Forest structure from terrestrial laser scanning – in support of remote sensing calibration/validation and operational inventory

Forests are an important part of the natural ecosystem, providing resources such as timber and fuel, performing services such as energy exchange and carbon storage, and presenting risks, such as fire damage and invasive species impacts. Improved characterization of forest structural attributes is desirable, as it could improve our understanding and management of these natural resources. However, the traditional, systematic collection of forest information – dubbed “forest inventory” – is time-consuming, expensive, and coarse when compared to novel 3-D measurement technologies. Remote sensing estimates, on the other hand, provide synoptic coverage, but often fail to capture the fine- scale structural variation of the forest environment. Terrestrial laser scanning (TLS) has demonstrated a potential to address these limitations, but its operational use has remained limited due to unsatisfactory performance characteristics vs. budgetary constraints of many end-users. To address this gap, my dissertation advanced affordable mobile laser scanning capabilities for operational forest structure assessment. We developed geometric reconstruction of forest structure from rapid-scan, low-resolution point cloud data, providing for automatic extraction of standard forest inventory metrics. To augment these results over larger areas, we designed a view-invariant feature descriptor to enable marker-free registration of TLS data pairs, without knowledge of the initial sensor pose. Finally, a graph-theory framework was integrated to perform multi-view registration between a network of disconnected scans, which provided improved assessment of forest inventory variables. This work addresses a major limitation related to the inability of TLS to assess forest structure at an operational scale, and may facilitate improved understanding of the phenomenology of airborne sensing systems, by providing fine-scale reference data with which to interpret the active or passive electromagnetic radiation interactions with forest structure. Outputs are being utilized to provide antecedent science data for NASA’s HyspIRI mission and to support the National Ecological Observatory Network’s (NEON) long-term environmental monitoring initiatives

Analysis and network simulations of honeybee interneurons responsive to waggle dance vibration signals

BACKGROUND: Honeybees have long fascinated neuroscientists with their highly evolved social structure and rich behavioral repertoire. They sense air vibrations with their antennae, which is vital for several activities during foraging, like waggle dance communication and flight. GOALS: This thesis presents the investigation of the function of an identified vibration-sensitive interneuron, DL-Int-1. Primary goals were the investigation of (i) adaptations during maturation and (ii) the role of DL-Int-1 in networks encoding distance information of waggle dance vibration signals. RESULTS: Visual inspection indicated that DL-Int-1 morphologies had similar gross structure, but were translated, rotated and scaled relative to each other. To enable detailed spatial comparison, an algorithm for the spatial co-registration of neuron morphologies, Reg-MaxS-N was developed and validated. Experimental data from DL-Int-1 was provided by our Japanese collaborators. Comparison of morphologies from newly emerged adult and forager DL-Int-1 revealed minor changes in gross dendritic features and consistent, region-dependent and spatially localized changes in dendritic density. Comparison of electrophysiological response properties showed an increase in firing rate differences between stimulus and non-stimulus periods during maturation. A putative disinhibitory network in the honeybee primary auditory center was proposed based on experimental evidence. Simulations showed that the network was consistent with experimental observations and clarified the central inhibitory role of DL-Int-1 in shaping the network output. RELEVANCE: Reg-MaxS-N presents a novel approach for the spatial co-registration of morphologies. Adaptations in DL-Int-1 morphology during maturation indicate improved connectivity and signal propagation. The central role of DL-Int-1 in a disinhibitory network in the honeybee primary auditory center combined with adaptions in its response properties during maturation could indicate better encoding of distance information from waggle dance vibration sig- nals

New Hampshire general court, journal of the house of representatives 1983 session, December 1, 1982 through June 30, 1983.

Titles and imprints vary; Some volumes include miscellaneous state documents and reports; Rules of the House of Representative