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Project Type: Sponsored Research
Project Sponsor: National Science Foundation - Geoinformatics Project Location: Not Site Specific Status: Funded |
project overview
purpose of project
This project seeks to develop the next generation of analytical and processing tools for new airborne and ground-based LiDaR monitoring data to help earth scientists and natural resource managers exploit these data streams to address some of our most pressing environmental questions and management challenges.
Project Summary:
Intellectual Merit:
This 2-year collaborative project between Idaho State University (ISU), Utah State University (USU), and USFS Rocky Mountain Research Station (RMRS) will advance discoveries in Earth Science by developing software tools for Earth Science-specific analysis of 3-D point cloud data from platforms like airborne LiDAR (ALS), ground-based LiDAR (TLS), multi-beam SONAR (MBS), and Structure from Motion (SfM). The tools will improve the precision of point clouds along fault scarps and facilitate analysis across time and space of landslides, fluvial, glacial, aeolian, thermokarst, and other landform features. The tool development will scale-up existing documented and proven algorithms to be more accessible, as well as build new algorithms that are necessary to address emerging Earth science challenges such as change detection analysis from repeat surveys, improved bare earth surface generation, and novel fusion of point clouds collected from different platforms (e.g. ALS and TLS). The new software will be developed collaboratively between geoscientists and computer scientists to optimize performance when handling the large and often problematic data volumes associated with point clouds. Recent increases in the ease and scope of acquisition and subsequent availability of 3D point cloud data have yielded critical advances in a range of Earth science disciplines, including geomorphology, tectonics, engineering geology, and soil science. However, despite the increasing amount of available data, the management, processing and interpretation of point cloud data are still bottlenecks and typically are the most time consuming elements of the scientific workflow. In addition, new tools are needed that can leverage evolving point cloud acquisition technology and the ever larger and higher-resolution data being acquired. The algorithm development we propose will focus on multitemporal analysis, improved height filtering using automatic parameterization, intensity normalization and automatic gain control correction, and transferability of analysis tools between the various platforms (e.g. ALS, TLS, MBS, SfM). This project will also create a GUI-based wizard interface for LiDAR processing and analysis, which will simplify and automate the workflow for earth scientists. Resultantly, this work will provide a suite of community software that will permit innovative and potentially transformative data analysis with the potential to enhance our understanding of numerous earth surface processes.
Broader Impacts:
The algorithms developed herein will be made widely available to a diverse user community via a scalable approach. Targeted user communities range from existing and new desktop ‘power’ users to the larger geoscience community interested in easy-to-use processing mechanisms via the web-based OpenTopography portal. The tools will also be released as both web applications and stand-alone applications with the codes all exposed through open source licenses. ISU’s, USU’s, and RMRS’s existing point cloud and raster tools and OpenTopography all have large user communities (collectively, the tools from ISU, USU, and RMRS have been downloaded several thousand times) and the new tools in this project will serve an even wider audience. We expect that hundreds of new users will employ and benefit from these tools based on the existing user base, enhanced exposure provided by integration into OpenTopography, and the growing ease of acquisition and interest in 3-D point cloud data. Furthermore, the PIs will distribute the tools through their activities in the hydrology, geology, geomorphology, and cyberinfrastructure communities within and outside their states. The PIs already actively help federal and state agencies such as the USDA, USFS, USGS, NOAA, NPS and ARS and BLM with point cloud monitoring and analysis challenges. These new tools will be exposed to these agencies through existing and new contracts and training. The project researchers publish regularly in the scientific literature, teach short courses in LiDAR (3 workshops and 1 webinar are planned for this project), and participate in outreach efforts (e.g. LiDAR-based 3D visualizations of snowpack for water resources). Such outreach activities will be strengthened in this project. For example, a 3D visualization is planned using the ALS and TLS point clouds data fusion tool to demonstrate fault scarp delineation at the TLS scale, in the context of a larger scale ALS dataset for a potential hydro-electric site in Idaho. Similarly a how-to video on using the GCD employed on OpenTopography will be highlighted for the Columbia Habitat Monitoring Program (NOAA and EPA). In 100-500 words summarize the research project.
