Follow lmmoskal on Twitter Dr. L. Monika Moskal
Associate Professor of Remote Sensing
 
   
 
Understanding high spatiotemporal resolution multidimensional ecosystem process, function, monitoring and applications through geospatial techniques
 
 

UW

RSGAL FACTSHEETS
Factsheet6 Halabisky, M., and L.M. Moskal., 2012. Using LiDAR and object based image analysis to map wetlands in Mt. Rainier National Park . Factsheet # 23.
Factsheet6 Kirsch JL, Moskal LM, Fischer DG. 2012. Relationships between fine root productivity and variation of canopy height in a temperate forest. Factsheet #22.
Factsheet6 Kazakova A.N., L.M. Moskal, 2012. Quantifying vertical and horizontal stand structure using Terrestrial LiDAR. Factsheet # 21.
Factsheet6 Moskal, L. M.  and  J. Kirsch, 2012. Calibrating Estimates of Above- and Below- Ground Forests Biomass Using Remotely Sensed Metrics. Factsheet # 20.
Factsheet6 Kazakova, A.N., L.M. Moskal, and D.M. Styers. 2011. Hyperspectral Remote Sensing of Urban Tress. Factsheet # 19.
Factsheet6 Moskal, L. M., D. M. Styers, J. Richardson and M. Halabisky, 2011. Seattle Hyperspatial LULC from LiDAR & NIR Imagery Using OBIA. Factsheet # 18.
Factsheet6 Kazakova A. N., L.M. Moskal, D. M. Styers and D.G. Fischer, 2011. Estimating Tree Species Diversity Using Aerial LiDAR and Multispectral Imagery. Factsheet # 17.
Factsheet6 Kirsch, J.L., L.M. Moskal,  D. M. Styers and D.G. Fischer , 2011. Relationships Between Above- and Belowground Plant Carbon Using Field Metrics and LiDAR. Factsheet #16.
Factsheet6 Hannam, M. and L.M. Moskal, 2011. Coastal Wetlands: Monitoring Estuarine Topographic Change with Terrestrial Laser Scanning. Factsheet # 15.
Factsheet6 Vaughn, N. and L.M. Moskal, 2011. Identification of Individual Tree Species Using  Full Waveform LiDAR. Factsheet 14.
Factsheet6 Stephens, D.R. and L.M. Moskal, 2010. Forestry: Deriving Site Growth Indices From Multi-Temporal Small-Footprint Aerial LiDAR Data. Factsheet # 13.
Factsheet6 Moskal., L. M. and D. M. Styers , 2010. Land use/land cover (LULC) from high-resolution near infrared aerial imagery: costs and applications. Factsheet # 12.
Factsheet6 Park, J., F. Krogstad, J. Fridley and L. M. Moskal, 2009. Small Stream Mapping Method: Local Difference Algorithm (LDA) Using LiDAR and LandSAT. Factsheet # 11.
Factsheet6 Halabisky, M. , T. Wheeler and L.M. Moskal., 2009.  Mobile GIS Data Capture. Factsheet #10.
Factsheet6 Vondrasek, C. and L.M. Moskal., 2009. Decadal Analysis of Change in Wetlands in Arid Regions. Factsheet # 9.
Factsheet6 Hannam, M., L.M. Moskal and S. Wyllie-Echeverria, 2009. Predicting an Invasive Species’ Distribution with LiDAR-derived Topography. Factsheet # 8.
Factsheet6 Halabisky, M.A. , and L.M. Moskal, 2009. Monitoring the Spatiotemporal Heterogeneity of Arid Wetlands Factsheet # 7.
Factsheet6 James, L., L. M. Moskal, 2008. Spatiotemporal Analysis of Mountain Goat Habitat. Factsheet # 6.
Factsheet5 Richardson, J. J, L.M. Moskal, S. Kim, 2008. Estimating Urban Forest Leaf Area Index (LAI) from aerial LiDAR. Factsheet # 5.
Factsheet4 Erdody, T.L., and L. M. Moskal, 2008. LiDAR derived canopy fuel metrics for wildfire modeling. Factsheet # 4.
Factsheet3 Kato, A., L. M. Moskal., P. Schiess, M. Swanson, D. Calhoun and W. Stuetzel, 2008. LiDAR based  tree crown surface reconstruction. Factsheet # 3.
Factsheet2 Zheng G. and L. M. Moskal, 2008. Leaf Area Index (LAI) from Terrestrial LiDAR. Factsheet # 2.
Factsheet1 Moskal, L. M. and G. Zheng, 2008. Forest inventory and stem characterization from terrestrial LiDAR. Factsheet # 1.

