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L. Monika Moskal

Professor (Earth sciences; Environmental sciences)

United States

Championing applied spatiotemporal scalable earth observation techniques in environmental applications with attention to uncertainty. Prof. Moskal specializes in Remote Sensing and Earth Observation at the School of Environmental and Forest Sciences (SEFS), within the College of the Environment, at the University of Washington, Seattle and serves as the Director of the Precision Forestry Cooperative (PFC), which also houses her Remote Sensing and Geospatial Analysis Laboratory (RSGAL). She is affiliated with the UW Interdisciplinary PhD Program and the UW Department of Geography. Prof. Moskal earned a PhD in Remote Sensing and GIS from the University of Kansas, Masters in Remote Sensing from the University of Calgary and Bachelors of Environmental Sciences from the University of Waterloo. Prof. Moskal has worked throughout the western U.S. and Canada, and her research has received substantial funding from the NSF, USDA Forest Service, as well as NASA.

Publications

  • https://orcid.org/0000-0003-1563-6506
  • Lidar-based modelling approaches for estimating solar insolation in heavily forested streams
  • Relationships between Satellite-Based Spectral Burned Ratios and Terrestrial Laser Scanning
  • Forest structure predictive of fisher (Pekania pennanti)dens exists in recently burned forest in Yosemite, California, USA
  • Lidar-based approaches for estimating solar insolation in heavily forested streams
  • Characterizing Tree Spatial Distribution Patterns Using Discrete Aerial Lidar Data
  • Characterizing the Spatial Variations of Forest Sunlit and Shaded Components Using Discrete Aerial Lidar
  • Wetland Surface Water Detection from Multipath SAR Images Using Gaussian Process-Based Temporal Interpolation
  • Stratifying Forest Overstory for Improving Effective LAI Estimation Based on Aerial Imagery and Discrete Laser Scanning Data
  • Classifying Forest Type in the National Forest Inventory Context with Airborne Hyperspectral and Lidar Data
  • Estimating Fuel Moisture in Grasslands Using UAV-Mounted Infrared and Visible Light Sensors
  • Assessing the Contribution of Woody Materials to Forest Angular Gap Fraction and Effective Leaf Area Index Using Terrestrial Laser Scanning Data
  • Object-Based Tree Species Classification in Urban Ecosystems Using LiDAR and Hyperspectral Data
  • An Integrated Approach for Monitoring Contemporary and Recruitable Large Woody Debris
  • Urbanization alters the influence of weather and an index of forest productivity on avian community richness and guild abundance in the Seattle Metropolitan Area
  • Retrieving forest canopy extinction coefficient from terrestrial and airborne lidar
  • High-resolution habitat modeling with airborne LiDAR for red tree voles
  • Retrieving Directional Gap Fraction, Extinction Coefficient, and Effective Leaf Area Index by Incorporating Scan Angle Information from Discrete Aerial Lidar Data
  • Mapping the Individual Trees in Urban Orchards by Incorporating Volunteered Geographic Information and Very High Resolution Optical Remotely Sensed Data: A Template Matching-Based Approach
  • Harnessing the Temporal Dimension to Improve Object-Based Image Analysis Classification of Wetlands
  • Population responses of common ravens to reintroduced gray wolves
  • Estimation of forest structure and canopy fuel parameters from small-footprint full-waveform LiDAR data
  • Improved Salient Feature-Based Approach for Automatically Separating Photosynthetic and Nonphotosynthetic Components Within Terrestrial Lidar Point Cloud Data of Forest Canopies
  • Deriving pseudo-vertical waveforms from small-footprint full-waveform LiDAR data
  • LUMINATE: Linking agricultural land use, local water quality and Gulf of Mexico hypoxia
  • Assessing the utility of green LiDAR for characterizing bathymetry of heavily forested narrow streams
  • Reconstructing semi-arid wetland surface water dynamics through spectral mixture analysis of a time series of Landsat satellite images (1984-2011)
  • Terrestrial laser scanning reveals seagrass microhabitat structure on a tideflat
  • Urban food crop production capacity and competition with the urban forest
  • Terrestrial laser scanning for vegetation sampling
  • Determining woody-to-total area ratio using terrestrial laser scanning (TLS)
  • Monitoring Post Disturbance Forest Regeneration with Hierarchical Object-Based Image Analysis
  • Retrieval of Effective Leaf Area Index in Heterogeneous Forests With Terrestrial Laser Scanning
