En aquesta memòria es presenten diversos treballs d’investigació relacionats amb la robòtica mòbil i diverses tècniques de mesura que permeten obtenir informació d’un entorn no estructurat mitjançant l’ús de càmeres i sistemes làser de mesura de distancies. L’ús de sensors permet que un robot mòbil pugui obtenir informació del seu entorn i realitzar una planificació de trajectòria amb l’objectiu d’aconseguir un fi preestablert. En aquesta memòria es presenta un treball que ha permès crear un sistema de mesura extern de la trajectòria d’un robot mòbil. Aquest sistema es pot usar com element extern de verificació de la trajectòria planificada pel propi robot i, aplicada en el cas de robots de neteja del terra, permet estimar el grau de cobertura del terra i obtenir models de la eficàcia del robot de neteja. Actualment, la captura d’informació de l’entorn d’un robot es basa principalment en la utilització de sistemes de mesura làser que actuen com elements palpadors en un pla (làser bidimensional) i en un volum (làser tridimensional). En aquesta memòria es presenten diversos treballs basats en l’anàlisi de la informació aportada per un làser bidimensional per obtenir informació del entorn. Aquest treballs han derivat en aplicacions específiques com la mesura del volum de biomassa d’un conjunt d’arbres, la mesura i determinació de diversos paràmetres originats pel caminar d’una persona i en la detecció simplificada d’obstacles i objectes en una determinada trajectòria. En aquest últim cas, l’estat actual de la tecnologia làser ha permès proposar una nova aplicació del sistema de detecció d’obstacles i objectes com un sistema d’ajuda per persones cegues o amb visió reduïda. Els resultats obtinguts amb les diverses aplicacions proposades han demostrat la utilitat i versatilitat dels sistemes de mesura basats en visió artificial i en mesura de distàncies mitjançant sensors làser. / En esta memoria se presentan diversos trabajos de investigación relacionados con la robótica móvil y con diversas técnicas de medición que permiten obtener información de un entorno no estructurado mediante el uso de cámaras y sistemas láser de medida de distancias. El uso de sensores permite que un robot móvil pueda obtener información de su entorno y realizar una planificación de trayectoria con el objetivo de conseguir un fin preestablecido. En esta memoria se presenta un trabajo que ha permitido crear un sistema de medición externa de la trayectoria de un robot móvil. Este sistema puede utilizarse como elemento externo de verificación de la trayectoria planificada por el propio robot y, aplicado al caso de robots de limpieza del suelo, permite estimar el grado de cobertura del suelo y obtener modelos de la eficacia del robot de limpieza. Actualmente, la captura de información del entorno de un robot se basa principalmente en la utilización de sistemas de medida láser que actúan como elementos palpadores en un plano (láser bidimensional) o en un volumen (láser tridimensional). En esta memoria se presentan diversos trabajos basados en el análisis de la información aportada por un láser bidimensional para obtener información del entorno. Dichos trabajos han derivado en aplicaciones específicas como la medida del volumen de la biomasa de un conjunto de árboles, la medida y determinación de diversos parámetros originados por el andar de una persona y en la detección simplificada de obstáculos y objetos presentes en una determinada trayectoria. En éste último caso, el estado actual de la tecnología láser ha permitido proponer una nueva aplicación del sistema de detección de obstáculos y objetos como sistema de ayuda para personas ciegas o con visión reducida. Los resultados obtenidos en las diversas aplicaciones propuestas han demostrado la utilidad y versatilidad de los sistemas de medida basados la información obtenida de cámaras y de sistemas láser de medida de distancias. / This memory introduces several research works related with robotic mobile and some measurement techniques that obtain information from an unstructured environment using cameras and laser range systems. The use of sensors in a mobile robot allows the acquisition of information of the environment in order to plan a path to execute a specific task. This memory introduces a work that introduces a system to externally estimate the path of a mobile robot. This system can be used to verify the internal path planed by the mobile robot and, in the specific case of floor cleaning mobile robots, to estimate the coverage of the surface and the efficiency of the cleaning robot. Currently, the information of the environment acquired by a mobile robot is based on the usage of laser measurement systems that operates as tactile elements in a plane (laser bidimensional) or in a volume (laser tridimensional). In this memory, several research works based on the analysis of the data provided by a bidimensional laser are presented. These works have evolved into specific applications as the estimate of tree volume biomass, gait parameters registration and analysis, and obstacle and objects detection as an aid system for blind or visual impairment people. The results obtained in the proposed applications have proved the utility and versatility of the new proposed applications based on the analysis of the information provided by cameras and laser distance sensors.