This 2-year collaborative project between Idaho State University (ISU), Utah State University (USU), and USFS Rocky Mountain Research Station (RMRS) will advance discoveries in Earth Science by developing software tools for Earth Science-specific analysis of 3-D point cloud data from platforms like airborne LiDAR (ALS), ground-based LiDAR (TLS), multi-beam SONAR (MBS), and Structure from Motion (SfM). The tools will improve the precision of point clouds along fault scarps and facilitate analysis across time and space of landslides, fluvial, glacial, aeolian, thermokarst, and other landform features. The tool development will scale-up existing documented and proven algorithms to be more accessible, as well as build new algorithms that are necessary to address emerging Earth science challenges such as change detection analysis from repeat surveys, improved bare earth surface generation, and novel fusion of point clouds collected from different platforms (e.g. ALS and TLS). The new software will be developed collaboratively between geoscientists and computer scientists to optimize performance when handling the large and often problematic data volumes associated with point clouds. Recent increases in the ease and scope of acquisition and subsequent availability of 3D point cloud data have yielded critical advances in a range of Earth science disciplines, including geomorphology, tectonics, engineering geology, and soil science. However, despite the increasing amount of available data, the management, processing and interpretation of point cloud data are still bottlenecks and typically are the most time consuming elements of the scientific workflow. In addition, new tools are needed that can leverage evolving point cloud acquisition technology and the ever larger and higher-resolution data being acquired. The algorithm development we propose will focus on multitemporal analysis, improved height filtering using automatic parameterization, intensity normalization and automatic gain control correction, and transferability of analysis tools between the various platforms (e.g. ALS, TLS, MBS, SfM). This project will also create a GUI-based wizard interface for LiDAR processing and analysis, which will simplify and automate the workflow for earth scientists. Resultantly, this work will provide a suite of community software that will permit innovative and potentially transformative data analysis with the potential to enhance our understanding of numerous earth surface processes.
Broader Impacts:
The algorithms developed herein will be made widely available to a diverse user community via a scalable approach. Targeted user communities range from existing and new desktop ‘power’ users to the larger geoscience community interested in easy-to-use processing mechanisms via the web-based OpenTopography portal. The tools will also be released as both web applications and stand-alone applications with the codes all exposed through open source licenses. ISU’s, USU’s, and RMRS’s existing point cloud and raster tools and OpenTopography all have large user communities (collectively, the tools from ISU, USU, and RMRS have been downloaded several thousand times) and the new tools in this project will serve an even wider audience. We expect that hundreds of new users will employ and benefit from these tools based on the existing user base, enhanced exposure provided by integration into OpenTopography, and the growing ease of acquisition and interest in 3-D point cloud data. Furthermore, the PIs will distribute the tools through their activities in the hydrology, geology, geomorphology, and cyberinfrastructure communities within and outside their states. The PIs already actively help federal and state agencies such as the USDA, USFS, USGS, NOAA, NPS and ARS and BLM with point cloud monitoring and analysis challenges. These new tools will be exposed to these agencies through existing and new contracts and training. The project researchers publish regularly in the scientific literature, teach short courses in LiDAR (3 workshops and 1 webinar are planned for this project), and participate in outreach efforts (e.g. LiDAR-based 3D visualizations of snowpack for water resources). Such outreach activities will be strengthened in this project. For example, a 3D visualization is planned using the ALS and TLS point clouds data fusion tool to demonstrate fault scarp delineation at the TLS scale, in the context of a larger scale ALS dataset for a potential hydro-electric site in Idaho. Similarly a how-to video on using the GCD employed on OpenTopography will be highlighted for the Columbia Habitat Monitoring Program (NOAA and EPA). In 100-500 words summarize the research project.
Related Links & Research
project outputs
project details
Project PI: Nancy Glenn (Idaho State University - Boise Center Aerospace Laboratory)
USU PI: Joseph Wheaton (Project Co-PI)
Project Collaborators: Andrew Hudak (Rocky Mountain Research Station - USFS), Philip Bailey (North Arrow Research)
Funding Source: National Science Foundation - Geoinformatics .zCloud Tools is supported by the National Science Foundation under Awards #1226145 and #1226127 "Collaborative Proposal: Making Point Clouds Useful for Earth Science"
Project Start Date: September: September, 2012
Project End Date (anticipated): August, 2015
USU PI: Joseph Wheaton (Project Co-PI)
Project Collaborators: Andrew Hudak (Rocky Mountain Research Station - USFS), Philip Bailey (North Arrow Research)
Funding Source: National Science Foundation - Geoinformatics .zCloud Tools is supported by the National Science Foundation under Awards #1226145 and #1226127 "Collaborative Proposal: Making Point Clouds Useful for Earth Science"
Project Start Date: September: September, 2012
Project End Date (anticipated): August, 2015
