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Advanced modeling and algorithms for high-precision GNSS analysis / Kan Wang (2016)
Titre : Advanced modeling and algorithms for high-precision GNSS analysis Type de document : Thèse/HDR Auteurs : Kan Wang, Auteur Editeur : Zurich : Eidgenossische Technische Hochschule ETH - Ecole Polytechnique Fédérale de Zurich EPFZ Année de publication : 2016 Collection : Dissertationen ETH num. 23188 Note générale : bibliographie
thesis submitted to attain the degree of doctor of sciences of ETH Zurich
Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] ambiguïté entière
[Termes descripteurs IGN] antenne GPS
[Termes descripteurs IGN] centre de phase
[Termes descripteurs IGN] données BeiDou
[Termes descripteurs IGN] données Galileo
[Termes descripteurs IGN] données GPS
[Termes descripteurs IGN] double différence
[Termes descripteurs IGN] erreur systématique
[Termes descripteurs IGN] GPS en mode différentiel
[Termes descripteurs IGN] horloge
[Termes descripteurs IGN] phase GNSS
[Termes descripteurs IGN] positionnement cinématique
[Termes descripteurs IGN] récepteur GNSS
[Termes descripteurs IGN] récepteur trifréquence
[Termes descripteurs IGN] résolution d'ambiguïté
[Termes descripteurs IGN] retard ionosphèrique
[Termes descripteurs IGN] Suisse
[Termes descripteurs IGN] trajet multiple
[Vedettes matières IGN] Traitement de données GNSS
Résumé : (auteur) In the recent ten years, the Global Navigation Satellite System (GNSS) processing has experienced a fast development in many areas including the increasing number of frequencies, the higher quality of positioning instruments, e.g. the receiver clocks and the satellite clocks, and more integrated modeling and calculation strategies. This thesis includes investigations of different modeling and parameterization methods in modern GNSS positioning with the focus on three important positioning error sources: the receiver clock errors, the phase ambiguities and the ionospheric delays.
The thesis shows that making use of the high-quality receiver clocks and applying appropriate receiver clock modeling can help to improve the kinematic height estimates, which are highly correlated with the receiver clock parameters. An efficient pre-elimination and back-substitution strategy of epoch parameters with relative clock constraints between subsequent and near-subsequent epochs has been developed to enable processing of, e.g., high-rate data. A detailed analysis of the relationship between the clock quality and the improvement of kinematic heights has been performed. Studies were also conducted to decorrelate the receiver clock parameters, the kinematic heights and the troposphere parameters. Experiments with real data have shown that appropriate deterministic and stochastic clock models can also be helpful to increase the resolution of the estimated Zenith Path Delay (ZPD) parameters without obvious degradation of the stability of the kinematic heights.
The second aspect of the thesis focuses on the resolution of triple-frequency phase ambiguities with different linear combinations. A complete analytical investigation of Geometry-Free (GF) and Ionosphere-Free (IF) triple-frequency phase ambiguity resolution with minimized noise level has been performed for different frequency triplets. The analysis was done separately for the best two linear combinations and the third one. Experiments have shown that the fractional parts and the formal errors of the combined ambiguities of the best two linear combinations are relatively small for Galileo E1, E5b and E5a and GPS L1, L2 and L5 triplets, while the third linear combination remains a challenge. Further analysis with the geostationary satellites of the Beidou Navigation Satellite System (BDS) elaborated in the framework of this thesis has also confirmed that the combined ambiguities from the best two GF and IF linear combinations can be fixed by rounding, while the estimated ambiguities on L1 have relatively large deviations from the values obtained from the traditional dual-frequency double-difference ambiguity resolution. Apart from the triple-frequency ambiguity resolution on the double-difference level, the so-called track-to-track ambiguities between different tracks of the same receiver and the same satellite have also been investigated for the best two triple-frequency linear combinations using GPS L1, L2 and L5 as well as Galileo E1, E5b and E5a observations. The outcome demonstrates that elevation-dependent influences on the observations like Phase Center Variations (PCVs), Phase Center Offsets (PCOs) and multipath are important for the fixing of the track-to-track ambiguities.
The combined track-to-track ambiguities using the best two linear combinations are also effective in detecting problems in the observation data.
