L’utilisation de lasers pulsés ouvre la voie à de nouvelles fonctionnalités et à une compacité accrue des systèmes lidars pour la mesure de vibration à distance. Or des bruits de phase et d’amplitude affectent le signal lidar, diminuant particulièrement les performances du régime impulsionnel à multiplets, concept par ailleurs prometteur pour la mesure à longue portée.Ces travaux portent d’abord sur la caractérisation expérimentale de ces bruits afin de les modéliser, en particulier l’effet de la turbulence atmosphérique. Puis nous cherchons à optimiser les formes d’ondes et le traitement du signal en fonction de la vibration et de la statistique de bruit. Nous proposons une méthode originale basée sur un estimateur du maximum de vraisemblance de la fréquence Doppler, associé à une extraction à partir de la représentation temps-fréquence du signal. L’apport de cette approche est constaté par la simulation et l’expérience, en comparant les performances de plusieurs régimes d’émission. / The use of pulsed lasers could lead to new functionnalities and increased compacity of lidar systems for remote vibration sensing. However, specific amplitude and phase noises affect the lidar signal, and particularly decrease the performance of a polypulse based emission regime, thought to be promising for very long range measurements.This work first deals with the experimental characterization of these noise sources in order to properly model them, with a focus on atmospheric turbulence. We then seek to optimize the employed waveform and signal processing in regard of the vibration and noise conditions. An original method is proposed that involves maximum likelihood based estimation of the vibration-induced Doppler shift, and its extraction from a time-frequency representation of the signal. The benefits of this approach are shown in simulation and experimentation, by comparing the performance of various emission modes.

This thesis focuses on the analysis of all data sources available for landscape memory interpretation. Amongst those data sources are Lidar, Landsat and orthophoto pictures. According to the analytical outcome the most convenient data source seems to be the Lidar data. Based on their analysis and interpretation an information source for complex land consolidation was elaborated in the form of the forest park proposal.

This master thesis is focused on GPS telemetry of red deer (Cervus elaphus) and sika deer (Cervus nippon) in the Doupov Mts., the Czech republic. Positional data from 14 red deer does and 2 sika deer does was collected during the study period of April 2013 to February 2016. The main aim was to determine habitat preferences of does with the use of the very precise vertical differentiation of vegetation created by air laser scanning of the surface (LiDAR technology). The study examines the dependence of the average maximum height of vegetation nearby positions of does on the time of year and time of day. For the evaluation was used two-way factorial analysis of variance. The highest average height of the vegetation nearby does was found during the day and the lowest during the night. Does of red deer and sika deer occurred in open habitats particularly at night, where they were actively seeking for food and more closed habitats with higher vegetation during the day, where they could hide themselves. Focusing on a period of the year, the height of vegetation in the summer period without hunting was significantly lower than in the summer period with hunting. This could be caused by starting hunting season but also it might be a response to reduced quality of available grass by aging. The two does of sika deer were treated individually. Significant differences were revealed between both does. However they both were occupying habitats with the lowest height of vegetation at night during the rut season. The gained results can now be used to supplement information about ethology of red deer and sika deer. The comprehensive knowledge of ethology can be directly used in the management of these two species, particularly for hunting efficiency and subsequent reduction of their population numbers, particularly in the case of sika deer. However these results can be directly used in forest management in active protection of forest stands against damage by wild game.

This thesis deals with comparsion of digital terrain models from different sources processed in GIS for hydrological purposes. The diploma thesis is composed from several parts. First part sis consist of characteristics related to watershed and water flow, which are important for the understanding this work. The thesis also describes digitial terrain model, his creation and methods for obtainig digitial models. Then, there are described data sources from which is possible to gain digitial models. Next chapter is dedicated to the coordinate system. The last parts of this thesis describes drain alghorithms. Characteristic of this area was collected on experimental watershed Modrava II with the ESRI ArcGIS Desktop software that would mainly Spatial Analyst and ArcHydro extensions. The results of this diploma thesis can be concluded that the free digital terrain model SRTM 90 is not suitable for small regions with diverse terrain structure. Thereason is a small resolution model. Other terrain models provided free of chargé are sufficient even for small areas as the selected area of interest. Paid digitial models can al lbe established for the area of interest as appropriate.

