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Physical Sciences and Mathematics Commons™
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Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
Characterizing Dryland Ecosystems Using Remote Sensing And Dynamic Global Vegetation Modeling, Abdolhamid Dashtiahangar
Characterizing Dryland Ecosystems Using Remote Sensing And Dynamic Global Vegetation Modeling, Abdolhamid Dashtiahangar
Boise State University Theses and Dissertations
Drylands include all terrestrial regions where the production of crops, forage, wood and other ecosystem services are limited by water. These ecosystems cover approximately 40% of the earth terrestrial surface and accommodate more than 2 billion people (Millennium Ecosystem Assessment, 2005). Moreover, the interannual variability of the global carbon budget is strongly regulated by vegetation dynamics in drylands. Understanding the dynamics of such ecosystems is significant for assessing the potential for and impacts of natural or anthropogenic disturbances and mitigation planning, and a necessary step toward enhancing the economic and social well-being of dryland communities in a sustainable manner (Global …
Regional Scale Dryland Vegetation Classification With An Integrated Lidar-Hyperspectral Approach, Hamid Dashti, Andrew Poley, Nancy Glenn, Nayani Ilangakoon, Lucas Spaete, Dar Roberts, Et. Al.
Regional Scale Dryland Vegetation Classification With An Integrated Lidar-Hyperspectral Approach, Hamid Dashti, Andrew Poley, Nancy Glenn, Nayani Ilangakoon, Lucas Spaete, Dar Roberts, Et. Al.
Michigan Tech Publications
The sparse canopy cover and large contribution of bright background soil, along with the heterogeneous vegetation types in close proximity, are common challenges for mapping dryland vegetation with remote sensing. Consequently, the results of a single classification algorithm or one type of sensor to characterize dryland vegetation typically show low accuracy and lack robustness. In our study, we improved classification accuracy in a semi-arid ecosystem based on the use of vegetation optical (hyperspectral) and structural (lidar) information combined with the environmental characteristics of the landscape. To accomplish this goal, we used both spectral angle mapper (SAM) and multiple endmember spectral …
Regional Scale Dryland Vegetation Classification With An Integrated Lidar-Hyperspectral Approach, Hamid Dashti, Nancy F. Glenn, Nayani Ilangakoon, Josh Enterkine, Alejandro N. Flores
Regional Scale Dryland Vegetation Classification With An Integrated Lidar-Hyperspectral Approach, Hamid Dashti, Nancy F. Glenn, Nayani Ilangakoon, Josh Enterkine, Alejandro N. Flores
Geosciences Faculty Publications and Presentations
The sparse canopy cover and large contribution of bright background soil, along with the heterogeneous vegetation types in close proximity, are common challenges for mapping dryland vegetation with remote sensing. Consequently, the results of a single classification algorithm or one type of sensor to characterize dryland vegetation typically show low accuracy and lack robustness. In our study, we improved classification accuracy in a semi-arid ecosystem based on the use of vegetation optical (hyperspectral) and structural (lidar) information combined with the environmental characteristics of the landscape. To accomplish this goal, we used both spectral angle mapper (SAM) and multiple endmember spectral …