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Forest biomass estimation with hemispherical photography for multiple forest types and various atmospheric conditions

Posted on:2011-02-04Degree:Ph.DType:Dissertation
University:Oregon State UniversityCandidate:Clark, Joshua AndrewFull Text:PDF
GTID:1443390002960121Subject:Agriculture
Abstract/Summary:
The importance of accurately identifying inventories of domestic energy, including forest biomass, has increasingly become a priority of the US government and its citizens as the cost of fossil fuels has risen. It is useful to identify which of these resources can be processed and transported at the lowest cost for both private and public landowners. Accurate spatial inventories of forest biomass can help landowners allocate resources to maximize forest biomass utilization and provide information regarding current forest health (e.g., forest fire potential, insect susceptibility, wildlife habitat range). This research has indicated that hemispherical photography (HP) may be an accurate and low cost sensing technique for forest biomass measurements.;In this dissertation: (1) It is shown that HP gap fraction measurements and both above ground biomass and crown biomass have a linear relationship. (2) It is demonstrated that careful manipulation of images improves gap fraction estimates, even under unfavorable atmospheric conditions. (3) It is shown that estimates of Leaf Area Index (LAI), based on transformations of gap fraction measurements, are the best estimator for both above ground forest biomass and crown biomass. (4) It is shown that many factors negatively influence the utility of HP for biomass estimation. (5) It is shown that biomass of forests stands with regular spacing is not modeled well using HP.;As researchers continue to explore different methods for forest biomass estimation, HP is likely to remain as a viable technique, especially if LAI can be accurately estimated. However, other methods should be compared with HP, particularly for stands where LAI is poorly estimated by HP.
Keywords/Search Tags:Forest biomass, LAI
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