Discharges of warfare bio aerosol clouds are powerful weapons in war and terror situations. A discharge of a small amount of a contagious substance can obliterate large areas. The discharges can usually not be seen with bare eyes, hence some tool needs to be used to find bio aerosol cloud discharges. One way is to use a lidar for the detection of clouds. By sending out a laser pulse into the atmosphere some of the light is scattered back. By measuring the backscattered light, the aerosol structure of the atmosphere can be obtained. If a cloud is hit by the laser beam, an increase of light is observed and the cloud can be detected and tracked.In this thesis a tool for simulating the elastic backscattered light has been developed. A graphical user interface for easier handling has also been developed. For automatic detection of clouds some detection algorithms have been tested. Another graphical user interface for presentation of the simulated lidar signals has also been constructed.The simulator is working well. A lot of different parameters can be changed for the lidar system, the atmosphere and the cloud type. The model works as a helpful tool for specifications of an elastic lidar system to be developed and also as a guide for expected system performance and ways to present the results.

Conventional airborne laser scanner systems output the three-dimensional coordinates of the surface location hit by the laser pulse. Data storage capacity and processing speeds available today has made it possible to digitally sample and store the entire reflected waveform, instead of only extracting the coordinates. Research has shown that return waveforms can give even more detailed insights into the vertical structure of surface objects, surface slope, roughness and reflectivity than the conventional systems. One of the most important advantages with registering the waveforms is that it gives the user the possibility to himself define the way range is calculated in post-processing. In this thesis different techniques have been tested to visualize a waveform data set in order to get a better understanding of the waveforms and how they can be used to improve methods for classification of ground objects. A pulse detection algorithm, using the EM algorithm, has been implemented and tested. The algorithm output position and width of the echo pulses. One of the results of this thesis is that echo pulses reflected by vegetation tend to be wider than those reflected by for example a road. Another result is that up till five echo pulses can be detected compared to two echo pulses that the conventional system detects.

Nowadays, LiDAR(Light Detection And Ranging, LiDAR) is the more important and widely applicable measurement technique. The rise of visual system in 3D is very useful to the measurement of LiDAR and gets more importance value for 3D reconstruction technology, in which abundant surface features are implied in the point cloud data. Combined with the image and laser technique for real-time rendering, the LiDAR will be more functional. This thesis proposes and designs a system which combined with Laser Range Finder and 3D visual interface for vehicles, and also equipped with rotary encoder and initial measurement unit to DR(Dead Reckoning) function. Through the coordinate transform method of 2D to 3D, the 3D coordinate of each point will be calculated, and embedded with the color information which captured from the camera to take 3D color point cloud collection. This method is also called Mobile Mapping System(MMS). In addition, this mapping system uses Direct Memory Access technology to display the point cloud synchronous in 3D visual system. Except for the point cloud collection, the reconstruction of point cloud data is used in this system. The surface reconstruction is based on Nearest Neighbor Interpolation method. There are two factors to conduct the interpolation process: the angle and distance between two sample points from the points sequence. The reconstruction of point cloud and calibration of DR is not only to confirm the accuracy of 3D point cloud map but also the ¡§New Geography¡¨ of the 3D electronic map. This research will build up an independent Mobile Mapping System.

