US Forest Service
 

Pacific Northwest Research Station

 
 
 
Pacific Northwest Research Station
333 SW First Avenue
Portland, OR 97204

(503) 808-2100

US Forest Service
Pacific Northwest Research Station logo.
Hans-Erik Andersen.

Hans-Erik Andersen

Program: Resource Monitoring and Assessment/Forest Inventory and Analysis
Title: Research Forester
Address: USDA Forest Service Pacific Northwest Research Station
University of Washington
Anderson Hall, Room 107 (Express Mail drop-off)
P.O. Box 352100
Seattle, WA 98195-2100
Phone: 206-221-9034
Email: handersen@fs.fed.us

 

Jump to Publications

 

Education

  • University of Washington, Ph.D., 2003
  • International Institute for Aerial Survey and Earth Sciences (ITC), Professional Master Degree, 1998
  • University of Washington, M.S., 1997
  • Williams College, B.A., 1994

 

Current Research

My research consists of developing new techniques for using remote sensing and other geospatial technologies within large-scale, multiobjective resource inventory systems. The scale of the Alaskan landscape, and the remoteness and lack of access to most of the forest and related ecosystems, requires development and application of inventory and monitoring techniques that largely depend on remotely acquired information, which must be integrated with field-based information in innovative and complex statistical sampling designs. I investigate how emerging geospatial/remote sensing technologies and analytical techniques can best be applied to assess the extent, condition, use, and trends associated with Alaska’s ecosystems and natural resources.

Why This Research is Important

This research is important because adequate technology has not been developed or applied to effectively, and comprehensively, inventory and monitor the forested ecosystems of Alaska. Therefore, critical baseline information on the extent, condition, trends, and uses of all Alaskan forests is not available to meet the needs for management and protection of these areas.


Future Research

I plan on exploring how multitemporal remote sensing—collected over a range of scales and resolutions--and field data can be used to investigate complex interactions among climate, land use, disturbance, and condition in the forested ecosystems of Alaska, with particular attention to rates of carbon accumulation and loss within boreal forests

 

Featured Publications

Bullet.Strunk, J., H. Temesgen, H.-E. Andersen, J. Flewelling, and L. Madsen. 2012. Effects of lidar pulse density and sample size on a model-assisted approach to estimate forest inventory variables. Canadian Journal of Remote Sensing. 38(5): 644-654.


Bullet.d’Oliveira, M.V.N., S. Reutebuch, R. McGaughey, and H.-E. Andersen. 2012. Estimating forest biomass and identifying low-intensity logging areas using airborne scanning lidar in Antimary State Forest, Acre State, Western Brazilian Amazon. Remote Sensing of Environment. 124: 479-491.


Bullet.Strunk, J., S. Reutebuch, H.- E. Andersen, P. Gould, and R. McGaughey. 2012. Model-Assisted Forest Yield Estimation with Light Detection and Ranging. Western Journal of Applied Forestry. 27(2): 53-59.


Bullet.Andersen, H.-E., J. Stunk, H. Temesgen, D. Atwood, and K. Winterberger. 2011. Using multi-level remote sensing and ground data to estimate forest biomass resources in remote regions: A case study in the boreal forests of interior Alaska. Canadian Journal of Remote Sensing. 37(6): 596-611.


Bullet.Andersen, H.-E., J. Strunk, and H. Temesgen. 2011. Using airborne light detection and ranging as a sampling tool for estimating forest biomass resources in the upper Tanana Valley of interior Alaska. Western Journal of Applied Forestry. 26(4): 157-164.


Bullet.Sullivan, A.; McGaughey, R.; Andersen, H.-E.; Schiess, P. 2009. Object-oriented classification of forest structure from light detection and ranging data for stand mapping. Western Journal of Applied Forestry. 24(4): 198-204.


Bullet.Kim, S.; McGaughey, R.J.; Andersen, H.-E.; Schreuder, G. 2009. Tree species differentiation using intensity data derived from leaf-on and leaf-off airborne laser scanner data. Remote Sensing of Environment. 113(8): 1575-1586.


