Precision Forestry Cooperative


List of peer-reviewed publications only produced by the personnel in PFC (PFC lab leads are in bold) if you can’t find or access a publication please email us.


Kennedy, R.E., Ohmann, J., Gregory, M., Yang, Z., Bell, D., Kane, V.R., Hughes, M.J., Cohen, W., Powell, S., Meeti, N., Larrue, T., Hooper, S., Kane, J.T., Miller, D., Perkins, J., Seidl. 2018.  An empirical, integrated forest carbon monitoring system.  Environmental Research Letters 13:025004. 


Johnston, A. and L. M. Moskal. 2017. High-Resolution Habitat Modeling with Airborne LiDAR for Red Tree Voles. Journal of Wildlife Management and Wildlife Monographs 81(1);58-72.

Ma, L., G. Zheng, J. Eitel, T.S. Magney and L.M. Moskal, 2017. Retrieving forest canopy extinction coefficient from terrestrial and airborne lidar. Agricultural and Forest Meteorology 236;1-21.

North, M. P., J. T. Kane, V. R. Kane, G. A. Asner, W. Berigan, D. J. Churchill, S. Conway, R.J. Gutierrez, S. Jeronimo, J. Keane, A. Koltunov, T. Mark, L. M. Moskal, T. Muton, Z. Peery, C. Ramirez, R. Sollman, A. M. White and S. Whitmore. 2017. Cover of tall trees best predicts California spotted owl habitat. Forest Ecology and Management 405;166-178.

Shyrock, B, J. Marzluff and L. M. Moskal. 2017. Urbanization alters the influence of weather and an index of forest productivity on avian community richness and guild abundance in the Seattle metropolitan area. Frontiers Ecology and Evolution 5:40;14p.

Zheng, G, L. Ma, J. Eitel, W. He, TS. Magney, L.M. Moskal and M. Li. 2017. Retrieving Directional Gap Fraction, Extinction Coefficient, and Effective Leaf Area Index by Incorporating Scan Angle Information from Discrete Aerial Lidar Data. IEEE Transactions of Geosciences and Remote Sensing 55(1);577-590.


Halabisky, M., L. M. Moskal, A. Gillespie, M. Hannam. 2016. Reconstructing semi-arid wetland surface water dynamics through spectral mixture analysis of a time series of Landsat satellite images (1984 – 2011). Remote Sensing of Environment 177;171-183.

Kushch, S.A., S.F. Tóth, R. Deal and G.J. Ettl. 2016. Multi-objective optimization to evaluate tradeoffs among forest ecosystem services following fire hazard reduction in the Deschutes National Forest, USA. Ecosystem Services 22(2016);328-347.

Lydersen, J. M.; Collins, B. M.; Brooks, M. L.; Matchett, J.R.; Shive, K. L.; Povak, N. A.; Kane, V. R.; Smith, D. F. 2017. Fuel treatment and fire history within the Rim Fire in California. Fort Collins, CO: Forest Service Research Data Archive.

Ma, L., Zheng, G., Eitel, J., Moskal, L.M., He, W. and H. Huang. 2016. Improved Salient Feature-Based Approach for Automatically Separating Photosynthetic and Nonphotosynthetic Components Within Terrestrial Lidar Point Cloud Data of Forest Canopies. IEEE Transactions on Geoscience and Remote Sensing 54(2);679-696.

Ma, L., Zheng, G., Eitel, J., Magney, T. and L. M. Moskal. 2016. Determining woody-to-total area ratio using terrestrial laser scanning (TLS), Agricultural and Forest Meteorology 228-229;217-228.

McDill, M.E., S.F. Tóth, R. St. John, J. Braze, and S.A. Rebain. 2016. Comparing Model I and Model II Formulations of Spatially-Explicit Harvest Scheduling Models with Adjacency Constraints. Forest Science 62(1): 28-37.

Richardson J. and L. M. Moskal. 2016.  An Integrated Approach for Monitoring Contemporary and Recruitable Large Woody Debris. Remote Sensing 8(9);778.

Richardson J. and L. M. Moskal. 2016.  Urban Food Crop Production Capacity and Competition with the Urban Forest. Urban Forestry and Urban Greening 15;58-64.

Ross, K. & S.F. Tóth. 2016. A Model for Managing Edge Effects in Harvest Scheduling Using Spatial Optimization. Scandinavian J. of Forest Research 37(1);346-354.

