Sökning: "Spectral Signature"
Visar resultat 1 - 5 av 14 uppsatser innehållade orden Spectral Signature.
- Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap
Sammanfattning : The European spruce bark beetle is considered as one of the most destructive forest insects to Norway spruce trees in Europe. Climate change may increase the frequency and intensity of bark beetle outbreaks. It is therefore of vital importance to detect the bark beetle outbreaks and take it under control to prevent further damages. LÄS MER
- Master-uppsats, Lunds universitet/Astronomi
Sammanfattning : Context. The planet-metallicity correlation for gaseous giants is widely accepted through spectroscopic studies. However, whether a similar correlation exists for terrestrial planets is a debated subject. LÄS MER
- Master-uppsats, Uppsala universitet/Institutionen för fysik och astronomiUppsala universitet/Institutet för rymdfysik, Uppsalaavdelningen
Sammanfattning : Aurora occurs in various shapes, one of which is the hitherto unreported phenomenon of auroral fragments. For three periods of occurrence of these fragments their properties were studied in detail during this master’s thesis, using mainly ground-based instrumentation located near Longyearbyen on Svalbard, Norway. LÄS MER
4. UAV based hyperspectral grassland monitoring in an alpine shallow erosion area : lessons learnt from classifying vegetation indicating shallow erosion riskMaster-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap
Sammanfattning : UAV based hyperspectral grassland monitoring in an alpine shallow erosion area Recent research in the Alps found that a reduction in grassland management is correlated to an increase in a certain type of shallow erosion areas called blaiken. This change also entails changes to the dominant grassland vegetation. LÄS MER
5. Analysing Raman spectra of crystalline cellulose degradation by fungi using artificial neural networksKandidat-uppsats, Lunds universitet/Beräkningsbiologi och biologisk fysik; Lunds universitet/Institutionen för astronomi och teoretisk fysik
Sammanfattning : This thesis investigates the use of artificial neural networks for classifying Raman spectra of partially degraded cellulose samples by fungal species. A multilayer perceptron configuration of 4 hidden layers and 128 hidden nodes was able to classify a set of 60 samples with an overall prediction accuracy of 0.55. LÄS MER