  • Computational-Geometry-Based Retrieval of Effective Leaf Area Index Using Terrestrial Laser Scanning
  • Hyperspectral Analysis of Soil Nitrogen, Carbon, Carbonate, and Organic Matter Using Regression Trees
  • Leaf Orientation Retrieval From Terrestrial Laser Scanning (TLS) Data
  • Retrieving Forest Inventory Variables with Terrestrial Laser Scanning (TLS) in Urban Heterogeneous Forest
  • Spatial variability of terrestrial laser scanning based leaf area index
  • Tree Species Detection Accuracies Using Discrete Point Lidar and Airborne Waveform Lidar
  • Fourier transformation of waveform Lidar for species recognition
  • Uncertainty in urban forest canopy assessment: Lessons from seattle, WA, USA
  • Monitoring Urban Tree Cover Using Object-Based Image Analysis and Public Domain Remotely Sensed Data
  • Object-based classification of semi-arid wetlands
  • Strengths and limitations of assessing forest density and spatial configuration with aerial LiDAR
  • Fusion of LiDAR and imagery for estimating forest canopy fuels
  • Capturing tree crown formation through implicit surface reconstruction using airborne lidar data
  • Modeling approaches to estimate effective leaf area index from aerial discrete-return LIDAR
  • Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors
  • New high-resolution field surveying methods for validation of crown attributes from 3D scanning laser data
  • True orthophoto creation through fusion of lidar derived digital surface model and aerial photos
  • A wrapped-surface reconstruction method of lidar points to identify tree crown attributes
  • Bioremediation of mining refuse at Tar Creek
  • Spatiotemporal modeling of post-disturbance forest regeneration in the Yellowstone National Park region
  • Temporal signatures and harmonic analysis of natural and anthropogenic disturbances of forested landscapes: A case study in the Yellowstone region
  • Relationship between airborne multispectral image texture and aspen defoliation
  • Visualizing the forest: a forest inventory characterization in the Yellowstone National Park based on geostatistical models
  • Visualization of Forest Cover Change: Human Impacts in Northeastern Kansas & Natural Disturbances in Yellowstone National Park
  • Multi-layer Forest Stand Discrimination with Spatial Co-occurrence Texture Analysis of High Spatial Detail Airborne Imagery
  • 3D visualization for the analysis of forest cover change
  • Temporal signatures and harmonic analysis of natural and anthropogenic disturbances of forested landscapes: A case study in the Yellowstone region
  • Multi-layer forest stand discrimination with spatial co-occurrence texture analysis of high spatial detail airborne imagery
  • Incorporating texture into classification of forest species composition from airborne multispectral images
  • AVI multilayer forest classification using airborne image texture
  • Biogeochemical analysis with Landsat TM and a geographic information system
  • Quantification of landscape change from satellite remote sensing
  • Interpretation of forest harvest conditions in New Brunswick using Landsat TM enhanced wetness difference imagery (EWDI)
  • Incorporating texture into classification of forest species composition from airborne multispectral images
  • Interpretation and classification of partially harvested forest stands in the fundy model forest using multitemporal landsat TM digital data
  • Supervised classification of multisource satellite image spectral and texture data for agricultural crop mapping in buenos aires province, argentina
  • An ARC/INFO Macro Language (AML) polygon update program (PUP) integrating forest inventory and remotely-sensed data
  • The Wetland Intrinsic Potential tool: Mapping wetland intrinsic potential through machine learning of multi-scale remote sensing proxies of wetland indicators
  • Tree-Species Classification and Individual-Tree-Biomass Model Construction Based on Hyperspectral and LiDAR Data
  • Quantifying Forest Litter Fuel Moisture Content with Terrestrial Laser Scanning
  • Terrestrial and Airborne Lidar to Quantify Shrub Cover for Canada Lynx (Lynx canadensis) Habitat Using Machine Learning
  • The Wetland Intrinsic Potential tool: mapping wetland intrinsic potential through machine learning of multi-scale remote sensing proxies of wetland indicators
  • Revealing the hidden carbon in forested wetland soils

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Co-workers & collaborators

Bo Zhao

Bo Zhao

Peng Gong

Peng Gong

L. Monika Moskal's public data