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This thesis takes place in the context of the spread of immersive content. For the last couple of years, immersive audio recording and playback technologies have gained momentum and have become more and more popular. New codecs are needed to handle those spatial audio formats, especially for communication applications. There are several ways to represent spatial audio scenes. In this thesis, we focused on First Order Ambisonic. The first part of our research focused on improving multi-mono coding by decorrelated each ambisonic signal component before the multi-mono coding. To guarantee signal continuity between frames, efficient quantization new mechanisms are proposed. In the second part of this thesis, we proposed a new coding concept using a powermap to recreate the original spatial image. With this concept, we proposed two compressing methods. The first one is a post-processing focused on limiting the spatial distortion of the decoded signal. The spatial correction is based on the difference between the original and the decoded spatial image. This post-processing is later extended to a parametric coding method. The last part of this thesis presents a more exploratory method. This method studied audio signal compression by neural networks inspired by image compression models using variational autoencoders., Cette thèse s'inscrit dans le contexte de l'essor des contenus immersifs. Depuis quelques années, les technologies de captation et de restitution sonore immersive se sont développées de manière importante. Ce nouveau contenu a fait naître le besoin de créer de nouvelles méthodes dédiées à la compression audio spatialisée, notamment dans le domaine de la téléphonie et des services conversationnels. Il existe plusieurs manières de représenter l'audio spatialisé, dans cette thèse nous sommes intéressés à l'ambisonie d'ordre 1. Dans un premier temps, nos travaux ont porté sur la recherche d'une solution pour améliorer le codage multimono. Cette solution consiste en un traitement en amont du codec multimono pour décorréler les signaux des composantes ambisoniques. Une attention particulière a été portée à la garantie de continuité du signal entre les trames et à la quantification des métadonnées spatiales. Dans un second temps, nous avons étudié comment utiliser la connaissance de la répartition de l'énergie du signal dans l'espace, aussi appelée image spatiale, pour créer de nouvelles méthodes de codage. L'utilisation de cette image spatiale a permis d'élaborer deux méthodes de compression. La première approche proposée est basée sur la correction spatiale du signal décodés. Cette correction se base sur la différence entre les images spatiales du signal d'origine et du signal décodés pour atténuer les altérations spatiales. Ce principe a été étendu dans une seconde approche à une méthode de codage paramétrique. Dans une dernière partie de cette thèse, plus exploratoire, nous avons étudié une approche de compression par réseaux de neurones en nous inspirant de modèles de compression d'images par auto-encodeur variationnel.

Canopy temperature (CT) has been related to water-use and yield formation in crops. However, constantly (e.g., sun illumination angle, ambient temperature) as well as rapidly (e.g., clouds) changing environmental conditions make it difficult to compare measurements taken even at short time intervals. This poses a great challenge for high-throughput field phenotyping (HTFP). The aim of this study was to i) set up a workflow for unmanned aerial vehicles (UAV) based HTFP of CT, ii) investigate different data processing procedures to combine information from multiple images into orthomosaics, iii) investigate the repeatability of the resulting CT by means of heritability, and iv) investigate the optimal timing for thermography measurements. Additionally, the approach was v) compared with other methods for HTFP of CT. The study was carried out in a winter wheat field trial with 354 genotypes planted in two replications in a temperate climate, where a UAV captured CT in a time series of 24 flights during 6 weeks of the grain-filling phase. Custom-made thermal ground control points enabled accurate georeferencing of the data. The generated thermal orthomosaics had a high spatial accuracy (mean ground sampling distance of 5.03 cm/pixel) and position accuracy [mean root-mean-square deviation (RMSE) = 4.79 cm] over all time points. An analysis on the impact of the measurement geometry revealed a gradient of apparent CT in parallel to the principle plane of the sun and a hotspot around nadir. Averaging information from all available images (and all measurement geometries) for an area of interest provided the best results by means of heritability. Correcting for spatial in-field heterogeneity as well as slight environmental changes during the measurements were performed with the R package SpATS. CT heritability ranged from 0.36 to 0.74. Highest heritability values were found in the early afternoon. Since senescence was found to influence the results, it is recommended to measure CT in wheat after flowering and before the onset of senescence. Overall, low-altitude and high-resolution remote sensing proved suitable to assess the CT of crop genotypes in a large number of small field plots as is required in crop breeding and variety testing experiments.