The third aspect of the thesis includes the investigation of the differential ionospheric delays and gradients in the region of Switzerland from 1999 to 2013. In differential Global Positioning System (GPS) positioning, the ionospheric delays for short baselines are in most cases small enough to be ignored, except under extreme conditions, e.g., during ionospheric stormy days, and for applications with high integrity requirements, e.g., during approach and landing of aircrafts. This thesis introduces an algorithm using double-difference phase measurements with resolved phase ambiguities and global ionosphere maps provided by the Center for Orbit Determination in Europe (CODE) to extract the single-difference ionospheric delays, and enabling an automatic and robust processing of the data over 15 years. The results show that the daily maximum slant ionospheric gradients calculated from the differential slant ionopheric delays and the baseline lengths from 1999 to 2013 are below the slant ionosphere gradient boundary of the Conterminous United States (CONUS) ionospheric anomaly threat model.
Numéro de notice : 17250 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Thèse étrangère Note de thèse : dissertation : sciences : ETH Zurich : 2016 En ligne : http://dx.doi.org/10.3929/ethz-a-010610972 Format de la ressource électronique : URL Permalink : Algorithms for vision-based path following along previously taught paths / Deon George Sabatta (2015)
Titre : Algorithms for vision-based path following along previously taught paths Type de document : Thèse/HDR Auteurs : Deon George Sabatta, Auteur Editeur : Zurich : Eidgenossische Technische Hochschule ETH - Ecole Polytechnique Fédérale de Zurich EPFZ Année de publication : 2015 Collection : Dissertationen ETH num. 22391 Format : 21 x 30 cm Note générale : bibliographie
A thesis submitted to attain the degree of doctor of sciences of ETH Zurich
Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes descripteurs IGN] base de données d'images
[Termes descripteurs IGN] calcul d'itinéraire
[Termes descripteurs IGN] chemin le plus court (algorithme)
[Termes descripteurs IGN] lacet
[Termes descripteurs IGN] milieu urbain
[Termes descripteurs IGN] navigation autonome
[Termes descripteurs IGN] optimisation (mathématiques)
[Termes descripteurs IGN] vision par ordinateur
Résumé : (auteur) This thesis focusses on the task of navigating an autonomous vehicle along a previously driven path using feedback obtained from a camera system. The desired path is stored in the form of a “visual memory”, essentially a collection of images, captured when the vehicle was first driven along the path. Algorithms of this form find applications in many semi-autonomous inspection/exploration tasks, where the vehicle is initially navigated by an operator, using the visual data for other purposes. On completion of the task, the operator has provided the autonomous vehicle with all the information it needs to find its way back to the starting location, and potentially repeat the entire trip. By using reference images recorded along the initial path, the system is afforded a form of global localisation using only local sensing, by providing relative information to specific key-points within the environment.
The work presented in this thesis uses, as a base, two well established path following controllers, and extends these control algorithms into the visual domain, by deriving the required parameters of each of the controllers from information gathered in the images. One of the key focus points of this work is the use of only the bearing (yaw) information from the images. By only working with feature bearing information we essentially reduce the number of parameters by half (by ignoring elevation) without sacrificing performance on 2D-manifolds.
The first controller extends the well-known shortest distance to path control algorithm, by deriving a scaled distance to path and relative orientation from the visual memory. Using the scaled distance to path, we incorporate the unknown scale that typically plagues vision-based systems, into the controller to remove the velocity dependence of the control law. This algorithm was implemented and tested in an indoor environment with a motion capture system.
The second controller extends a model predictive control (MPC) based algorithm, derived during the 2007 DARPA Grand Challenge and initially reliant on GPS information, to make use of image data, thereby alleviating the need for GPS position information. To achieve this, a novel image-based cost function is proposed that can relate the relative distances between several images. This cost function guides the choice of control trajectories to minimise the computed cost from the reference path. The performance of the proposed cost function is examined in detail, including the effects of the number of features, average distance to feature, feature observation noise and the number of outliers.
To use this cost function, the control algorithm also needs an indication of how future actions will affect the cost, and to this end feature extrapolation becomes necessary. With limited visual information, and short baselines, this process is often not very successful, and various techniques are presented to improve the performance. These include the weighting of features based on their error prediction, and the reduction of the prediction horizon required by the controller.
