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GEDI space lasers

Our guest today is Laura Duncanson PhD, an Assistant Professor for the Department of Geographical Sciences at the University of Maryland College Park. Since the beginning of her academic career, Laura’s eyes have been turned skyward to better understand and serve our planet. Her focus for years has been the user of Lidar technology to track the loss and growth of the world’s forests. In order to accomplish this, she has worked with the NASA Goddard Space Flight Center and a series of research partnerships, culminating in the Global Ecosystem Dynamics Investigation (GEDI) mission. 

What is GEDI?

The Global Ecosystem Dynamics Investigation (GEDI) project, launched in 2018, is a spaceborne Lidar mission with the objective of scanning the world’s forests in 3D. Mounted on the International Space Station (ISS), GEDI maps forest height, cover, and canopy changes. 

Of course, remote sensing scientists have been mapping forests with Lidar for years, what makes GEDI so groundbreaking? Well, one of the most important aspects of creating a scientifically useful aerial/satellite imagery dataset is the collection being taken from a fixed altitude. This is not too difficult to do for smaller areas.

Planes can be used at a national scale, and drones at a local scale, but until GEDI, there has not been a viable option for global scale Lidar.

Attachment to the ISS allows collections to be taken from a precisely known location, and for full Earth coverage to become a reality rather than an aspiration. 

GEDI is equipped with three lasers, which produce eight tracks of data. Each laser covers a 25m circle on the ground.

These tracks are spaced 60m by 600m apart, covering a span of 4.2km on the ground.

This does, however, leave significant coverage gaps between tracks, requiring multiple passes to fill in the gaps. Considering GEDI is attached to the ISS, it is limited to the ISS’s orbit. This means the extent of taskability is limited to “rocking” the sensor from side to side to capture oblique angles of the target.

 
ALONG TRACK LIDAR RETURN ENERGY SHOWING VERTICAL DISTRIBUTION OF VEGETATION (Courtesy of UMD)

GEDI is a near infrared Full Waveform Lidar System (vs a Discrete Return Lidar System which people are more familiar with). Full waveform Lidar captures a more continuous reading of returned photons, allowing more detailed data at the cost of it being more resource-intensive to interpret. Surfaces which reflect more photons, like bulky canopies, result in a greater returned waveform, where narrower features, like small trees, result in a smaller waveform reading. An excellent animation of this process is provided here.  

How is GEDI Useful?

The purpose of this highly detailed forest collection is for more than simply proving it can be done. Forest attributes like height and canopy cover can be used to quantify forest carbon content and change over time due to deforestation and afforestation.

Understanding the changes in carbon distribution in our world is vital for planning for the potential effects of climate change, and allows for monitoring real impacts of policies.

Although GEDI is state of the art technology, capable of collecting very high resolution data, it is not perfectly useful by itself.

Ground truthing and manual collections are still necessary to give complete meaning to the Lidar data.

The majority of forest carbon is sequestered in tree trunks. Given trunks are hidden under the tree’s canopy, they are very difficult to measure from the air, even with Lidar.

This means boots on the ground are necessary to collect training data on trunk measurements, which can then be combined with Lidar readings to extrapolate expected carbon values associated with different forest structures. 

The GEDI project has a network of international research partners who help to provide training datasets for their local forests. There are still areas, notably Central Asia, West Africa, and southern South America that lack any on the ground measurements. They also lack data from aerial Lidar missions (planes) to act as checks against the GEDI data.

The best solution until this collection becomes more feasible is to collect this data in ecologically similar areas, then use it to infer values in the underserved areas. 

The Future of GEDI

As futuristic as GEDI is, all of our forest data collection problems have not yet been solved. Being a near infrared system, GEDI is not capable of seeing through clouds, nor does it pass over the Poles. This, combined with the large gaps between collected tracks means it takes quite a while to get full wall to wall Lidar coverage of the Earth’s landmasses. 

GEDI has been planned to run until 2023, however, the hardware is predicted to last up to a decade.

Researchers are hoping to appeal to the proper authorities to have the mission extended.

This becomes an even more noble pursuit considering NASA’s plans to launch ISRO, a Synthetic Aperture Radar mission (NISAR) in 2023. There are untold possibilities when it comes to being able to combine data products from both Lidar, SAR, and standard imagery collections. Losing the Lidar component to this would be a tragedy, especially considering the current GEDI mission is a result of over 30 years of campaigning and research. 

Raw data is flashy, but ultimately of little use if the right tools do not exist to manipulate and derive meaning from it.

GEDI’s use of the less-popularized Full Waveform Lidar means that there is less existing data infrastructure than for discrete Lidar data formats.

Researchers and data scientists need to develop their own custom tools to capitalize on this information rich data. These currently take the form of Python and R packages. The NASA Data Center even provides some Juptyter notebooks, and the USGS provides LP DAAC for working with GEDI data. Although these obstacles cannot be overlooked, it means there is huge potential for growth in workflows and technology in the future as GEDI products become more widely integrated to existing and emerging systems. 

GEDI data is available for free download here, and a key to the various levels of data products provided can be found here