feel it, but if you were trying to use Google Maps on a vacation in rural Thailand, you would realize the worldwide road network is so vast, even Google is yet to map the majority of it!
This is what made a group of researchers at Massachusetts Institute of Technology (MIT) look for ways to lessen the workload of app developers like Google Maps. Enter RoadTracer, an artificial intelligence powered program that can extract road networks from aerial imagery – with 45% more success rate than existing methods.
If you want the sharpest satellite imagery in the world, then you should harness the power of DigitalGlobe satellite imagery.
To give you a ballpark figure: Each pixel in a Worldview-3 image is about the size of home plate on a baseball diamond. That’s about 31 cm. So instead of being far-sighted, you can see a better and clearer world with some of DigitalGlobe’s products.
There is a real need to create new, insightful information products that can be used to proactively investigate flood-prone areas across a whole range of scales – from sites to river basins to a national level. Elevation is the single most important variable in determining flood hazard levels, and we focus on this by developing three flood analysis tools. Each can be implemented at scale and is a significant undertaking. We hope these tools can provide more geographic context and shed light on some key hydrodynamic processes about flooding.
The word best have been overused. Checkout the best Web Maps available online.
NDVI is the most common index that analysts use in remote sensing. But how do you calculate it? What do NDVI values represent? How do Earth scientists use NDVI?