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Full-Text Articles in Life Sciences
The Core Of It All: From The Forest To The Concrete Jungle, Ayo Andra J. Deas
The Core Of It All: From The Forest To The Concrete Jungle, Ayo Andra J. Deas
Dissertations, Theses, and Capstone Projects
The Core of It All is a component of principle within Fasaha. The mission of Fasaha is to implement programming directed toward development of one’s Core through self-actualization. Self-Actualization is defined as bringing forth the total essential qualities of one’s own consciousness, character, and identity through positive behavior. Throughout this manuscript, principle is defined as the standard of natural essential qualities determining intrinsic consciousness, character and identity. Programming is defined as providing with intrinsic instructions for the automatic performance of a task.
Fasaha is a support service that enhances the existing organization’s service. Throughout this dissertation, it will be apparent …
Quantifying Aboveground Biomass In A Tropical Forest Using A Lidar Waveform Weighted Allometric Model, Alejandro Rojas
Quantifying Aboveground Biomass In A Tropical Forest Using A Lidar Waveform Weighted Allometric Model, Alejandro Rojas
Theses and Dissertations
Our knowledge of the distribution and amount of terrestrial above ground biomass (AGB) has increased using lidar technology. Recent advancements in satellite lidar has enabled global mapping of forest biomass and structure. However, there are large biases in satellite lidar estimates which impacts our understanding of carbon dynamics, particularly in tropical forests.
Ni-Meister et al. (2022) developed a lidar full waveform weighted height-based allometric model which produced very good results in temperate deciduous/conifer forest in the continental US. The purpose of this study was to evaluate this biomass model in an African tropical forest using the Land Vegetation and Ice …
Exploring Data Mining Techniques For Tree Species Classification Using Co-Registered Lidar And Hyperspectral Data, Julia K. Marrs
Exploring Data Mining Techniques For Tree Species Classification Using Co-Registered Lidar And Hyperspectral Data, Julia K. Marrs
Theses and Dissertations
NASA Goddard’s LiDAR, Hyperspectral, and Thermal imager provides co-registered remote sensing data on experimental forests. Data mining methods were used to achieve a final tree species classification accuracy of 68% using a combined LiDAR and hyperspectral dataset, and show promise for addressing deforestation and carbon sequestration on a species-specific level.