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Remote Sensing & Geospatial Analysis Laboratory

Research & Engagement

RSGAL’s research goal is to understand multiscale and multidimensional dynamics of landscape change through the application of remote sensing, GIS and geospatial tools. The lab develops tools necessary to analyze hyper-resolution remotely sensed data by exploiting spatial, temporal and spectral capabilities of the data. RSGAL work focuses on the application of high spatial resolution remote sensing (LiDAR, imagery) to investigate vegetation structure, specifically the utilization of leaf area index in heterogeneous canopies. Other RSGAL research themes involve multi resolution and multi sensor data fusion, spatiotemporal object-based image analysis and geovisualization techniques to communicate research results. Moskal’s and RSGAL research has been applied to the following themes: ecosystem services and function, bioenergy/biomass, forest inventories, forest health, change analysis, biodiversity, habitat mapping, spatiotemporal wetland assessment, geostatistical analysis of prairie vegetation communities, urban growth and forest fragmentation. Below are some examples of our research in less traditional, non-academic format; this is not an all encompassing list.

Featured NASA & NSF Projects

  • Teal Carbon – Stakeholder-driven Monitoring of Forested Wetland Carbon, NASA # CMS 2018 Moskal
  • A bottom-up, stakeholder-driven CMS for regional biomass carbon dynamics: Phase II, NASA # CMS 2018 Hudak
  • Center for Advanced Forestry Systems (CAFS)III located at The University of Washington, NSF # 8832606, two prior phases were also funded under 3851013 & 3098329
  • CNH: Northern Gulf of Mexico Hypoxia & Land Use in the Watershed: Feedback & Scale Interactions, NSF # 1010009

Current other funding sources include: USDA Forest Service, USGS, BLM, WA DNR &DoE, NPS, US F&W, & others

Wetland Research

Forest Remote Sensing Research

Urban Forests Research

Past Research at MSU

List of all Research Projects

  • A list of all projects can be found here


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