Controlling spatial variation in agricultural field trials is the most important step to compare treatments efficiently and accurately. Spatial variability can be controlled at the experimental design level with the assignment of treatments to experimental units and at the modeling level with the use of spatial corrections and other modeling strategies. The goal of this study was to compare the efficiency of methods used to control spatial variation in a wide range of scenarios using a simulation approach based on real wheat data. Specifically, classic and spatial experimental designs with and without a twodimensional autoregressive spatial correction were evaluated in scenarios that include differing experimental unit sizes, experiment sizes, relationships among genotypes, genotype by environment interaction levels, and trait heritabilities. Fully replicated designs outperformed partially and unreplicated designs in terms of accuracy; the alpha-lattice incomplete block design was best in all scenarios of the medium-sized experiments.However, in terms of response to selection, partially replicated experiments that evaluate large population sizes were superior in most scenarios. The AR1×AR1 spatial correction had little benefit in most scenarios except for the medium-sized experiments with the largest experimental unit size and low GE. Overall, the results from this study provide a guide to researchers designing and analyzing large field experiments. Supplementary materials accompanying this paper appear online.

Canopy temperature (CT) has been related to water-use and yield formation in crops. However, constantly (e.g., sun illumination angle, ambient temperature) as well as rapidly (e.g., clouds) changing environmental conditions make it difficult to compare measurements taken even at short time intervals. This poses a great challenge for high-throughput field phenotyping (HTFP). The aim of this study was to i) set up a workflow for unmanned aerial vehicles (UAV) based HTFP of CT, ii) investigate different data processing procedures to combine information from multiple images into orthomosaics, iii) investigate the repeatability of the resulting CT by means of heritability, and iv) investigate the optimal timing for thermography measurements. Additionally, the approach was v) compared with other methods for HTFP of CT. The study was carried out in a winter wheat field trial with 354 genotypes planted in two replications in a temperate climate, where a UAV captured CT in a time series of 24 flights during 6 weeks of the grain-filling phase. Custom-made thermal ground control points enabled accurate georeferencing of the data. The generated thermal orthomosaics had a high spatial accuracy (mean ground sampling distance of 5.03 cm/pixel) and position accuracy [mean root-mean-square deviation (RMSE) = 4.79 cm] over all time points. An analysis on the impact of the measurement geometry revealed a gradient of apparent CT in parallel to the principle plane of the sun and a hotspot around nadir. Averaging information from all available images (and all measurement geometries) for an area of interest provided the best results by means of heritability. Correcting for spatial in-field heterogeneity as well as slight environmental changes during the measurements were performed with the R package SpATS. CT heritability ranged from 0.36 to 0.74. Highest heritability values were found in the early afternoon. Since senescence was found to influence the results, it is recommended to measure CT in wheat after flowering and before the onset of senescence. Overall, low-altitude and high-resolution remote sensing proved suitable to assess the CT of crop genotypes in a large number of small field plots as is required in crop breeding and variety testing experiments.

10 pags., 8 figs., 4 tabs. -- Open Access funded by Creative Commons Atribution Licence 3.0, In this paper, the fisheye camera method is validated for spatial non-uniformity corrections in luminous flux measurements with integrating spheres. The method was tested in eight integrating spheres with six LED lamps, and the determined angular intensity distributions and spatial non-uniformity correction factors were compared with the results of five goniophotometers. The average closeness score, describing the similarity between any two distributions, was 94.6 out of 100 for the distributions obtained using the fisheye camera method when compared with the goniophotometric results. The average closeness score for the five goniophotometers, when each goniophotometer was compared with the other four, was 96.6. On average, the relative deviation between the two methods was 0.05% when calculating the spatial corrections. The most significant sources of uncertainty for the fisheye camera method were large, view-obstructing sphere elements residing close to the camera port., The work leading to this study is partly funded by the European Metrology Programme for Innovation and Research (EMPIR) Project 15SIB07 PhotoLED ‘Future Photometry Based on Solid State Lighting Products’. The EMPIR initiative is cofunded by the European Union’s Horizon 2020 research and innovation programme and the EMPIR Participating States. Acknowledges the funded position of Aalto ELEC doctoral school and the support of the Tutkijat Maailmalle program.

This paper presents a fisheye camera method for determining spatial non-uniformity corrections in luminous flux measurements with integrating spheres. Using a fisheye camera installed into a port of an integrating sphere, the relative angular intensity distribution of the lamp under test is determined. This angular distribution is used for calculating the spatial non-uniformity correction for the lamp when combined with the spatial responsivity data of the sphere. The method was validated by comparing it to a traditional goniophotometric approach when determining spatial correction factors for 13 LED lamps with different angular spreads. The deviations between the spatial correction factors obtained using the two methods ranged from -0.15% to 0.15%. The mean magnitude of the deviations was 0.06%. For a typical LED lamp, the expanded uncertainty (k = 2) for the spatial non-uniformity correction factor was evaluated to be 0.28%. The fisheye camera method removes the need for goniophotometric measurements in determining spatial non-uniformity corrections, thus resulting in considerable system simplification. Generally, no permanent modifications to existing integrating spheres are required.

