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Biomass and Carbon Stock Quantification in Cork Oak Forest of Maamora Using a New Approach Based on the Combination of Aerial Laser Scanning Carried by Unmanned Aerial Vehicle and Terrestrial Laser Scanning Data

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FORESTS 2022年第8期13卷 1211页

作者： Sanaa, Fadil Imane, Sebari Mohamed, Bouhaloua Kenza, Ait El kadi Souhail, Kellouch Lfalah, Hamza Khadija, Meghraoui IAV Hassan II Sch Geomat & Surveying Engn Dept Cartog & Photogrammetry Rabat 10000 Morocco Natl Agcy Water & Forests Rabat 10000 Morocco IAV Hassan II Dept Nat Resources & Environm Rabat 10000 Morocco AXIGEO Campanie Marrakech 40000 Morocco

The Mediterranean forests, particularly Cork oak (Quercus suber L., 1927), make a major contribution to the fight against climate change through Carbon sequestration. Hence, there is a great interest in the accurate quantification of biomass and carbon stock. In this context, this study aims at assessing the performance of a new approach, based on the combination of Unmanned aerial vehicle airborne Aerial laser scanning (ALS-UAV) and Terrestrial laser scanning (TLS) data, in the determination of dendrometric parameters (Circumference at 1.30 m and tree Height), and consequently the estimation of biomass and carbon stock, considering field data as reference. This study takes the Maamora forest in Morocco as an example of a Mediterranean Cork oak forest. The methodology consists of collecting data at three levels: the entire area level for an ALS-UAV scan, the plot and tree levels for TLS surveys, as well as field data collection. Afterwards, dendrometric parameters (Circumference at 1.30 m and the tree height) were estimated using individual tree segmentation and biomass;the carbon stock (aboveground, belowground, and total) was estimated using allometric equations. The comparison of the estimated dendrometric parameters with those measured in the field shows a strong relationship, with a Pearson coefficient of 0.86 and 0.83, a correlation coefficient (R-2) of 0.81 and 0.71, and a Root mean square error (RMSE) of 1.84 cm and 0.47 m, respectively. Concerning the biomass and carbon stock estimation, the proposed approach gives a satisfactory accuracy, with a Pearson coefficient of 0.77, an R2 of 0.83, and an RMSE of 36.40 kg for biomass and 20.24 kg for carbon stock.

关键词： biomass carbon stock combination of ALS-UAV and TLS data segmentation tree Mediterranean region allometric equations Cork oak forest

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Risk factors and the resistance mechanisms involved in Pseudomonas aeruginosa mutation in critically ill patients

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JOURNAL OF INTENSIVE CARE 2019年第1期7卷 36页

作者： Druge, Stephanie Ruiz, Stephanie Vardon-Bounes, Fanny Grare, Marion Labaste, Francois Seguin, Thierry Fourcade, Olivier Minville, Vincent Conil, Jean-Marie Georges, Bernard CHU Rangueil Serv Reanimat Polyvalente TSA 50032 1 Ave Jean PoulhesPole Anesthesie & Reanimat F-31059 Toulouse 9 France Inst Federatif Biol Lab Bacteriol & Hyg TSA 40031 330 Ave Grande Bretagne F-31059 Toulouse 9 France Univ Hosp Toulouse Dept Anesthesiol & Intens Care Units F-31059 Toulouse 9 France

Background: The objective of this study was to determine the main risk factors of Pseudomonas aeruginosa mutation as well as the mechanisms of acquired resistance. Methods: We conducted a 2-year prospective study in patients who were carriers of a Pseudomonas aeruginosa strain and who had been admitted to a medical/surgical ICU. Results: Of the 153 patients who were included, 34 had a mutation in their strain. In a multivariate analysis, a duration of ventilation > 24 days was a risk factor for mutation (risk ratio 4.29;CI 95% 1.94-9.49) while initial resistance was a protective factor (RR 0.36;CI 95% 0.18-0.71). In a univariate analysis, exposure of P. aeruginosa to ceftazidime was associated with an over-production of AmpC cephalosporinase and exposure to meropenem was associated with impermeability. A segmentation method based on the duration of ventilation (> 24 days), initial resistance, and exposure of strains to ceftazidime made it possible to predict at 83% the occurrence of mutation. Conclusion: The duration of ventilation and the presence of resistance as soon as P. aeruginosa is identified are predictive factors of mutation in ICU patients.

