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Filtering by: Subject Forest biomass -- Blue Mountains (Or. and Wash.) -- Remote sensing Remove constraint Subject: Forest biomass -- Blue Mountains (Or. and Wash.) -- Remote sensing Decade 2010-2019 Remove constraint Decade: 2010-2019

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  • Remote sensing of forest biomass dynamics using Landsat-derived disturbance and recovery history and lidar data

    Creator:
    Pflugmacher, Dirk
    Abstract:
    Improved monitoring of forest biomass is needed to quantify natural and anthropogenic effects on the terrestrial carbon cycle. Landsat's temporal and spatial coverage, fine spatial grain, and long history of earth observations provide a unique opportunity for measuring biophysical properties of vegetation across large areas and long time scales. However,...
    Resource Type:
    Dissertation
    Full Text:
    : Remote Sensing of Forest Biomass Dynamics Using Landsat-derived Disturbance and Recovery History and

  • Distribution and behavior of cattle grazing riparian pastures

    Creator:
    Wilson, Marie A. (Marie Annette)
    Abstract:
    One second GPS collars were deployed on cattle in three different pastures at three separate times during the year. In each riparian pasture the vegetative communities and stream bank edge were digitally mapped using low elevation aerial photographs and checked in the field for accuracy. A 5 m buffer zone...
    Resource Type:
    Masters Thesis
    Full Text:
    using precise ground measurements and remote sensing technology on the same stretch of Catherine

  • Multi-temporal LiDAR Analysis of Landscape Fire Effects in Southwestern Oregon

    Creator:
    Hoe, Michael
    Abstract:
    Quantitative assessments of post-fire effects are key to improving our understanding of ecosystem resilience. While remote sensing technology has allowed us to assess post-fire landscape effects, we are often limited by the lack of information related to pre-fire forest attributes. As a result, our ability to interpret fire effects in...
    Resource Type:
    Masters Thesis
    Full Text:
    forest canopy fuels. Remote Sensing of Environment 114 (4), 725–737. 12 Escuin, S., R. Navarro, and