Roesch-McNally, G., S.S. Rabotyagov, J. Tyndall, G.J. Ettl, and S.F. Tóth. 2016. Auctioning the Forest: A qualitative approach to exploring stakeholder responses to bidding on forest ecosystem services. Small-Scale Forestry 15(3);321-333.

St. John, R., K. Öhm, and S.F. Tóth, P. Sandström, A. Korosuo, and L.O. Eriksson. 2016. Combining Spatiotemporal Corridor Design for Reindeer Migration with Harvest Scheduling in Northern Sweden. Scandinavian J. of Forest Research 37(1);355-363.

Stavros, E.N., Tane, Z., Kane, V.R., Veraverbeke, S., McGaughey, R.J., Lutz, J.A., Ramirez, C. 2016. Unprecedented remote sensing data from before and after California King and Rim Megafires. Ecology 97;3244.

Zheng, G. Ma, L.X., He, W., Eitel, J.U.H., Moskal, L.M. and Zhang, Z.Y. 2016. Assessing the contribution of woody materials to forest angular gap fraction and effective leaf area index using terrestrial laser scanning (TLS) data. IEEE Transactions on Geoscience and Remote Sensing 54(3);1474-1484.

Zhang, Z., A. Kazakova, L. M. Moskal, D. Styers and N. Vaughn. 2016. Object-Based Tree Species Classification in Urban Ecosystems using LiDAR and Hyperspectral Data. Forests 7(6);122-138.


Hannam, M, and L. M. Moskal. 2015. Terrestrial Laser Scanning Reveals Seagrass Microhabitat Structure on a Tideflat, Remote Sensing 7(3);3037-3055.

Kane, V.R., C.A. Cansler, N.A. Povak, J.T. Kane, R.J. McGaughey, J.A. Lutz, D.J. Churchill, and M.P. North. 2015. Mixed severity fire effects within the Rim fire: Relative importance of local climate, fire weather, topography, and forest structure. Forest Ecology and Management 358;62-79.

Kane, V.R., J.A. Lutz, C.A. Cansler, N.A. Povak, D.J. Churchill, D.F. Smith, J.T. Kane, and M.P. North. 2015. Water balance and topography predict fire and forest structure patterns. Forest Ecology and Management 338;1-13.

St. John, R., and S.F. Tóth. 2015. Spatially-Explicit Forest Harvest Scheduling with Difference Equations. Annals of Operations Research 232(1);235-257.


Hermosilla, T., Coops, N.C., Ruiz, L.A., Moskal, L.M. 2014. Deriving pseudo-vertical waveforms from small-footprint full-waveform LiDAR data. Remote Sensing Letters 5(4);332-341.

Kane, V.R., M.P. North, J.A. Lutz, D.J. Churchill, S.L. Roberts, D.F. Smith, R.J. McGaughey, J.T. Kane, and M.L. Brooks. 2014. Assessing fire effects on forest spatial structure using a fusion of Landsat and airborne LiDAR data in Yosemite National Park Remote Sensing of Environment 151;89-101.

Kling C.L., Y. Panagopoulos, S. S. Robotyagov, A.M. Valcu, P.A. Gassman, T. Campbell, M. J. White, J.A. Arnold, R. Srinivasan, M.J. Jha, J. J. Richardson, L.M. Moskal, R.E. Turner, and N. N. Rabalais. 2014. LUMINATE: linking agricultural land use, local water quality and Gulf of Mexico hypoxia, European Review of Agricultural Economics p1-29.

Könnyű, N., S.F. Tóth, M.E. McDill and B. Rajasekaran. 2014. Temporal Connectivity of Mature Patches in Forest Planning Models. Forest Science 60(6): 1089-1099.

Richardson, J., L.M. Moskal and J. D. Bakker. Terrestrial Laser Scanning for Vegetation Sampling. Sensors. 14, 20304-20319.

Richardson, J. and L. M. Moskal. 2014. Assessing the utility of green LiDAR for characterizing bathymetry of heavily forested narrow streams, Remote Sensing Letters 5(4);352-357.

Styers, D. L. M. Moskal, M. Halabisky and J. Richardson. 2014, Evaluation of the contribution of LiDAR data and post-classification procedures to object-based classification accuracy. Journal of Remote Sensing. Journal of Applied Remote 8;16p.


Burns, E.S., S.F. Tóth, and R.G. Haight. 2013. A Modeling Framework for Life History-Based Conservation Planning. Biological Conservation 158(1);14-25.

