Value: “The importance or preciousness of something”. New information, innovation, and discovery – these are things of value. And whether we are improving upon products and processes we already employ, or we develop a new way to look at the world, we are bound to discover new information. It is in the latter case that I think about the ways in which we are already seeing LiDAR data analysis bring value to the world of remote sensing.
By design, LiDAR pulses penetrate forest canopy and literally enable us to uncover the bare earth that lies beneath. In revealing bare earth DEMs we are able to identify things (like lost cities and hidden faults) that were previously missed. Case in point includes two recent publications highlighting discoveries that were made by revealing the earth’s surface as it would look without canopy coverage.
The first was a collaborative effort between the University of Huston and the National Science Foundation. High resolution bare earth DEMs were derived from dense LiDAR data. These DEMs revealed ancient building ruins as well as some agricultural features that were undiscovered by ground crews who had been studying in the area for more than 25 years. The images below illustrate the dense canopy in the area that only when removed reveal features of the scale and shape that would suggest the presence of a village. Incidentally it is thought that this ancient village is actually the “legendary lost city of Ciudad Blanca.”
Another recently published example in the Geological Society of America bulletin uncovered an association of seismically triggered landslides in the Tahoe-Sierra frontal fault zone in CA. As in the previous case, high-resolution bare earth DEMs were derived from LiDAR point clouds. We were already aware of moraine and alluvial movement in the area. What was revealed through this study was a significant increase in the vertical separation rate along the fault. Additionally, the associated estimates of seismic moments (how big an earthquake might be) were significantly greater than in previous estimates. In other words, the potential magnitude of earthquakes resulting from movement along the fault is significantly greater than we previously thought. Larger seismic disturbances equate to increased landslide hazards. Now that’s valuable information! Below is an image of the area where the fault is clearly visible in the image below.
What valuable discoveries are you making with your LiDAR data?