This diploma thesis follows up the influence of horizontal and vertical structure of biotopes on biodiversity of bird species of Czech Republic of forest and open sites. Vertical structure model was created from digital model of surface of Czech Republic (1st generation) and digital model of relief of Czech Republic (5th generation). Information about horizontal structure were derived by analyzing aerial imagery. Then single variables were detected from these data. Subsequently, it was analyzed which of these variables and which way influence bird diversity. On both types of sites was found increasing bird diversity with increasing diversity of vertical structure. With increasing horizontal structure, however, bird diversity significantly increased only on open sites. The influence of other characteristics was mostly different on bird diversity of open and forest sites, but, for both types of sites, the positive influence had for example edge density of land cover categories or edge density of height categories. Additional part of this thesis was to explore if vertical characteristics of biotopes could influence prediction of selected bird species. Results was different in forest and open biotopes, nevertheless in both types of sites was found potential use of both horizontal and vertical variables.

It is essential to measure water depths of rivers, water reservoirs, ponds and lakes from various reasons like hydrologic modeling, monitoring of biotopes, monitoring of sediments or archeologic researches. Hence, the bathymetry techniques for measurements of shallow waters are still evolving. The goal is to find the best method allowing fast and economic mapping of large-scale areas and providing high-resolution data. Currently, the most common method in Czech Republic is probably depth measurement by an ADCP devices, which is a very accurate method, but still time-consuming. On the other hand, airborne laser scanning with wavelength of 532 nm (green laser pulse) has a great potential for shallow water mapping. This work is focused on the possibilities of use of the airborne laser scanning for bathymetry of rivers and water reservoirs in conditions typical for Czech Republic. The methods of obtaining the bathymetric data are discussed in theoretical part, as well as principles of its operation. In the practical part, two study areas (a part of Vltava river and a Hracholusky dam) were scanned using the laser scanner Riegl VQ-880- G. Digital terrain model (DEM) was created from acquired data of the two study areas. After that the DEMs were compared with DEMs which were created from sonar data. The results of comparison are presented. The aim of this work is to assess the ability of airborne laser bathymetry in conditions typical for Czech Republic and verify the accuracy of this method. This method saves time and economic costs and it has great potential to be usable for future research.

This diploma thesis deals with calculation of forest stand heights on the basis of airborne laser scanning (ALS) on the territory of Training Forest Enterprise Křtiny. Point cloud data from ALS were interpolated into digital terrain model (DTM), digital surface model (DSM) and subsequently by subtraction of DTM from DSM into canopy height model (CHM). Inverted CHM was used for detection of tree tops by Inversed Watershed Segmentation; tree tops were identified as local minima. Calculated heights of forest stands were compared with height data taken from Forest Management Plan (FMP) and with data from field survey.