Hermosilla, T., Ruiz, L., Kazakova, A. Coops, N. and L. M. Moskal. 2013. Estimation of forest structure and canopy fuel parameters from small-footprint full-waveform LiDAR data. International Journal of Wildland Fire 23;224-233.

Kane, V.R., J.A. Lutz, S.L. Roberts, D.F. Smith, R.J. McGaughey, N.A. Povak, and M.L. Brooks. 2013. Landscape-scale effects of Fire Severity on Mixed-conifer and Red Fir Forest Structure in Yosemite National Park. Forest Ecology and Management 291;442-457.

Könnyű, N. and S.F. Tóth. 2013. A Cutting Plane Algorithm for Area-Based Adjacency Formulations in Harvest Scheduling Models. Eur. Journal of Operational Research 228(1);236-248.

Moskal, L.M. and M. Jakubauskas. 2013. Monitoring post disturbance forest regeneration with hierarchical object-based image analysis, in Forests, Special Issue: LiDAR and Other Remote Sensing Applications in Mapping and Monitoring of Forests Structure and Biomass 4(4);808-829.

Halabisky, M., M. Hannam, A. L. Long, C. Vondrasek and L. M. Moskal. 2013. The Sharper Image: Hyperspatial Remote Sensing in Wetland Science. Wetland Science and Practice June Issue;10p.

Passolt, Gregor, Miranda J. Fix and Sándor F. Tóth. 2013. A Voronoi Tesselation-based Approach to Generate Hypothetical Forest Landscapes. Canadian Journal of Forest Reseach 43(1);78-89.

Rabotyagov, S.S., S.F. Tóth, and G.J. Ettl. 2013. Testing the Design Variables of ECOSEL: A Market Mechanism for Forest Ecosystem Services. Forest Science 59(3);303-321.

Richardson, J. and L. M. Moskal. 2013. Uncertainty in Urban Forest Canopy Assessment: Lessons from Seattle, WA USA, Urban Forestry and Urban Greening 13(1);152-157.

Tóth, S.F., N. Könnyű, G.J. Ettl, L.W. Rogers, and S.S. Rabotyagov. 2013. ECOSEL: Selling Forest Ecosystem Services. Forest Policy & Economics 35(2013);73-82

Tóth, S.F., N. Könnyű, M.E. McDill & S. George. 2013. Lazy Constraints for Area-Based Adjacency Formulations in Harvest Scheduling Models. Forest Science 59(2);157-176


Burns, Eileen S., Sándor F. Tóth, and Robert G. Haight. 2013. A Modeling Framework for Life History-Based Conservation Planning. Biological Conservation 158(1);14-25.

Halabisky, M. and Moskal, L.M. 2012. Using LiDAR and object-based image analysis to map wetlands in Mt. Rainier National Park. 97th ESA Annual Convention 2012; August 2012.

Moskal, L. M. and Zheng, Guang. 2012. Retrieving Forest Inventory Variables with Terrestrial Laser Scanning (TLS) in Urban Heterogeneous Forest. Remote Sensing 4(1);1-20.

Moskal, L.M. and J. J. Richardson . 2012. Delineating and Classifying Forest Stands Based on Three-Dimensional Structure and Pattern, ForestSat2012, Corvallis, OR, September 2012

Rabotyagov, Sergey S., Sándor F. Tóth, and Gregory J. Ettl. 2012. Testing the Design Variables of ECOSEL: A Market Mechanism for Forest Ecosystem Services. Forest Science 59(3);303-321.

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.

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.

Tóth, S. F., N..Könnyű, M.  E. McDill, and Sonney G. 2012. Lazy Constraints for Area-Based Adjacency Formulations in Harvest Scheduling Models. Forest Science.

Tóth, S. F., R. G. Haight, and L.W. Rogers. 2011. Dynamic Reserve Selection: Optimal Land Retention with Land Price Feedbacks. Operations Research 59(5);1059-1078.

Tóth, S. F., M. E. McDill, N. Könnyű, and S. George. 2012. A Strengthening Procedure for the Path Formulation of the Area-based Adjacency Problem in Harvest Scheduling Models. Mathematical and Computational Forestry & Natural-Resource Sciences 4(1);16-38.

Vaughn, N., L. M. Moskal and E.C. Turnblom, 2012. Tree Species Detection Accuracy with Airborne Waveform LiDAR, **Special Issue on Laser Scanning in Forests, Remote Sensing 4(2);377-403.