This control algorithm was demonstrated in both urban and extra-urban settings over paths on the order of 400m where the performance is shown to be comparable to that of differential GPS. Finally, it is also shown how the algorithm can be simply adapted to incorporate collision avoidance behaviour during the path replay in the event that the environment has changed between recording and playback.
Numéro de notice : 17201 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Thèse étrangère Note de thèse : Doctoral thesis : Sciences : ETH Zurich : 2015 En ligne : http://dx.doi.org/10.3929/ethz-a-010419338 Format de la ressource électronique : URL Permalink : Data-driven feature learning for high resolution urban land-cover classification / Piotr Andrzej Tokarczyk (2015)
Titre : Data-driven feature learning for high resolution urban land-cover classification Type de document : Thèse/HDR Auteurs : Piotr Andrzej Tokarczyk, Auteur Editeur : Zurich : Eidgenossische Technische Hochschule ETH - Ecole Polytechnique Fédérale de Zurich EPFZ Année de publication : 2015 Collection : Dissertationen ETH num. 22544 Format : 21 x 30 cm Note générale : bibliographie
A thesis submitted to attain the degree of doctor of sciences of ETH Zurich
Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes descripteurs IGN] analyse en composantes principales
[Termes descripteurs IGN] classification dirigée
[Termes descripteurs IGN] classification par forêts aléatoires
[Termes descripteurs IGN] environnement de développement
[Termes descripteurs IGN] image à très haute résolution
[Termes descripteurs IGN] image à ultra haute résolution
[Termes descripteurs IGN] milieu urbain
[Termes descripteurs IGN] occupation du sol
[Termes descripteurs IGN] prise en compte du contexte
[Termes descripteurs IGN] ruissellement
[Termes descripteurs IGN] surface imperméable
[Termes descripteurs IGN] théorie de Dempster-Shafer
Résumé : (auteur) Automated classification of aerial and satellite images is one of the fundamental challenges in remote sensing research. Over the last 30 years, researchers have tried to overcome the tedious and time consuming manual interpretation of images. With the advent of digital technologies, classification approaches facilitating image interpretation have emerged. They were quickly embraced, and nowadays classification of remote sensing imagery is a mature field with many well-established methods. However, a major yet largely unsolved problem is the design and selection of features, that would be appropriate for a specific classification task. Usually, it is not known in advance which image features would help separating object classes in an optimal way and manual feature by trial and error is still a common practice. In the last decade rapid development of remote sensing sensors gave the end-user access to very high resolution imagery. At a ground sampling distance below a meter, small objects and ne-grained texture of larger objects emerge. Thus, to properly exploit the information that these images contain, additional contextual and textural properties of objects should be extracted. Unfortunately, classification of such images is often performed using features tailored to low- and medium resolution sensors: raw pixel values, usually augmented with either simple band ratios (e.g. in form of vegetation indices), or specific texture filter banks (e.g. Gabor filters).
In this thesis, we consider the problem of feature design and selection for classification of urban land-cover from very high resolution (VHR) remote sensing images. To appropriately capture characteristic object patterns, we propose a set of simple and efficient features, called random quasi-exhaustive (RQE) feature bank. It consists of a multitude of multiscale texture features computed efficiently via integral images inside a sliding window. At the same time, we propose to sidestep manual feature selection, and let a boosting classifier choose only those features from a RQE feature bank that are able to efficiently discriminate between different object classes in a specific classification task. We believe that the proposed feature set is fairly generic to many urban remote sensing datasets, such that the features selected by the classifier can be adapted to the characteristics of a certain image: different lighting or different scene structures.
We start with presenting the developed framework for supervised classification of land-cover in urban environments. We demonstrate the efficiency of a boosting classifier used in conjunction with the RQE feature databank on five different very high resolution remote sensing datasets. Next, we move from supervised feature learning to unsupervised methods. Using random forest classifier, we investigate the performance of features extracted using data-driven methods, such as principal component analysis (PCA) or Deep Belief Networks (DBN). We show that, at least in our study, complex unsupervised and non-linear feature learning did not improve classification accuracy over standard linear baseline methods. Finally, we use the developed supervised classification framework for an application in the field of urban hydrology. We produce imperviousness maps, which are then used to model rainfall-runoff processes in urban catchments. We show that the proposed method yields results superior over state-of-the-art methods in the field of urban hydrology. Furthermore, we perform an end-to-end comparison, in which different image data sources produced using different classification methods are used as an input for a hydraulic sewer model.