Les mesures de télédétection (MT) dépendent de l'interaction du rayonnement avec les paysages terrestres et l'atmosphère ainsi que des configurations instrumentales (bande spectrale, résolution spatiale, champ de vue: FOV,...) et expérimentales (structure et propriétés optiques du paysage et atmosphère,...). L'évolution rapide des techniques de télédétection requiert des outils appropriés pour valider leurs principes et améliorer l'emploi des MT. Les modèles de transfert radiatif (RTM) simulent des quantités (fonctions de distribution de la réflectance (BRDF) et température (BTDF), forme d'onde LiDAR, etc.) plus ou moins proches des MT. Ils constituent l'outil de référence pour simuler les MT, pour diverses applications : préparation et validation des systèmes d'observation, inversion de MT,... DART (Discrete Anisotropic Radiative Transfer) est reconnu comme le RTM le plus complet et efficace. J'ai encore nettement amélioré son réalisme via les travaux de modélisation indiqués ci-dessous. 1. Discrétisation de l'espace des directions de propagation des rayons. DART simule la propagation des rayons dans les paysages terrestres et l'atmosphère selon des directions discrètes. Les méthodes classiques définissent mal le centroïde et forme des angles solides de ces directions, si bien que le principe de conservation de l'énergie n'est pas vérifié et que l'obtention de résultats précis exige un grand nombre de directions. Pour résoudre ce problème, j'ai conçu une méthode originale qui crée des directions discrètes de formes définies. 2. Simulation d'images de spectroradiomètre avec FOV fini (caméra, pushbroom,...). Les RTMs sont de type "pixel" ou "image". Un modèle "pixel" calcule une quantité unique (BRDF, BTDF) de toute la scène simulée via sa description globale (indice foliaire, fraction d'ombre,...). Un modèle "image" donne une distribution spatiale de quantités (BRDF,...) par projection orthographique des rayons sur un plan image. Tous les RTMs supposent une acquisition monodirectionnelle (FOV nul), ce qui peut être très imprécis. Pour pouvoir simuler des capteurs à FOV fini (caméra, pushbroom,...), j'ai conçu un modèle original de suivi de rayons convergents avec projection perspective. 3. Simulation de données LiDAR. Beaucoup de RTMs simulent le signal LiDAR de manière rapide mais imprécise (paysage très simplifié, pas de diffusions multiples,...) ou de manière précis mais avec de très grands temps de calcul (e.g., modèles Monte-Carlo: MC). DART emploie une méthode "quasi-MC" originale, à la fois précise et rapide, adaptée à toute configuration instrumentale (altitude de la plateforme, attitude du LiDAR, taille de l'empreinte,...). Les acquisitions multi-impulsions LiDAR (satellite, avion, terrestre) sont simulées pour toute configuration (position du LiDAR, trajectoire de la plateforme,...). Elles sont converties dans un format industriel pour être traitées par des logiciels dédiés. Un post-traitement convertit les formes d'onde LiDAR simulées en données LiDAR de comptage de photons. 4. Bruit solaire et fusion de données LiDAR et d'images de spectroradiomètre. DART peut combiner des simulations de LiDAR multi-impulsions et d'image de spectro-radiomètre (capteur hyperspectral,...). C'est une configuration à 2 sources (soleil, laser LiDAR) et 1 capteur (télescope du LiDAR). Les régions mesurées par le LiDAR, dans le plan image du sol, sont segmentées dans l'image du spectro-radiomètre, elle aussi projetée sur le plan image du sol. Deux applications sont présentées : bruit solaire dans le signal LiDAR, et fusion de données LiDAR et d'images de spectro-radiomètre. Des configurations d'acquisition (trajectoire de plateforme, angle de vue par pixel du spectro-radiomètre et par impulsion LiDAR) peuvent être importées pour encore améliorer le réalisme des MT simulées, De plus, j'ai introduit la parallélisation multi-thread, ce qui accélère beaucoup les calculs / Remote Sensing (RS) data depend on radiation interaction in Earth landscapes and atmosphere, and also on instrumental (spectral band, spatial resolution, field of view (FOV),...) and experimental (landscape/atmosphere architecture and optical properties,...) conditions. Fast developments in RS techniques require appropriate tools for validating their working principles and improving RS operational use. Radiative Transfer Models (RTM) simulate quantities (bidirectional reflectance; BRDF, directional brightness temperature: BTDF, LiDAR waveform...) that aim to approximate actual RS data. Hence, they are celebrated tools to simulate RS data for many applications: preparation and validation of RS systems, inversion of RS data... Discrete Anisotropic Radiative Transfer (DART) model is recognized as the most complete and efficient RTM. During my PhD work, I further improved its modeling in terms of accuracy and functionalities through the modeling work mentioned below. 1. Discretizing the space of radiation propagation directions.DART simulates radiation propagation along a finite number of directions in Earth/atmosphere scenes. Classical methods do not define accurately the solid angle centroids and geometric shapes of these directions, which results in non-conservative energy or imprecise modeling if few directions are used. I solved this problem by developing a novel method that creates discrete directions with well-defined shapes. 2. Simulating images of spectroradiometers with finite FOV.Existing RTMs are pixel- or image-level models. Pixel-level models use abstract landscape (scene) description (leaf area index, overall fraction of shadows,...) to calculate quantities (BRDF, BTDF,...) for the whole scene. Image-level models generate scene radiance, BRDF or BTDF images, with orthographic projection of rays that exit the scene onto an image plane. All models neglect the multi-directional acquisition in the sensor finite FOV, which is unrealistic. Hence, I implemented a sensor-level model, called converging tracking and perspective projection (CTPP), to simulate camera and cross-track sensor images, by coupling DART with classical perspective and parallel-perspective projection. 3. Simulating LiDAR data.Many RTMs simulate LiDAR waveform, but results are inaccurate (abstract scene description, account of first-order scattering only...) or require tremendous computation time for obtaining accurate results (e.g., Monte-Carlo (MC) models). With a novel quasi-MC method, DART can provide accurate results with fast processing speed, for any instrumental configuration (platform altitude, LiDAR orientation, footprint size...). It simulates satellite, airborne and terrestrial multi-pulse laser data for realistic configurations (LiDAR position, platform trajectory, scan angle range...). These data can be converted into industrial LiDAR format for being processed by LiDAR processing software. A post-processing method converts LiDAR waveform into photon counting LiDAR data, through modeling single photon detector acquisition. 4. In-flight Fusion of LiDAR and imaging spectroscopy.DART can combine multi-pulse LiDAR and cross-track imaging spectroscopy (hyperspectral sensor...). It is a 2 sources (sun, LiDAR laser) and 1 sensor (LiDAR telescope) system. First, a LiDAR multi-pulse acquisition and a sun-induced spectro-radiometer radiance image are simulated. Then, the LiDAR FOV regions projected onto the ground image plane are segmented in the spectro-radiometer image, which is also projected on the ground image plane. I applied it to simulate solar noise in LiDAR signal, and to the fusion of LiDAR data and spectro-radiometer images. To further improve accuracy when simulating actual LiDAR and spectro-radiometer, DART can also import actual acquisition configuration (platform trajectory, view angle per spectro-radiometer pixel / LiDAR pulse). Moreover, I introduced multi-thread parallelization, which greatly accelerates DART simulations