Zheng, G., Moskal, L. M. and S-H. Kim. 2012. Retrieval of effective leaf area index in heterogeneous forests with terrestrial laser scanning, IEEE Transactions on Geoscience and Remote Sensing 50(10);3958-3969.

Zheng, G. and L. M. Moskal. 2012. Computational-Geometry-Based Retrieval of Effective Leaf Area Index Using Terrestrial Laser Scanning, IEEE Transactions on Geoscience and Remote Sensing 50(10);12p.

Zheng, G. and L. M. Moskal. 2012. Leaf Orientation Retrieval from Terrestrial Laser Scanning Data, IEEE Transactions on Geoscience and Remote Sensing 50(10);10p.

Zheng, G. and L. M. Moskal. 2012. Spatial variability of terrestrial laser scanning based leaf area index, International Journal of Applied Earth Observation and Geoinformation 19;226–237.


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.

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.

Halabisky, M., L. M. Moskal and S. A. Hall. 2011. Object-Based Classification of Semi-Arid Wetlands, Journal of Applied Remote Sensing 5(05351);13p.

Kane, V.R., R. Gersonde, J.A. Lutz, R.J. McGaughey, J.D. Bakker, and J.F. Franklin. 2011. Patch dynamics and development of structural and spatial heterogeneity in Pacific Northwest forests. Canadian Journal of Forest Research 41;2276-2291.

Kim, S,, T. Hinckley; D. Briggs. 2011. Classifying individual tree genera using stepwise cluster analysis based on height and intensity metrics derived from airborne laser scanner data. Remote Sensing of Environment 115(12);3329-3342.

Moskal, L.M. and D. M. Styers. 2011. Monitoring Urban Forest Canopies Using Object-Based Image Analysis and Public Domain Remotely Sensed Data. Remote Sensing Special Issue on Urban Remote Sensing 3(10);2243-2262.

Moskal, L. M. and Zheng, G. 2012. Retrieving Forest Inventory Variables with Terrestrial Laser Scanning (TLS) in Urban Heterogeneous Forest.Remote Sensing 4(1);1-20.

Richardson, J. J. and Moskal, L. M. 2011. Strengths and limitations of assessing forest density and spatial configuration with aerial LiDAR, Remote Sensing of Environment 115(10);2640-2651.

Vaughn N., L. M. Moskal and E. Turnblom. 2011. Fourier transformation of waveform LiDAR for species recognition. Remote Sensing Letters 2(4);347-356.


Erdody T. and L. M. Moskal. 2010. Fusion of LiDAR and Imagery for Estimating Forest Canopy Fuels, Remote Sensing of Environment 114(4);725-737.

Kane, V.R., J.D. Bakker, R.J. McGaughey, J.A. Lutz, R. Gersonde, and J.F. Franklin. 2010. Examining conifer canopy structural complexity across forest ages and elevations with LiDAR data. Canadian Journal of Forest Research 40;774-787.

Kane, V.R., R.J. McGaughey, J.D. Bakker, R. Gersonde, J.A. Lutz, and J.F. Franklin. 2010. Comparisons between field- and LiDAR-based measures of stand structural complexity. Canadian Journal of Forest Research 40;761-773.

Kato, A., T. Kobayashi, L.M. Moskal, P. Schiess and D. Calhoun. 2010. Certification of carbon credit using airborne LiDAR. In CD Proceedings of SilviLaser 2010, Freiburg, Germany; 14p.

Kato, A., Moskal, L.M., Schiess, P., Swanson, M.E., Calhoun D. 2010. True Orthophoto Creation Through Fusion of LiDAR Derived Digital Surface Model and Aerial Photos. Digital Proceedings of ISPRS Commission VII Symposium 2010 Vienna, Austria; 14p.

Tóth, Sándor F., Sergey S. Rabotyagov and Gregory J. Ettl. 2010 . ECOSEL: An Auction Mechanism for Forest Ecosystem Services. Mathematical and Computational Forestry & Natural Resource Sciences 2(2);99-116.

Tóth, S.F., J. Turner, S.A. Kushch, R. Yao, S.S. Rabotyagov, B. Dhakal, and L.W. Rogers 2010. ECOSEL: Application of Environmental Auctions to a New Zealand Planted Forest. New Zealand Forest Research Institute (Scion) General Technical Report no. 47085. October 2010.

Vaughn, N. and L. M. Moskal. 2010 Fourier transform of waveform LiDAR for species recognition – data requirements. In CD Proceedings of SilviLaser 2010.  Freiburg, Germany; 22p.