Numéro de notice : 17202 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : Doctoral thesis : Sciences : ETH Zurich : 2015 En ligne : http://dx.doi.org/10.3929/ethz-a-010414770 Format de la ressource électronique : URL Permalink : Depth, anisotropy, and water equivalent of snow estimated by radar interferometry and polarimetry / Silvan Leinss (2015)
Titre : Depth, anisotropy, and water equivalent of snow estimated by radar interferometry and polarimetry Type de document : Thèse/HDR Auteurs : Silvan Leinss, Auteur Editeur : Zurich : Eidgenossische Technische Hochschule ETH - Ecole Polytechnique Fédérale de Zurich EPFZ Année de publication : 2015 Collection : Dissertationen ETH num. 23093 Importance : 243 p. Format : 21 x 30 cm Note générale : bibliographie
A thesis submitted to attain the degree of doctor of sciences of ETH Zurich
Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes descripteurs IGN] anisotropie
[Termes descripteurs IGN] image TerraSAR-X
[Termes descripteurs IGN] interféromètrie par radar à antenne synthétique
[Termes descripteurs IGN] MNS TerraSAR & TanDEM-X
[Termes descripteurs IGN] neige
[Termes descripteurs IGN] polarimétrie radar
Résumé : (auteur) Snow contributes to the water supply of almost one-sixth of the world's population and has a strong influence on the energy balance of the earth. Snow provides water for life but also threatens life in the form of avalanches and flooding due to snow melt. Most of the world's snow cover is located in remote and inaccessible regions, therefore large-scale snow monitoring is only possible with remote sensing techniques. In the entire electromagnetic spectrum, ranging from kilometer long radio waves to ultrashort gamma waves, only three atmospheric spectral windows exit through which satellites can observe the surface of the earth. Two of them, the optical and the infrared window, are often blocked by clouds or atmospheric water vapor. Visible or infrared light, which is reflected at the snow surface, is difficult to be used for derivation of any volumetric information of the snow pack. Active and passive microwave systems, which operate in the radio window, have the potential to obtain volumetric information of snow because microwaves can penetrate the snow cover. The aim of this thesis is to determine snow properties, like snow depth, snow anisotropy, and snow water equivalent, by analyzing phase differences of radar signals reflected from snow covered regions. Current radar systems provide not only the backscatter intensity of an object, but also an object-specific scattering phase. The phase contains information about object properties as well as accurate information about the propagation delay time. In this thesis, phase differences resulting from propagation delays are analyzed with respect to different polarizations, observation times and observation geometries. Based on polarimetric phase differences, a method to determine the depth of fresh snow was developed. The copolar phase difference (CPD) obtained from radar images acquired with vertically and horizontally polarized microwaves by the satellites TerraSAR-X and TanDEM-X were analyzed. Positive phase differences could be explained by a horizontal anisotropy in fresh snow, which results from snow settling. As the phase difference is a volumetric property, the magnitude of the phase difference is roughly proportional to the depth of fresh snow. The validation with snow depth measurements on the ground show that the spatial variability of the depth of fresh snow can be determined with a resolution below 100 m with space-borne sensors like TerraSAR-X. Cold temperatures have been found to decrease observed phase differences due to temperature gradient metamorphism. The observed relation between the CPD and fresh snow, snow settling, and temperature gradient metamorphism provides a contact-less and destruction-free tool to observe the anisotropy, which is a metamorphic state of snow. The measurable dielectric anisotropy is directly linked to the structural anisotropy of snow which is responsible for the mechanical stability as well as the thermal conductivity of the snow pack. This makes the anisotropy relevant for the energy balance of snow and snow covered soil. In order to measure the anisotropy, a rigorous electromagnetic model was developed which provides a parameter free link between three-dimensional two-point correlation functions of the microstructure of snow, the effective permittivity tensor, and the macroscopically measured copolar phase difference. For verification of the model, four years of ground-based radar data, acquired by the SnowScat instrument in Sodankylä, Finland, were analyzed with respect to the frequency and incidence angle dependence of the copolar phase. Computer tomography data were used for validation of the anisotropy determined from the copolar phase difference measured by SnowScat. The unique dataset of the currently longest time series of anisotropy measurements provides a new basis for improvement of existing snow models. Four years of anisotropy data were used to develop and validate a thermodynamic snow model based on meteorological input data. The model consists of three terms which describe snow settling, temperature gradient metamorphism, and relaxation based on isotropic water vapor transport. The model was calibrated by balancing the three terms in order to reproduce the measured anisotropy time series. The results of the model, vertically resolved anisotropy pro les of the snow pack, were validated with anisotropy