Biomass forest modelling using UAV LiDAR data under fire effect

Mestrado em Engenharia Florestal e dos Recursos Naturais / Instituto Superior de Agronomia. Universidade de LisboaThe main goal of the study is to analyse the possibility of quantifying the loss of biomass in burned forest stands using Light Detection and Ranging (LiDAR) data. Since wildfires are not uncommon in Mediterranean areas, it is useful to quantify the magnitude of fire damage in forests. With the use of remote sensing, it is possible to plan post-fire recovery management and to quantify the losses of biomass and carbon stock. Mata Nacional de Leiria (MNL) was chosen, because, after the fire in October 2017, it showed areas with low and medium-high fire severity. MNL is divided in several rectangular management units (MU). To achieve our objective, it was necessary to find a MU with burned and unburned areas. In this selection process, we used Sentinel-2 images. The fire severity was estimated by deriving a spectral index related with the effects of fire and to compute the temporal difference (pre- minus post-fire) of this index, the delta normalized burn ratio (DNBR). Forest inventory was carried out in four plots installed in the selected MU. Allometric equations were used to estimate values of stand aboveground biomass. These values were used to fit a relationship with data extracted from LiDAR cloud metrics. The LiDAR data were acquired with a VLP-16 Velodyne LiDAR PUCK™ mounted on an Unmanned Aerial Vehicles (UAV) at an altitude of 60 m above the ground. The point clouds were then processed with the FUSION software until a cloud metrics was generated and then regression models were used to fit equations related to LiDAR-derived parameters. Two biomass equations were fit, one with the whole tree metrics having a R² = 0,95 and a second one only considering the tree crown metrics presenting a R² = 0,93. The state of the forest (unburned/burned) was significant on the final equationN/

Diagnostic indices for vertiginous diseases

<p>Abstract</p> <p>Background</p> <p>Vertigo and dizziness are symptoms which are reported frequently in clinical practice. We aimed to develop diagnostic indices for four prevalent vertiginous diseases: benign paroxysmal positional vertigo (BPPV), Menière's disease (MD), vestibular migraine (VM), and phobic postural vertigo (PPV).</p> <p>Methods</p> <p>Based on a detailed questionnaire handed out to consecutive patients presenting for the first time in our dizziness clinic we preselected a set of seven questions with desirable diagnostic properties when compared with the final diagnosis after medical workup. Using exact logistic regression analysis diagnostic scores, each comprising of four to six items that can simply be added up, were built for each of the four diagnoses.</p> <p>Results</p> <p>Of 193 patients 131 questionnaires were left after excluding those with missing consent or data. Applying the suggested cut-off points, sensitivity and specificity were 87.5 and 93.5% for BPPV, 100 and 87.4% for MD, 92.3 and 83.7% for VM, 73.7 and 84.1% for PPV, respectively. By changing the cut-off points sensitivity and specificity can be adjusted to meet diagnostic needs.</p> <p>Conclusions</p> <p>The diagnostic indices showed promising diagnostic properties. Once further validated, they could provide an ease to use and yet flexible tool for screening vertigo in clinical practice and epidemiological research.</p

Inhalation von Stickstoffmonoxid

In einem in vivo Modell der Kaninchenlunge wurde intravitalmikroskopisch der Einfluss von inhaliertem NO auf die pulmonale Thrombozytenkinetik untersucht.Hierbei ergaben sich folgende wesentliche Ergebnisse: 1. Pulmonale I/R induziert eine ausgeprägte Retention von Thrombozyten in Alveolarkapillaren. 2. Die Beatmung unter Zusatz von NO zum Atemgas während der Reperfusionsphase konnte die Retention von Thrombozyten wirkungsvoll unterdrücken. 3. Die mikrohämodynamischen Parameter unterschieden sich nicht zwischen den Versuchsgruppen. Mit dieser Studie konnte erstmals in vivo gezeigt werden, das I/R der Lunge eine massive Retention von Thrombozyten in der pulmonalen Mikrozirkulation auslöst. Aus den Ergebnissen dieser beiden Studien ergeben sich somit folgende Schlussfolgerungen: Inhaliertes Stickstoffmonoxid unterdrückt in der pulmonalen Mikrozirkulation die Adhärenz aktivierter Thrombozyten und auch die Adhärenz von Thrombozyten am postischämischen alveolären und venolären Endothel. Da diese Befunde nicht durch mikrohämodynamische Veränderungen bedingt sind, muss ein direkter Einfluss von iNO auf die Adhärenzeigenschaften sowohl des Endothels wie auch der Thrombozyten angenommen werden