Bullet.Andersen, H.-E.; Clarkin, T.; Winterberger, K.; Strunk. J. 2009. An accuracy assessment of geographic coordinates obtained using survey- and recreational-grade GPS receivers across a range of forest conditions within the Tanana Valley of interior Alaska. Western Journal of Applied Forestry. 24(3): 128-136.


Bullet.Andersen, H.-E. 2009. Using airborne LIDAR to characterize forest stand condition on the Kenai Peninsula of Alaska. Western Journal of Applied Forestry. 24(2): 95-102.


Bullet.Pang, Y.; Lefsky, M.; Andersen, H.-E.; Miller, M.; Sherrill, K. 2008. Validation of the ICESat vegetation product using crown-area-weighted mean height derived using crown delineation with discrete return LIDAR data. Canadian Journal of Remote Sensing. 34(Supplement 2): S471-S484.


Bullet.Li, Y.; Andersen, H.-E.; McGaughey. R.J. 2008. A comparison of statistical methods for estimating forest biomass from light detection and ranging data. Western Journal of Applied Forestry. 23(4): 223-231.


Bullet.Breidenbach, J.; Kublin, E.; McGaughey, R.; Andersen, H.-E.; Reutebuch, S. 2008. Mixed-effects models for estimating stand volume by means of small footprint airborne laser scanner data. The Photogrammetric Journal of Finland. 21(1): 4-15.


Bullet.Andersen, H.-E.; McGaughey, R.J.; Reutebuch, S.E. 2008. Assessing the influence of flight parameters, interferometric processing, slope, and canopy density on the accuracy of X-band IFSAR-derived forest canopy height models. International Journal of Remote Sensing. 29(5): 1495-1510.


Bullet.Gatziolis, D.; Andersen, H.-E. 2008. A guide to LIDAR data acquisition and processing for the forests of the Pacific Northwest. Gen. Tech. Rep. PNW-GTR-768. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station.


Bullet.Andersen, H.-E.; Breidenbach, J. 2007. Statistical properties of mean stand biomass estimators in a LIDAR-based double sampling forest survey design. Proceedings of the ISPRS workshop on Laser Scanning. IAPRS. XXXVI (Part 3 / W52): 8–13.


Bullet.Andersen, H.-E.; Reutebuch, S.E.; McGaughey, R.J. 2006. Active remote sensing. In: Shao, G.; Reynolds, K., eds. Computer applications in sustainable forest management. Dordrecht: Springer-Verlag: 43-66. Chapter 3.


Bullet.Andersen, H.-E.; Reutebuch, S.E.; McGaughey, R.J. 2006. A rigorous assessment of tree height measurements obtained using airborne LIDAR and conventional field methods. Canadian Journal of Remote Sensing. 32(5): 355-366.


Bullet.Reutebuch, S.E.; Andersen, H.-E.; McGaughey, R.J. 2005. LIDAR: an emerging tool for multiple resource inventory. Journal of Forestry. 103(6): 286-292.


Bullet.Andersen, H.-E.; Reutebuch, S.E.; McGaughey, R.J. 2005. Accuracy of an IFSAR-derived digital terrain model under a conifer forest canopy. Canadian Journal of Remote Sensing. 31(4): 283-288.


Bullet.Andersen, H.-E.; McGaughey, R.J.; Reutebuch, S.E. 2005. Estimating forest canopy fuel parameters using LIDAR data. Remote Sensing of Environment. 94: 441-449.


Bullet.Reutebuch, S.E., R.J. McGaughey, H.-E. Andersen, and W. Carson. 2003. Accuracy of a high-resolution LIDAR-based terrain model under a conifer forest canopy. Canadian Journal of Remote Sensing 29(5): 1-9.




US Forest Service - Pacific Northwest Research Station
Last Modified: Monday,16December2013 at14:18:42CST


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