pro les determined by computer tomography. In comparison to the anisotropy, which determines specific properties of the snow volume, the snow water equivalent (SWE) determines how much water is stored in the snow pack. Differential interferometry, where the phase difference of two radar acquisitions separated by a certain time is analyzed, is a promising tool to determine SWE. However, temporal decorrelation of the phase signal is a major drawback of this technique. A decorrelation time of a few days has been observed in space-borne acquisitions from TerraSAR-X which prevents any successful SWE determination. However, using SnowScat as a ground based radar interferometer, it was possible for the first time to measure the accumulation of SWE during four entire winter seasons. A multi-frequency phase unwrapping technique was used for reconstruction of phase wraps which occurred due to intense snow precipitation. The study was performed at exceptionally high frequencies in the X- and Ku-band and with a very high temporal resolution of only 4 hours. The successful demonstration of differential interferometry to determine SWE raises hope to apply the demonstrated technique on data of future radar satellites which operate at longer repeat times of a few days and lower frequencies of a few GHz. Both methods, the CPD analysis as well as differential interferometry, cannot be vi applied for wet snow. Microwave penetration into wet snow is generally small and most of the reflected energy results from scattering at the snow surface. This is interesting for single-pass SAR interferometry, where phase differences are compared, which are measured by two SAR-sensors which simultaneously observe the same scene with slightly different angles. Single-pass SAR interferometry can provide accurate surface models at a horizontal resolution of a few meters. The difference between two digital elevation models (DEM), one obtained during snow free conditions and one obtained during the onset of snow melt, can therefore provide direct information about snow depth. DEM differencing was applied on TanDEM-X acquisitions from spring and autumn and snow depths maps were obtained which agree with the snow- depth-maps provided by the Institute for Snow and Avalanche Research, SLF. A key requirement for successful snow depth estimation is that the snow surface can be recognized as wet. As the backscatter intensity decreases significantly during snow melt, wet snow detection is straight forward and the total accumulated snow depth of wet spring snow can be determined. This thesis shows that the analysis of the phase signal contained in radar acquisitions provides a broad spectrum of information about the snow pack. The developed method for anisotropy determination provides not only a unique opportunity to improve snow models, but also a method to globally sense the metamorphic state of snow. The currently longest radar-derived time series of SWE measurements raise hope to apply differential interferometry for global SWE determination of dry snow. The shown accuracy for snow depth determination from high frequency, interferometric, single-pass SAR systems demonstrates that such systems are important missions for monitoring changes in snow depth and ice thickness in remote alpine and polar regions in order monitor changes of the global distribution of fresh water stored in the form of ice or snow. Numéro de notice : 17199 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : doctoral thesis : Sciences : ETH Zurich : 2015 En ligne : http://dx.doi.org/10.3929/ethz-a-010603517 Format de la ressource électronique : URL Permalink : To die or not to die: Forest dynamics in Switzerland under climate change / Nicolas Bircher (2015)
Titre : To die or not to die: Forest dynamics in Switzerland under climate change Type de document : Thèse/HDR Auteurs : Nicolas Bircher, Auteur Editeur : Zurich : Eidgenossische Technische Hochschule ETH - Ecole Polytechnique Fédérale de Zurich EPFZ Année de publication : 2015 Collection : Dissertationen ETH num. 22775 Importance : 188 p. Format : 21 x 30 cm Note générale : bibliographie
A thesis submitted to attain the degree of doctor of sciences of ETH Zurich
Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] composition floristique
[Termes descripteurs IGN] forêt alpestre
[Termes descripteurs IGN] inventaire forestier étranger (données)
[Termes descripteurs IGN] modèle dynamique
[Termes descripteurs IGN] Picea abies
[Termes descripteurs IGN] série temporelle
[Termes descripteurs IGN] structure d'un peuplement forestier
[Termes descripteurs IGN] Suisse
[Termes descripteurs IGN] végétation
[Vedettes matières IGN] Végétation et changement climatique
Résumé : (auteur) A high diversity of forest ecosystems is found around the globe providing various ecosystem services to humans. Responses of forests to recent increases of drought events have given rise to serious concerns about future forest development. Since anthropogenic climate change is proceeding at an unprecedented rate, the forestry sector is challenged to swiftly develop and plan adaptive management measures that guarantee the sustainable provision of forest ecosystem services in the future. The planning of management strategies is strongly dependent on reliable knowledge on future forest dynamics. To this end, the Swiss government has launched an extensive research program to examine the impact of climate change on Swiss forests. One aim among others is to assess the sensitivity of common forest types of Switzerland to climate change.