Kato, A. Moskal L.M., Schiess, P. Swanson, M., Calhoun, D. and W. Stuetzle. 2009.  Capturing Tree Crown Formation through Implicit Surface Reconstruction using Airborne LiDAR Data, Remote Sensing of Environment 113(6);1148-1162.

Moskal, L. M., T. Erdody, A. Kato, J. Richardson, G. Zheng and D. Briggs. 2009. Aerial and Terrestrial LiDAR Applications in Precision Forestry. In CD Proceedings of The First International Conference on LiDAR Technology and Remote Sensing Applications, Harbin, China; 5p.

Richardson, J., Moskal, L. M. and S. Kim. 2009. Modeling Approaches to Estimate Effective Leaf Area Index from Aerial Discrete-Return LIDAR, Agricultural and Forest Meteorology 149;1152-1160.

Sullivan, Alicia A., R.J. McGaughey, H.E. Andersen, P. Schiess. 2009. Object-Oriented Classification of Forest Structure from Light Detection and Ranging Data for Stand Mapping. Western Journal of Applied Forestry 24(4)4;198-204.

Tóth, S.F., R.G. Haight, S.A. Snyder, S. George, J.R. Miller, M.S. Gregory and A.M. Skibbe. 2009. Reserve Selection with Minimum Contiguous Area Restrictions: An Application to Open Space Protection Planning in Suburban Chicago. Biological Conservation . Biological Conservation, doi:10.1016/j.biocon.2009.02.037.

Tóth, S.F. and M.E. McDill. 2009. Finding Efficient Harvest Schedules under Three Conflicting Objectives. Forest Science 55(2);117-131.

Tóth, S.F., G.J. Ettl and S.S. Rabotyagov. 2008. ECOSEL: An Auction Mechanism for Forest Ecosystem Services. The Center for International Trade in Forest Products Newsletter. Fall 2008.

Zheng, G. and L. M. Moskal. 2009. Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors. Sensors 9(4);2719-2745.


Andersen, H.-E.; R.J. McGaughey, and S.E. Reutebuch. 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 J. of Remote Sensing 29(5);1495-1510.

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

Cherry, M.L., V. Vikram, D.G. Briggs, D.W. Cress, and G.T. Howe. 2008. Genetic variation in direct and indirect measures of wood stiffness in coastal Douglas-fir Can. J. For. Res. 38(9);2476-2486.

Kane, V.R., A.R. Gillespie, R.J. McGaughey, J.A. Lutz, K. Ceder, and J.F. Franklin. 2008. Interpretation and topographic compensation of conifer canopy self-shadowing. Remote Sensing of Environment 112(10);3820-3832.

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

Lutz, J.A., J.A. Freund, R.K. Hagmann, V.R. Kane, A.J. Larson, and J.F. Franklin. 2008. Mid-career graduate students in ecology. Frontiers in Ecology and Environment 6(7);394-395.

Tóth, Sándor F. and M.E. McDill. 2008. Promoting Large, Compact Mature Forest Patches in Harvest Scheduling Models. Environmental Modeling and Assessment 13(1-15).


Breidenbach, J., R.J. McGaughey, H.E. Andersen, G. Kändler, and S.E.Reutebuch. 2007. A mixed effects model to estimate stand volume by means of small footprint airborne lidar data for an American and German study site. International Archives of Photogrammetry and Remote Sensing 36(3) W52;77-83.

Kato, A., Moskal, L.M. Swanson, M.E., Schiess, P. and D. Calhoun. 2007.  A wrapped-surface reconstruction method of LiDAR points to identify tree crown attributes, In CD Proceedings of American Society for Photogrammetry and Remote Sensing – 28th Canadian Symposium on Remote Sensing and ASPRS Fall Specialty Conference 2007, Ottawa, ON, Canada, pp 134-142.


Gillespie, A.R., L. Gilson, M.A. Gillespie, and V.R. Kane. 2006. A framework for estimating unresolved spectral shade. In: J.A. Sobrino (Ed.), Second recent advances in quantitative remote sensing (pp. 385-390). Spain: Publicacions de la Universitat de Valencia.


Moskal, L.M. 2005. Temporal signatures and harmonic analysis of natural and anthropogenic disturbances of forested landscapes: a case study in the Yellowstone region, 2005. In Proceedings of IEEE  MultiTemp 2005, 3rd International Workshop on the Analysis of Multi-temporal Remote Sensing Images, Biloxi, MS; pp15-19.