Multi-spectral imagery provides a robust and low-cost dataset for assessing wetland extent and quality over broad regions and is frequently used for wetland inventories. However in forested wetlands, hydrology is obscured by tree canopy making it difficult to detect with multi-spectral imagery alone. Because of this, classification of forested wetlands often includes greater errors than that of other wetlands types. Elevation and terrain derivatives have been shown to be useful for modelling wetland hydrology. But, few studies have addressed the use of LiDAR intensity data detecting hydrology in forested wetlands. Due the tendency of LiDAR signal to be attenuated by water, this research proposed the fusion of LiDAR intensity data with LiDAR elevation, terrain data, and aerial imagery, for the detection of forested wetland hydrology. We examined the utility of LiDAR intensity data and determined whether the fusion of Lidar derived data with multispectral imagery increased the accuracy of forested wetland classification compared with a classification performed with only multi-spectral image. Four classifications were performed: Classification A - All Imagery, Classification B - All LiDAR, Classification C - LiDAR without Intensity, and Classification D - Fusion of All Data. These classifications were performed using random forest and each resulted in a 3-foot resolution thematic raster of forested upland and forested wetland locations in Vermilion County, Illinois. The accuracies of these classifications were compared using Kappa Coefficient of Agreement. Importance statistics produced within the random forest classifier were evaluated in order to understand the contribution of individual datasets. Classification D, which used the fusion of LiDAR and multi-spectral imagery as input variables, had moderate to strong agreement between reference data and classification results. It was found that Classification A performed using all the LiDAR data and its derivatives (intensity, elevation, slope, aspect, curvatures, and Topographic Wetness Index) was the most accurate classification with Kappa: 78.04%, indicating moderate to strong agreement. However, Classification C, performed with LiDAR derivative without intensity data had less agreement than would be expected by chance, indicating that LiDAR contributed significantly to the accuracy of Classification B.

Lava flows are common at volcanoes around the world and on other terrestrial planets, but their behavior is not fully understood. In Hawai`i, advances in remote sensing are offering new insights into lava flow emplacement. In this dissertation, I develop new techniques using satellite-based synthetic aperature radar, aerial photographs, and airborne lidar to produce three-dimensional high-resolution maps of lava flows from data collected before, during, and after emplacement. These new datasets highlight complex lava channel networks within these flows, which are not incorporated into current predictive or probabilistic lava flow models yet may affect flow behavior. I investigate the origin and influence of these channel networks through morphologic analysis of underlying topography, network topology, and flow morphology and volume. Channel network geometries range from distributary systems dominated by flow branching around local obstacles to tributary systems constricted by topography. I find that flow branching occurs where the flow thins over steeper slopes and that the degree of flow branching, network connectivity, and longevity of flow segments all influence the final flow morphology. Furthermore, because channel networks govern the distribution of lava supply within a flow, changes in the channel topology can dramatically alter the effective volumetric flux in any one branch, which affects both flow length and advance rate. Specifically, branching will slow and shorten flows, while merging can accelerate and lengthen them. To test these observations from historic eruptions and morphologic analysis, I use analogue experiments to simulate the interaction of a lava flow with a topographic obstacle and determine the conditions under which the flow branches and the effects of the bifurcation on flow advance rate. These experiments support the earlier results but also demonstrate the importance of flow dynamics and obstacle morphology on governing when flows may overtop obstacles. Consideration of channel networks is thus important for predicting lava flow behavior and mitigating flow hazards with diversion barriers. One video of Kilauea lava flow activity from 2003-2010 accompanies this dissertation as a supplemental file. This dissertation includes both previously published and unpublished co-authored material.