Sugar maple (Acer saccharum Marshall) tree is an important part of North American forest ecosystems as well as a source of sap for maple syrup production. The quality, yield, and productivity of syrup can be considerably improved while also reducing production costs and the carbon footprint of the process by developing elite germplasm with high sap sugar content. The current work aims to provide a basis to identify and propagate elite sugar maple trees. A 22-year old seed based population of trees of uniform age, planted in uniform spacing was evaluated for sap sugar content and tree morphology (height and trunk circumference) over a period of three years and statistical measures to correct spatial trends in productivity were assessed. Furthermore, clonal propagation of sugar maple through conventional and micropropagation techniques has been largely unsuccessful and the basis of this recalcitrance has remained unknown. Optimization of light intensity to improve in vitro multiplication was attempted by culturing plantlets under three intensities (4, 16 and 40 μmol m−2 s−1) of two spectra of light (red-blue and full-spectrum white) and quantifying stress using chlorophyll fluorometry. The salient findings of this research are: 1) The nutritionally important properties of maple syrup vary across its grades and light transmittance, indicating the advantages of selecting and propagating elite trees to produce specific grades of syrup, 2) nearest neighbour based spatial correction method was superior over thin plate spline in eliminating the spatial trends in the field, 3) the critical factor limiting sugar maple’s response to in vitro propagation was light intensity and a unique low light intensity is required to overcome its recalcitrance. Since several limitations of conventional in vitro lighting systems viz., non-uniform intensity, inability to modulate intensity and spectra, and tedious procedures for randomization and replication of light quality treatments were faced, 3D printing was employed to develop a novel culture vessel with independently controlled LED lighting. Overall, the present studies not only provide a basis to identify, and propagate elite sugar maple trees but also provide novel tools to evaluate the influence of light quality in in vitro studies.

In crop breeding, the interest of predicting the performance of candidate cultivars in the field has increased due to recent advances in molecular breeding technologies. However, the complexity of the wheat genome presents some challenges for applying new technologies in molecular marker identification with next-generation sequencing. We applied genotyping-by-sequencing, a recently developed method to identify single-nucleotide polymorphisms, in the genomes of 384 wheat (Triticum aestivum) genotypes that were field tested under three different water regimes in Mediterranean climatic conditions: rain-fed only, mild water stress, and fully irrigated. We identified 102,324 single-nucleotide polymorphisms in these genotypes, and the phenotypic data were used to train and test genomic selection models intended to predict yield, thousand-kernel weight, number of kernels per spike, and heading date. Phenotypic data showed marked spatial variation. Therefore, different models were tested to correct the trends observed in the field. A mixed-model using moving-means as a covariate was found to best fit the data. When we applied the genomic selection models, the accuracy of predicted traits increased with spatial adjustment. Multiple genomic selection models were tested, and a Gaussian kernel model was determined to give the highest accuracy. The best predictions between environments were obtained when data from different years were used to train the model. Our results confirm that genotyping-by-sequencing is an effective tool to obtain genome-wide information for crops with complex genomes, that these data are efficient for predicting traits, and that correction of spatial variation is a crucial ingredient to increase prediction accuracy in genomic selection models.

Recognizing changes in ecosystem services (ES) and their relationships is the basis of achieving sustainable regional development. Regional collaborative development has become the core strategy of the development of the Beijing–Tianjin–Hebei (BTH) region. However, sub regions have different ecological changes and relationships. Here, we quantify and map ES, including water yield, sediment retention, carbon sequestration and grain productive capacity in 2000, 2005, 2010 and 2015, using several biophysical models and explore the relationships of spatial correction, trade-offs and synergies among multiple ES in different spatial scales. Results across the four years show that the quality and variation tendency of ES from each region are spatially heterogeneous. The relationship between ES that are not significant in the entire region shows different correlations in individual ecological–functional zones. From the perspective of regional disparity, the effect of land use factor and correlative mechanisms among ES are analyzed. To observe the spatiotemporal variations and relationships of ES in individual regions, land use management policies are proposed on the basis of the results of the relationships among ES.