LIDAR - Creating maps with Big Data

LIDAR – Using Geospatial Data to map landscapes down to the doorknob

                A standard LIDAR (Light Detection and Ranging) system emits a beam of light from a laser source and then captures the returned light in sensors as it bounces back from a reflecting object, measuring the distance by calculating the time required for the round trip. The federal government has been using LIDAR systems since the 1960’s, but LIDAR data-gathering projects have been increasing since the year 2000. U.S. troops have used LIDAR systems to aid in mapping rugged and extreme terrain in the war zones of Afghanistan. Other examples of LIDAR systems that are pushing the Big Data envelope include the first forest height map used to measure carbon cycles in ecosystems created by a Colorado State University scientist. The Department of Land Management and the U.S. Forest Service use it for their forest inventory surveys. The technology has gotten less expensive and more accurate.

                The National Enhanced Elevation Assessment estimates that the LIDAR can be used to identify flood zones, how to mitigate flood risk and implement infrastructure and construction. The LIDAR projects can also provide information for farmers on where irrigation runoff can be expected and where to plant crops that requires the most expensive fertilizers. Cities are also using LIDAR to build 3D maps. One of the bigger projects of the LIDAR was the creation of the Red River Basin Decision Information Network (RRBDIN). The LIDAR was used to map the large swaths of North Dakota, Minnesota and central Canada. The Red River basin had a major flood in 1997 that resulted in the creation of the RRBDIN. The RRBDIN is managed by the International Water Institute with support from the U.S. Army Corps of Engineers, North Dakota State University Extension and other partners. The RRBDIN’s LIDAR viewer allows users to create and customize maps down to a small 2-foot hill. They can use these maps with the forecast display tool. When the National Weather Service generates a forecast for a flood they can plan for the inundation and extents of the flooding. 

  

 

                The principle behind the LIDAR is simple. By measuring the time it takes light to bounce off an object, and knowing the speed of light (186,000 miles per second), one can detect the distance of the object. The challenge has been in developing equipment that can fire rapid pulses of light – in some cases up to 150,000 pulses per second – and that can measure the returning light with accuracy. LIDAR systems vary in the pulses that are required for each project. The high-energy pulse systems are typically used for atmospheric research, while the lower-powered micro pulse systems are more often employed for downward scanning, since they are considered “eye safe.” Although most airborne LIDAR systems use 1064-nanometer laser beams, bathymetric LIDAR systems – those used to penetrate water – employ a narrower 532-nm beam. Bathymetric LIDAR also transmits two light waves, one infrared and the other green. As a result, it can detect two returning signals, one off the water surface and the other from the seabed. Other technological advancements are the higher-resolution and more flexible scanners, optics and photoreceptors. It is estimated that NOAA’s LIDAR scans are shooting between 100,000 and 200,000 points per second with up to 10cm of error. 

 

                Beyond collecting better data, LIDAR pioneers are focusing on educating those who can make the best use of the LIDAR data. “We spend a lot of time talking with the local stakeholders and developing relationships with people throughout the state, letting people know when flights are happening, who can gain from them, “ said John English, LIDAR data coordinator for Oregon’s Department of Geology. Implementers throughout the LIDAR community agree that right now the pressing need is for more applications that can make effective use of the data that has already been collected. The sensors on the LIDAR systems have developed to where they record very dense data. Processing and analyzing this data is becoming a real issue. Hiring analyst that knows how to process these large data sets and communicate the outcomes for the user community is the next step in further development of the LIDAR system. Knowing how to crunch the numbers is now more important than broadening the technology. 

Another interesting article: http://gcn.com/articles/2013/03/15/lidar-philadelphia.aspx