Idaho and Regional LiDAR Research

Participants and Collaborators:
University of Idaho, University of Montana, Montana State Unversity, South Dakota School of Mines and Technology, University of North Dakota (UMAC), Rocky Mountain Research Station - Moscow, USDA Agricultural Research Station (Boise), USDA FS Remote Sensing Applications Center (RSAC), NASA AMES/Goddard

Who Are We and What do We do?

We are a broad research team from a diverse range of insitutions. Our group conducts algorithm development; forestry, range, and geological applications; in addition to outreach via informative ForestPARC workshops with groups such as the USDA FS Remote Sensing Applications Center (RSAC), Salt Lake City.

Follow This Link for our Lidar Web Tutorial ...

Research at a glance:

Participant researchers at the USDA Forest Service Rocky Mountain Research Station, Moscow are leading the development of a bare earth model (BEM) algorithm that is suitable in large biomass areas.

In particular, J.Evans and A.Hudak (IEEE Transactions on Geoscience and Remote Sensing, in press) have developed a new algorithm entitled the 'Progessive Curvature Filter'. A comparison of PCF with the commonly applied 'Block Minimum' is shown below. Ths algorithm is already widely used by the USDA Argricultural Research Service (ARS), RSAC, and our university particpants.


        All Returns                   Block Minimum                        PCF

In addition to BEM algorithms, our research groups have been developing novel methods to extract tree-level characteristics from canopy height models (CHMs). Work by A.M.S. Smith, M.J. Falkowski et al (Falkowski et al 2006; Canadian Journal of Remote Sensing) highlights how 'Spatial Wavelet Analysis' can be applied to extract tree crown widths and maximum tree heights from an open-canopy mixed conifer forest stand in northern Idaho:

In the University of Idaho's Department of Geography, Lidar research by J Rooker Jensen, K Humes, and others have focused on evaluating the technology's capabilities to measure forest inventory within the Nez Perce Resevation, nothern Idaho.

T.Link at the University of Idaho is working with the USDA Argicultural Research Station to acquire a several 100K ha acquisition of rangelands to enable vegetation structure mapping for hydrological and radiative transfer models.

At the University of Montana's National Center for Fire Landscape Analysis, C Sielestad, L Queen, et al are involved in the assessment of surface fuel models.

At the University of Idaho, our research team alongside the RMRS-Moscow has been for several years been using LiDAR to map the Priest River Experimental Forest (PREF), Moscow Mountain, and the St. Joe's National Forest

           
   
Priest River Experimental Forest forest canopy height estimate images     

A.Hudak et al has considerable experience in integrating LiDAR with multispectal satellite sensor imagery. Following on from Hudak et al (2002) in which LiDAR and Landsat ETM+ data were integrated, Hudak et al (2006) used both ALI (EO-1 Satellite) with LiDAR to model paramters such as Basal Area and Tree Density on Moscow Mountain.



On a related research topic, R.Lawrence at Montana State University is investigating the fusion of polarimteric synthetic aperture radar and hyperspectral imagery of landcover classification in Yellowstone National Park

We Also do Outreach and Extension Activities:

These events have mainly been achieved through ForestPARC (Sucess Stories). The following snapshots are of our May 2005 Workshop, which was hosted in coordination with the USDA Forest Service RSAC.



As shown above, this workshop included an Expert Panel Discussion, Vendor presentations, and Breakout sessions.

ForestPARC is currently cordinating with the CLICK group at the USGS - EROS Data Center, who have recently set-up a national depositary for XYZ LiDAR Data. ForestPARC is working with CLICK to establish a series of standarized products that will be avialable from the CLICK interface.

Group Publications and Proceedings Page