关键词： Pseudomonas aeruginosa Mutation Antibiotic Resistance mechanism ICU (intensive care unit) segmentation tree

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tree-Structured Models for Efficient Multi-Cue Scene Labeling

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2017年第7期39卷 1444-1454页

作者： Cordts, Marius Rehfeld, Timo Enzweiler, Markus Franke, Uwe Roth, Stefan Daimler AG Dept Environm Percept Boblingen Germany Tech Univ Darmstadt Dept Comp Sci Darmstadt Germany

We propose a novel approach to semantic scene labeling in urban scenarios, which aims to combine excellent recognition performance with highest levels of computational efficiency. To that end, we exploit efficient tree-structured models on two levels: pixels and superpixels. At the pixel level, we propose to unify pixel labeling and the extraction of semantic texton features within a single architecture, so-called encode-and-classify trees. At the superpixel level, we put forward a multi-cue segmentation tree that groups superpixels at multiple granularities. Through learning, the segmentation tree effectively exploits and aggregates a wide range of complementary information present in the data. A tree-structured CRF is then used to jointly infer the labels of all regions across the tree. Finally, we introduce a novel object-centric evaluation method that specifically addresses the urban setting with its strongly varying object scales. Our experiments demonstrate competitive labeling performance compared to the state of the art, while achieving near real-time frame rates of up to 20 fps.

关键词： Scene labeling automotive decision forests segmentation tree depth cues superpixels stixels

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RANDOMIZED MOTION ESTIMATION

RANDOMIZED MOTION ESTIMATION

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IEEE International Conference on Image Processing

作者： Boltz, Sylvain Nielsen, Frank Ecole Polytech F-91128 Palaiseau France

ISBN: (纸本)9781424479948

Motion estimation is known to be a non-convex optimization problem. This non-convexity comes from several ambiguities in motion estimation such as the aperture problem, or fast motion relative to the magnitude of the image gradient. In this paper, we propose a fast random search algorithm to estimate motion. Randomized algorithms are very popular in computer science and optimization for non-convex problems. However, to the best of our knowledge none has been used so far for motion estimation, due to complexity constraints. In this paper, we propose two fast algorithms to perform random search on image pixels. One produces a dense optical flow by matching patches. The other one takes advantage of a quad tree or segmentation tree structure of the image to estimate motion in regions of increasing size. Quantitative and visual results show that the motion obtained seems to be a very advantageous compromise between speed and quality of estimated motion.

关键词： Optical flow Matching Random search segmentation tree

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The intensity of a coffee rust epidemic is dependent on production situations

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ECOLOGICAL MODELLING 2006年第3-4期197卷 431-447页

作者： Avelino, J. Zelaya, H. Merlo, A. Pineda, A. Ordonez, M. Savary, S. Ctr Cooperat Int Rech Agron Dev F-34398 Montpellier 5 France Inst Hondureno Cafe Tegucigalpa Honduras INRA Ctr Rech INRA Bordeaux Aquitaine UMR Sante Vegetale F-33883 Villenave Dornon France

To gain a clearer understanding of conditions conducive to the development of coffee rust and improve disease control, we monitored the development of rust epidemics in 73 plots in Honduras, over 1-3 years depending on the case, focusing on coffee tree characteristics, crop management patterns, and the environment. A simple correspondence analysis was used to show that a link could be found between certain production situations and the intensity of coffee rust epidemics. Local characteristics specific to each plantation were particularly well linked to the intensity of coffee rust epidemics, whereas regional factors such as rainfall appeared to be of secondary importance. The yield and the number of leaves of the coffee trees were positively linked to epidemic development. Soil pH and fertilisation. were negatively associated with epidemic development. Shade, when it did not limit yield, probably affected the microclimate in such a way that coffee rust incidence increased. Altitude was a serious constraint in disease development. These links were illustrated by a segmentation tree, which helped to define risk domains and rationalise coffee rust control. it also provided an understanding of how intensifying Arabica cultivation, through its effects on yield and soil acidification, increased the risk of a serious coffee rust epidemic occurring. (c) 2006 Elsevier B.V All rights reserved.