X-ray attenuation techniques to explore the dynamics of water in porous media

The flow of water in an unsaturated porous medium is described by Richards' equation. It is based on the assumption that the air in the pores is arbitrarily mobile and able to disappear from the pore space at any time. To solve Richards' equation a parameterization of the relationship between the water content and the matric potential is necessary: the soil-water characteristic. There are several models that describe this curve. Their parameters are typically determined from dynamic outflow experiments. A experimental setup was designed, that allows measurements of X-ray attenuation data and tomographic images during the outflow experiment. With this setup experiments were done to test the validity of Richards' equation for different boundary conditions. Therefore, the measured vertical distribution of water was compared with simulated distributions. The differences found show that the continuity of the air phase is not given at all points, and heterogeneity may prevent the determined effective parameters from being objective. Additionally, methods are introduced to analyze the rough internal structure of samples using X-ray computed tomography

Geometric and Computational Aspects of Manipulation Rules for Graph-Based Engineering Diagrams

The digitization of graph-based engineering diagrams like P&IDs or circuit drawings from optical sources as well as their subsequent processing involves both image understanding and semantic technologies. More precisely, after a raw graph has been obtained by an object detection and line extraction pipeline, semantic gaps (like resolving material flow directions) need to be overcome to retain a comprehensive, semantically correct graph. Likewise, the graph representation often needs to be altered to achieve interoperability with established CAE systems and to accommodate customer-specific requirements. Semantic technologies provide powerful tools to manipulate such data but usually require rather complicated implementation. Graphically presentable graph based rules provide a code-free mean to ease the interaction with domain experts. In order to be applicable in real-world applications, both geometric and computational aspects need to be considered. This paper explores these aspects and demonstrates use cases of such rule graphs

Pairing Generation for Airline Crew Scheduling

Airline planning is a complex and difficult process. The biggest airlines in the world plan for and operate fleets of over 700 aircraft using tens of thousands of crew members. As such, small percentages in savings translate to millions of dollars. In this thesis, we study the pairing and duty generation problem in the context of airline crew scheduling, and propose approaches to improve the computational speed and the solution quality. We propose several enumeration algorithms to generate all possible duty periods of a given schedule to improve on the time required to generate duty periods; and present a set of column generation models to improve on the solution quality. When tested on a real test case study, the proposed approaches are found to improve the computational times from 142 seconds down to less than one second, and the cost savings of 13.7%

Combining Field and Imaging Spectroscopy to Map Soil Organic Carbon in a Semiarid Environment

Semiarid regions are especially vulnerable to climate change and human-induced land-use changes and are of major importance in the context of necessary carbon sequestration and ongoing land degradation. Topsoil properties, such as soil carbon content, provide valuable indicators to these processes, and can be mapped using imaging spectroscopy (IS). In semiarid regions, this poses difficulties because models are needed that can cope with varying land surface and soil conditions, consider a partial vegetation coverage, and deal with usually low soil organic carbon (SOC) contents. We present an approach that aims at addressing these difficulties by using a combination of field and IS to map SOC in an extensively used semiarid ecosystem. In hyperspectral imagery of the HyMap sensor, the influence of nonsoil materials, i.e., vegetation, on the spectral signature of soil dominated image pixels was reduced and a residual soil signature was calculated. The proposed approach allowed this procedure up to a vegetation coverage of 40% clearly extending the mapping capability. SOC quantities are predicted by applying a spectral feature-based SOC prediction model to image data of residual soil spectra. With this approach, we could significantly increase the spatial extent for which SOC could be predicted with a minimal influence of a vegetation signal compared to previous approaches where the considered area was limited to a maximum of, e.g., 10% vegetation coverage. As a regional example, the approach was applied to a 320 km2 area in the Albany Thicket Biome, South Africa, where land cover and landuse changes have occurred due to decades of unsustainable land management. In the generated maps, spatial SOC patterns were interpreted and linked to geomorphic features and land surface processes, i.e., areas of soil erosion. It was found that the chosen approach supported the extraction of soil-related spectral image information in the semiarid region with highly varying land cover. However, the quantitative prediction of SOC contents revealed a lack in absolute accuracy