Dynamic vegetation models (DVMs) are suitable to provide quantitative assessments of forest sensitivity to climate change, as their flexibility allows considering dynamic vegetation transitions under conditions that do not represent a steady state. Among DVMs, forest gap models portray long-term forest dynamics at the stand scale taking biotic interactions such as competition into account. Recent integration of sophisticated management techniques has substantially extended their range of application from unmanaged to complex mixed-species forests under management, thus making them interesting tools for the assessment of climate change impacts on forest ecosystems. However, forest gap models integrate a large number of ecological processes that still lack an empirical base. This is particularly true for tree mortality – a key demographic process in forest dynamics – where increasing empirical research has been followed by little action in DVMs. Thus, although it is widely acknowledged that empirical functions should be integrated into DVMs to enhance ecological realism, little is known about whet her this approach leads to an increased robustness of model projections.
Given this background, my thesis includes two major objectives: 1) to examine the potential of empirical mortality functions in dynamic vegetation models and 2) to assess the sensitivity of common Swiss forests to climate change.
In Chapter 1 of this thesis, I implemented an inventory- and a tree-ring based mortality function in the forest gap model ForClim and combined them with a stochastic and a deterministic approach for the determination of tree status (alive vs. dead). These four new model versions were tested for two Norway spruces stands, one of which was managed (inventory time series of 72 years) and the other was unmanaged (41 years). Furthermore, I ran long-term simulations (~400 years) into the future to test model behavior under three climate scenarios. I showed that three out of the four mode l versions showed good agreement for stand basal area and stem numbers when compared against inventory data of both forest sites. Due to very similar model behavior, an unambiguous choice of a “best” model version was, however, not possible. In contrast, long -term simulations revealed very different behavior of the mortality models, indicating that the choice of the mortality function is crucial for simulated forest dynamics. Based on these results, I concluded that 1) empirical mortality functions are valuable replacements for current theoretical mortality algorithms in dynamic vegetation models 2) but further tests would be needed to rigorously assess their potential and to better understand interactions of the mortality function with other model processes.
Enhanced use of empirical data in dynamic vegetation models is widely advocated. However, it is largely unknown whether empirically derive d functions are compatible with the wide range of processes and interactions that are usually found in DVMs and thus, whether they lead to an better model performance. In Chapter 2 , I addressed this question with the focus on the inventory-based mortality function that has already been used in Chapter 1 . I used Bayesian methods to recalibrate its mortality parameters within ForClim. I compared its performance with the ForClim version containing the original, empirically fitted mortality parameters and with the current ForClim v3.3 that included a theoretical mortality function. Calibration and subsequent validation was based on inventory data of 30 Swiss natural forest reserves. Similarities between the calibrated and the empirically fitted mortality parameters suggest that the general structure of ForClim is appropriate to integrate empirical mortality functions. However, I found some discrepancies that indicate necessary improvements regarding the role of species’ shade tolerance in growth-mortality relationships and an optimal balance between growth and mortality. Bayesian calibration led to best performance both at calibration and validation sites. Furthermore, it revealed that the sensitivity of ForClim to parametric uncertainty is particularly high for trees in low dbh classes but surprisingly small for standard model outputs such as basal area.