 

  • PUBLICATIONS
  • THESES
  • CONFERENCE PAPAERS
  • CONFERENCE PRESENTATIONS
  • CONFERENCE POSTERS
  • OTHER

PEER-REVIEWED JOURNAL PUBLICATIONS

  1. pdfRichardson, J. J. Bakker, L.M. Moskal, 2014. Terrestrial Laser Scanning for Vegetation Sampling, Sensors, 5:4, 352-357.
  2. pdfStyers, D. L. M. Moskal, M. Halabisky andJ. 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, Volume 8, 16p.
  3. pdfRichardson, J. and L. M. Moskal, 2014. Efficacy of Green LiDAR for Depth Measurements in Heavily Forested Streams, Remote Sensing Letters, 5(4), 352-357.
  4. pdfHermosilla, 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.
  5. pdfKling 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.pp1-29
  6. pdf 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.
  7. pdfMoskal, 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
  8. pdf 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.
  9. pdf 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 2013 Issue, 10p.
  10. pdf Zheng, G., L. M. Moskal and S-H. Kim, 2013. Retrieval of effective leaf area index in heterogeneous forests with terrestrial laser scanning , IEEE Transactions on Geoscience and Remote Sensing, 51(2): 777-786.
  11. pdf Gmur, S., D. Vogt, D. Zabowski, and L. M. Moskal, 2012. Hyperspectral Characterization of Soil Series, Nitrogen and Carbon, Sensor, 12(8):10639-10658.
  12. pdf Zheng, G. and L. M. Moskal, 2012. Computational Geometry-Based Retrieval of Effective Leaf Area Index Using Terrestrial Laser Scanning, IEEE Transactions on Geosciences and Remote Sensing, 50(10) 3958-3969.
  13. pdf 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.
  14. pdf Zheng, G. and L.M. Moskal, 2012. Leaf Orientation Retrieval from Terrestrial Laser Scanning Data, IEEE Transactions on Geoscience and Remote Sensing, 50(10), 3970-3979.
  15. pdf Vaughn, N. and L. M. Moskal, 2012. Tree Species Detection Accuracy with Airborne Waveform Lidar, Special Issue on Laser Scanning in Forests, Remote Sensing, 4(2), 377-403.
  16. pdf Moskal, L. M. and G. Zheng, 2012. Retrieving Forest Inventory Variables with Terrestrial Laser Scanning (TLS) in Urban Heterogeneous Forest. Remote Sensing, 4(1), 1-20.
  17. pdf Moskal, L.M., D. M. Styers and M. Halabisky, 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.
  18. pdf Richardson J. and L. M. Moskal, 2011. Strengths and Limitations of Assessing Forest Density and Spatial Configuration with Aerial LiDAR, Remote Sensing of Environment, 114(4), 725-737.
  19. pdf Halabisky, M.,L. M. Moskal and S. A. Hall, 2011. Object-Based Classification of Semi-Arid Wetlands, Journal of Applied Remote Sensing, 5(05351); p.13.
  20. pdf Vaughn N., L. M. Moskal and E. Turnblom, 2011. Fourier transformation of waveform LiDAR for species recognition, Remote Sensing Letters, 2(4); 347-356.
  21. pdf 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.
  22. pdf 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.
  23. pdf Zheng G. and L.M. Moskal, 2009. Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors. Sensors, 9(4):2719-2745.
  24. pdf 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.
  25. pdf Moskal, L.M. & S.E. Franklin, 2004. Relationship between airborne multispectral image texture and aspen defoliation, International Journal of Remote Sensing, 25:14; 2710-2711.
  26. pdf Dunbar, M. D., L. M. Moskal, & 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.
  27. pdf Moskal, L.M. & S.E. Franklin, 2002. Multistory forest stand discrimination with multiscale texture from high spatial detail airborne imagery, Geocarto International, 17(4); 53-66.
  28. pdf Franklin, S.E., L.M. Moskal, M.B. Lavigne, M.A. Wulder & 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.
  29. pdf Presutti, M., S.E. Franklin, L.M. Moskal & E.E. Dickson, 2001. Supervised classification of Landsat TM, RadarSAT W2 Data, & texture derivatives for agricultural crop mapping in Buenos Aires Province, Argentina, Canadian Journal of Remote Sensing, 27(6): 679-685.
  30. pdf 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.
  31. pdf 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
  32. pdf 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.
  33. pdf Franklin, S.E., McCaffrey, T.M., Lavigne, M.B., Wulder, M.A., and L. 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.

PEER-REVIWED BOOK CHAPTERS

  1. pdfMoskal, 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 & Remote Sensing in Mountain Environmental Research, Widacki,. W., Bytnerowicz, A. & Riebau, A. (eds). Institute of Geography & Spatial Management of the Jagiellonian University in Krakow & the USDA Forest Service: 219-232.

TRADE MAGAZINES

  1. pdf Dunbar, M., L.M. Moskal & M.E. Jakubauskas, 2003. 3D Visualization of Forest Cover Change: Human Impacts in Northeastern Kansas & Natural Disturbances in Yellowstone National Park. Earth Observation Magazines, 12 (7); 6-12.
 
 
Dr. Moskal's Office: Bloedel Hall 334
Phone: 206.221.6391
Seattle WA, 98195-2100
Email: lmmoskal@uw.edu