Award Abstract # 1226145
Collaborative Proposal: Making Point Clouds Useful for Earth Science

NSF Org: EAR
Division Of Earth Sciences
Recipient: IDAHO STATE UNIVERSITY
Initial Amendment Date: August 20, 2012
Latest Amendment Date: July 12, 2013
Award Number: 1226145
Award Instrument: Continuing Grant
Program Manager: Leonard E. Johnson
EAR
 Division Of Earth Sciences
GEO
 Directorate for Geosciences
Start Date: September 1, 2012
End Date: September 30, 2013 (Estimated)
Total Intended Award Amount: $219,000.00
Total Awarded Amount to Date: $219,000.00
Funds Obligated to Date: FY 2012 = $0.00
FY 2013 = $0.00
History of Investigator:
  • Nancy Glenn (Principal Investigator)
    nancyglenn@boisestate.edu
  • Andrew Hudak (Co-Principal Investigator)
Recipient Sponsored Research Office: Idaho State University
921 S 8TH AVE
POCATELLO
ID  US  83201-5377
(208)282-2592
Sponsor Congressional District: 02
Primary Place of Performance: Idaho State University
ID  US  83209-0002
Primary Place of Performance
Congressional District:
02
Unique Entity Identifier (UEI): JJC9GJJJL4M7
Parent UEI:
NSF Program(s): Instrumentation & Facilities,
GEOINFORMATICS
Primary Program Source: 01001213DB NSF RESEARCH & RELATED ACTIVIT
01001314DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 9150
Program Element Code(s): 158000, 725500
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.050

ABSTRACT

This collaborative project between Idaho State University (ISU), Utah State University (USU), and USFS Rocky Mountain Research Station (RMRS) will develop the next generation of analytical and processing tools for new airborne and ground-based LiDAR monitoring data. The tools will help earth scientists and natural resource managers exploit these data streams to address some of our most pressing environmental questions and management challenges. The software tools will target 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/or Structure from Motion (SfM). 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 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. 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.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Murgoitio, J, R Shrestha, N Glenn, and L Spaete "Airborne LiDAR and terrestrial laser scanning derived vegetation obstruction factors for visibility models" Transactions in GIS , v.TBD , 2013 , p.TBD DOI:10.1111/tgis.12022

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