OpenTopography Introduces Tool to Calculate Landscape Change from Lidar Data

Published July 27, 2021

By: Daniel Kim, SDSC Research Experience for High School Students (REHS)

Measuring landscape change is critical for understanding our changing planet. Yet the tools for conducting these analyses are computationally intensive and require a high degree of geospatial expertise. In order to significantly reduce these barriers, researchers from the San Diego Supercomputer Center (SDSC) at UC San Diego recently collaborated with scientists at Arizona State University (ASU) and UNAVCO, a non-profit university-governed consortium, to build on-demand topographic differencing tools that can reveal surface changes from events such as earthquakes, volcanic eruptions, landslides, climate change and urban development.

The researchers’ efforts are summarized in a recent article, Measuring Change at Earth’s Surface: On-Demand Vertical and Three- Dimensional Topographic Differencing Implemented in OpenTopography, in the journal Geosphere.

The topographic change tools described in the paper show human activity and natural processes. Examples include construction in Salt Lake City, a volcanic eruption in Hawaii, a landslide in Colorado and sand dune migration in New Mexico. The topographic differencing capabilities operate on high resolution topography datasets with at least one observation of elevation per 10 feet² and were collected with a lidar (LIght Detection And Ranging) instrument.

As governments and organizations continue to invest in new high resolution topography datasets, this on-demand differencing tool was developed to capture ongoing changes on our planet from natural disasters, climate change and urbanization. 

The open access paper specifically details the implementation of newly developed on-demand OpenTopography tools. The work describes several approaches to standardize the differencing workflow—including algorithm choice and the ideal resolution of the derived surface displacements that indicate landscape change.

According to ASU Lead Researcher and OpenTopography Co-Investigator Chelsea Scott, “Change detection can be calculated with vertical or 3D differencing algorithm options. Vertical differencing measures change from processes with primarily vertical change including urban growth, deforestation, river erosion and coastal processes. 3D differencing also resolves horizontal displacement, for example from earthquakes and slow-moving landslides. These on-demand web-based differencing tools remove the expertise and time-investment required to study landscape change.”

“OpenTopography is once again lowering the barrier for access to not just data but also compute intensive tools by enabling the tools to be run on-demand via a web-based portal,” said Viswanath Nandigam, principal investigator of the National Science Foundation-funded OpenTopography project at SDSC. “Having these tools readily available to operate on an ever-growing repository of high-resolution topography datasets will allow researchers to conduct 4D analysis to quantify a changing planet.”

The topographic differencing tools are also being used in classroom settings where students can develop their geospatial skills by performing compute intensive topographic differencing on cyberinfrastructure resources located at SDSC. 

OpenTopography is supported by the National Science Foundation under award numbers 1948997, 1948994 and 1948857.

About SDSC

The San Diego Supercomputer Center (SDSC) is a leader and pioneer in high-performance and data-intensive computing, providing cyberinfrastructure resources, services and expertise to the national research community, academia and industry. Located on the UC San Diego campus, SDSC supports hundreds of multidisciplinary programs spanning a wide variety of domains, from astrophysics and earth sciences to disease research and drug discovery. SDSC's newest National Science Foundation-funded supercomputer, Expanse, supports SDSC's theme of "Computing without Boundaries" with a data-centric architecture, public cloud integration and state-of-the art GPUs for incorporating experimental facilities and edge computing.