Dunbar, M. D., L. M. Moskal, and M. E. Jakubauskas. 2004.  3D Visualization for the analysis of forest cover change, Geocarto International, Special Issue on 100th Anniversary of the Association of American Geographers – Remote Sensing Specialty Group, 19(2);103-112.

Moskal, L.M. and S.E. Franklin, 2004. Relationship between airborne multispectral image texture and aspen defoliation, International Journal of Remote Sensing 2(14);2710-2711.

Moskal, L.M., M.D. Dunbar, M.E. Jakubauskas. 2004. Visualizing the forest: a forest inventory characterization in the Yellowstone National Park based on geostatistical models, in A Message From the Tatras: Geographical Information Systems and Remote Sensing in Mountain Environmental Research, Widacki, W., Bytnerowicz, A. and Riebau, A. (eds). Institute of Geography and Spatial Management of the Jagiellonian University in Krakow and the USDA Forest Service: 219-232.


Moskal, L.M. and S.E. Franklin. 2002.  Multistory forest stand discrimination with multiscale texture from high spatial detail airborne imagery, Geocarto International 17(4);53-66.

Tóth, S.F. 2002. Japán erdeiről és erdőgazdálkodásáról, 5. rész: Erdészeti Lapok 137(5):139-140. [in Hungarian]


Franklin, S.E., M.B. Lavigne, L.M. Moskal, M.A. Wulder and T.M. McCaffrey. 2001. Interpretation of partial harvest forest stand conditions using the Enhanced Wetness Difference Image (EWDI), Canadian Journal of Remote Sensing 27(2);118-128.

Moskal, L.M., K.P. Price, M. E. Jakubauskas and E.A. Martinko. 2001.  Comparison of hyperspectral AVIRIS and Landsat TM imagery for estimating burn site pine seedling regeneration densities in the Central Plateau of Yellowstone National Park. In Proceedings of the 3rd International Forestry and Agriculture Remote Sensing Conference and Exhibition, Denver, CO, November 2001, paper number E-8; 8p.

Moskal, L.M. and M. E. Jakubauskas. 2001.  Discriminating forest stand age classes using 2nd order image texture in the Central Plateau of Yellowstone National Park. In Proceedings of the 3rd International Forestry and Agriculture Remote Sensing Conference and Exhibition, Denver, CO, November 2001, paper number 4-3; 9p.

Moskal, L.M., M.E. Houts, M.E. Jakubauskas, K. Price and E. Martinko. 2001. Multispectral high resolution digital photography for forest characterization in the Central Plateau of the Yellowstone National Park. In Proceedings of The 3rd International Forestry and Agriculture Remote Sensing Conference and Exhibition, Denver, CO, November 2001, paper E-22; 10p

Presutti, M., S.E. Franklin, L.M. Moskal and E.E. Dickson. 2001. Supervised classification of multisource satellite image spectral and texture data for agricultural crop mapping in Buenos Aires Province, Argentina, Canadian Journal of Remote Sensing 27(6);679-684.

Tóth, S.F., T. Ueki and Y. Uozumi 2001. The Current Situation of Hungarian Forest Management, with Special Emphasis on the Recent Changes in Forest Ownership, Japanese Journal of Forest Planning 7:21-28.

Tóth, S.F., T. Ueki and Y. Uozumi 2001. The Ecological and Historical Background of Forest Management in Hungary, Japanese Journal of Forest Planning 7:11-19.


Franklin, S.E., E.E. Dickson, D.M. Farr, M.J. Hansen and L.M. Moskal. 2000. Quantification of landscape change from satellite remote sensing, Forestry Chronicle 76(6);877-886.

Franklin, S.E., R.J. Hall, L.M. Moskal, A.J. Maudie and M.B. Lavigne. 2000. Incorporating texture into classification of forest species composition from airborne multispectral images, International Journal of Remote Sensing 21(1);61-79.

Franklin, S.E., L.M. Moskal, M.B. Lavigne and K. Pugh.  2000. Interpretation and classification of partially harvested forest stands using multitemporal Landsat TM digital data, Canadian Journal of Remote Sensing 26(3);318-333.

Franklin, S.E., McCaffrey, T.M., Lavigne, M.B., Wulder, M.A., and M. Moskal. 2000. An ARC/INFO Macro Language (AML) polygon update program (PUP) integrating forest inventory and remotely-sensed data. Canadian Journal of Remote Sensing 26(6);566-575.