Assessing the sensitivity of common forest stands in Switzerland with a forest gap model makes it necessary 1) to know which forest stands are common and 2) to have suitable data for model initialization. In Chapter 3 , I developed a stratification of the Swiss forest area to identify those forest types of Switzerland that , in terms of their stand structure and tree species composition, are most common in different eco-regions and elevation zones. I used plot data form the third Swiss National Forest Inventory (NFI3) that contained both stand attributes and single-tree data. NFI plots were grouped into eco -regions and elevation zones according to the “Guide for sustainability in protection forests” (NaiS). I further segregated NFI plots into more groups based on two forest stand attributes: vertical stand structure and developmental stage. In a last step, I relied on recommendations of sylvicultural experts for dividing some groups into more strata to strengthen a realistic tree species composition. The stratification resulted in 71 strata that contained 25% of all NFI forest plots. Single-tree data of all NFI plots associated to one stratum were aggregate d. Although the final result is a somewhat “artificial” forest stand, it has the tremendous advantage that NFI plot data can be used directly for stand initialization in the forest gap model ForClim.
In Switzerland, studies on forest sensitivity to climate change often focus on extreme sites where shifts in tree species composition are already visible while less attention is paid to the fate of common forest stands that are most important for Swiss forestry. In Chapter 4, I ran simulations for 71 strata that had been identified in the previous chapter using two model versions to examine their development until the end of the 21 st century (year 2100). Simulations were run with common Swiss forest management strategies and without management. I considered forest development under current climate (1980-2009) and under 11 different climate change scenarios assuming an A2 greenhouse gas emission scenario. According to these simulation results, shifts in structure and composition of Swiss forests have to be expected for the second half of this century. However, high variability among the strata was found due to drivers of small-scaled forest dynamics such as regional climate, elevation gradients and current species composition. I showed that current management regimes can alleviate the negative impacts of climate change but adaptive measures are necessary to be applied at a site-specific and objective-oriented base. In conclusion, model- based assessments on forest sensitivity can only provide reliable decision-making support for forest managers if small-scaled drivers of forest stand dynamics are take n into consideration.
In the Synthesis, I reflect the findings of the previous chapters by discussing the potential of empirical mortality functions in DVMs and the use of forest gap models – as one type of DVM – as tools for decision-support regarding forest management under climate change. I come to the conclusion that empirical mortality functions are capable to further improve the performance of DVMs and to increase our confidence in their projections. However, empirical functions come with limitations, which might constrain avalid applicability. For this reason, I advocate not to focus on one individual function but to aggregate knowledge on mortality mechanism and data from various sources to enhance the validity of the tree mortality mechanism in DVMs beyond individual empirical data sets. Climate change is expected to have strong effects on future development of current Swiss forests at various sites. High variability in forest response to a changing environment underlines the need to plan future forest strategies at the local scale. Forest gap models have limitations that need to be discussed and tackled. Still, I am convinced that they have the potential to play a key role in decision-making processes as they can provide what decision makers need: a comprehensive reflection of essential processes and an adequate spatial resolution.
Numéro de notice : 17200 Affiliation des auteurs : non IGN Thématique : FORET Nature : Thèse étrangère Note de thèse : doctoral thesis : Sciences : ETH Zurich : 2015 En ligne : http://dx.doi.org/10.3929/ethz-a-010596194 Format de la ressource électronique : URL Permalink : Mapping literature : spatial data modelling and automated cartographic visualisation of fictional spaces / Anne-Kathrin Weber (2014)PermalinkCartographic web services / I. Enescu (2011)PermalinkModel-driven tools to support conceptual geospatial modelling / J. Althoff (2011)PermalinkNovel drawing algorithms and application of texture mapping for 2D cartographic line symbolization / Fei He (2008)PermalinkModellhafte Arbeitsabläufe zur digitalen Erstellung von topographischen und geologischen Karten und dreidimensionalen Visualisierungen / Lorenz Hurni (1995)PermalinkAspekte der graphischen Gestaltung komplexer Wirtschaftskarten in Schulatlanten / L. Brodersen (1986)Permalink