Progressive Curvature Filtering (PCF)
Entry ID: LIDAR-PCF

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Summary
Abstract: Progressive Curvature Filtering (PCF) is an iterative, multiscale approach for
finding positive curvatures representing non-ground returns in discrete return
LiDAR. The complex vertical arrangement of LiDAR data requires an iterative
processing approach to converge on an accurate solution of identified ground
returns. Through nested iterations, the PCF algorithm robustly addresses
topologic ... View entire text
Related URL
Description: AML to perform Progressive Curvature Filtering
Service Citation
Title: Progressive Curvature Filtering (PCF)
Provider: USDA - Rocky Mountain Research Station.
URL: http://forest.moscowfsl.wsu.edu/lidar/
Service Keywords
REFERENCE AND INFORMATION SERVICES >KNOWLEDGE/DECISION SYSTEMS Parameter Definition
MODELS >DIGITAL ELEVATION/DIGITAL TERRAIN MODELS Parameter Definition
MODELS >SOCIAL AND ECONOMIC MODELS Parameter Definition
MODELS >LAND SURFACE MODELS Parameter Definition

ISO Topic Category
Service Provider
USDA/FS/RMRS/MGSL > Moscow Forestry Sciences Laboratory, Rocky Mountain Research Station, Forest Service, U. S. Department of Agriculture Supplemental Info
Service Organization URL: http://forest.moscowfsl.wsu.edu/

Service Provider Personnel
Name: DENNIS E. FERGUSON
Phone: (208) 882-3557
Contact Address:
Forest Ecosystem Processes
Rocky Mountain Research Station
1221 South Main Street
City: Moscow
Province or State: ID
Postal Code: 83843
Country: USA
Personnel
Role: TECHNICAL CONTACT
Phone: (208) 882-3557
Contact Address:
Forest Ecosystem Processes
Rocky Mountain Research Station
1221 South Main Street
City: Moscow
Province or State: ID
Postal Code: 83843
Country: USA
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Publications/References
J. S. Evans, A. T. Hudak. A Progressive Curvature Filter for Identifying Ground
Returns from Discrete Return LiDAR in Forested Environments. (Submitted IEEE
Transactions on Geoscience and Remote Sensing).

R. A. Haugerud and D. J. Harding. 2001. Some Algorithms for Virtual
Deforestation (VDF) of Lidar Topographic Survey Data. International Archives of
Photogrammetry and Remote Sensing, Graz, Austria, vol. XXXIV-3/W4, pp. 211-217
Creation and Review Dates
SERF Creation Date: 2006-05-09
SERF Last Revision Date: 2011-01-27

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