关键词： Coffea arabica Hemileia vastatrix climate soil crop management yield foliage disease control correspondence analysis cluster analysis segmentation tree Honduras

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Stability and scalability in decision trees

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COMPUTATIONAL STATISTICS 2003年第4期18卷 505-520页

作者： Aluja-Banet, T Nafria, E Univ Politecn Catalunya Dept Stat & Operat Res ES-08034 Barcelona Spain Taylor Nelson Sofres Audiencia Medios Barcelona 08190 Spain

tree-based methods are statistical procedures for automatic learning from data, whose main applications are integrated into a data-mining environment for decision support systems. Here, we focus on two problems of decision trees: the stability of the rules obtained and their applicability to huge data sets. Since the tree-growing process is highly dependent on data, i.e. small fluctuations in data can cause big changes in the tree-growing process, we focused instead on the stability of the trees themselves. To this end we propose a series of data diagnostics to prevent internal instability in the tree-growing process before a particular split is made. Indeed, to be effective in actual managerial problems they must be applicable to massive amounts of stored data with maximum efficiency. For this reason we studied the theoretical complexity of such an algorithm. Finally, we present an algorithm that can cope with such problems, with linear cost upon the individuals, which can use a robust impurity measure as a splitting criterion.

关键词： segmentation tree CART data mining stability scalability

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Symbolic object description of strata by segmentation trees

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COMPUTATIONAL STATISTICS 2000年第1期15卷 13-24页

作者： Bravo, MC García-Santesmases, JM Univ Complutense Madrid Ctr Proc Datos E-28040 Madrid Spain Univ Complutense Madrid F CC Matemat D Estadist & Inv Operat E-28040 Madrid Spain

Based in a,generalised recursive tree-building algorithm for populations partitioned into strata a method to obtain simple descriptions of strata is presented. Also strata with a common rule are obtained. Common predictors and criterion variable describe population in all strata or classes of individuals. Algorithm considers strata structure in tree-building algorithm and combines in each step maximisation of an information content measure for the criterion variable in a new binary partition of the population and selection of decisional nodes, based in quality of prediction for subsets of strata. Each decisional tree node is composed of a set of strata and a rule for individuals in these strata that will jointly explain the criterion variable. Symbolic data analysis fits the method. Input of the algorithm is composed of classes of individuals. Algorithm is extended to individuals described by probabilistic symbolic objects. As output, symbolic objects describe tree, decisional nodes and strata.

关键词： tree-growing algorithm segmentation tree decision tree information content measure symbolic data analysis

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NON-PARAMETRIC MULTISCALE CURVE SMOOTHING

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International Journal of Pattern Recognition and Artificial Intelligence 1994年第6期8卷 1381-1406页

作者： PAUL L. ROSIN School of Computing Cognitive Systems Group Curtin University of Technology Perth 6001 Western Australia Current address: Institute for Remote Sensing Applications Terminale Postale 442 Joint Research Centre 1–21020 Ispra (VA) Italy.

Lowe 8 demonstrated a method for automatically segmenting and smoothing image curves by varying degrees. It was intended to remove noise and unnecessary fine detail, aiding subsequent processing such as grouping and matching. An alternative technique is described in this paper that is based on recursively subdividing the curve into alternative sets of sections. Rather than use thresholds on the values of curvature and its derivatives to determine the segmentation and degree of smoothing our technique is driven by three qualitative measures: (1) a criterion for selecting potential breakpoints, (2) a criterion for determining the amount of smoothing for curve sections, (3) a significance measure that determines which sections form the best selection. The advantages of the technique are robustness, scale invariance, and the absence of parameters.

关键词： Gaussian smoothing multiscale curve representation polynomial fitting natural scales significance measure segmentation tree

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