Crown fires, the fastest spreading of all forest fires, can occur in any forest type throughout the United States and the world. The occurrence of crown fires has become increasingly frequent and severe in recent years. The overall aim of this study is to estimate the forest canopy fuel parameters including crown base height (CBH) and crown bulk density (CBD), and to investigate the potential of using airborne lidar data in east Texas. The specific objectives are to: (1) propose allometric estimators of CBD and CBH and compare the results of using those estimators to those produced by the CrownMass/FMAPlus software at tree and stand levels for 50 loblolly pine plots in eastern Texas, (2) develop a methodology for using airborne light detection and ranging (lidar) to estimate CBD and CBH canopy fuel parameters and to simulate fire behavior using estimated forest canopy parameters as FARSITE inputs, and (3) investigate the use of spaceborne ICEsat /GLAS (Ice, Cloud, and Land Elevation Satellite/Geoscience Laser Altimeter System) lidar for estimating canopy fuel parameters. According to our results from the first study, the calculated average CBD values, across all 50 plots, were 0.18 kg/m³ and 0.07 kg/m³, respectively, for the allometric equation proposed herein and the CrownMass program. Lorey’s mean height approach was used in this study to calculate CBH at plot level. The average height values of CBH obtained from Lorey’s height approach was 10.6 m and from the CrownMass program was 9.1 m. The results obtained for the two methods are relatively close to each other; with the estimate of CBH being 1.16 times larger than the CrownMass value. According to the results from the second study, the CBD and CBH were successfully predicted using airborne lidar data with R² values of 0.748 and 0.976, respectively. The third study demonstrated that canopy fuel parameters can be successfully estimated using GLAS waveform data; an R² value of 0.84 was obtained. With these approaches, we are providing practical methods for quantifying these parameters and making them directly available to fire managers. The accuracy of these parameters is very important for realistic predictions of wildfire initiation and growth.

Population growth and urban sprawl have contributed to the formation of significant urban heat island phenomena in Houston, Texas, the fourth largest city in the United States. The population growth in Houston was 25.8% between 1990 and 2000 nearly double the national average. The demand for information concerning the effects of urban and suburban development is growing. Houston is currently the only major US city lacking any kind of comprehensive city zoning ordinances. The Normalized Difference Vegetation Index (NDVI) has been used as a surrogate variable to estimate land surface temperatures at higher spatial resolutions, given the fact that a high-resolution remotely sensed NDVI can be created almost effortlessly and remotely sensed thermal data at higher resolutions is much more difficult to obtain. This has allowed researchers to study urban heat island dynamics at a micro-scale. However, this study suggests that a vegetation index alone might not be the best surrogate variable for providing information regarding the independent effects and level of contribution that tree canopy, grass, and low-lying plants have on surface temperatures in residential neighborhoods. This research combines LIDAR (Light Detection and Ranging) feature height data and high-resolution infrared aerial photos to measure the characteristics of the micro-structure of residential areas (residentialstructure), derives various descriptive vegetation measurement statistics, and correlates the spatial distribution of surface temperature to the type and amount of vegetation cover in residential areas. Regression analysis is used to quantify the independent influence that different residential-structures have on surface temperature. In regard to implementing changes at a neighborhood level, the descriptive statistics derived for residential-structure at a micro-scale may provide useful information to decision-makers and may reveal a guide for future developers concerned with mitigating the negative effects of urban heat island phenomena.

Microwave scattering from sea ice ridges is poorly understood. This thesis aims to improve the current knowledge on in situ C-band microwave scattering from first-year sea ice (FYI) pressure ridges during winter, and how C-band backscatter can vary with changes to radar and target parameters. Remotely sensed data of ridged ice were collected at a sea ice mesocosm using a LiDAR laser scanner and a fully-polarimetric C-band scatterometer. Thesis results indicate that using an incidence angle between 30 and 50° and HV polarization will best enable distinguishing between smooth and ridged ice, while using an incidence angle of 40° and HV or HH polarization will best enable detecting variations in ridge height. Overall results indicate that a significant proportion of the variance in FYI snow-free ridge C-band backscatter can be explained by incidence angle, polarization, and ridge height, with almost 88% of the variability in backscatter attributed to ridge height.

Traffic signs, which transportation agencies must inventory and manage, are one of the most important roadway assets because they are used to ensure roadway safety and provide important travel guidance/information. Traffic sign inventory and condition assessment are two important components that are essential for establishing a cost-effective and sustainable traffic sign management system. Traditionally, state departments of transportation (DOTs) have conducted traffic sign inventory and condition assessment manually, a process that is labor-intensive, time-consuming, and sometimes hazardous to field engineers in the roadway environment. Methods have been developed to automate sign inventory and condition assessment using video log images in previous studies. However, the performance of these methods still needs to be improved. Based on the need to inventory signs and manage them more effectively, this study has two focuses. The first focus is to develop an enhanced traffic sign detection methodology to improve the productivity of an image-based sign inventory for state DOTs. The proposed methodology includes two enhanced algorithms: a) a lighting dependent statistical color model (LD-SCM)-based color segmentation algorithm that is robust to different image lighting conditions, especially adverse lighting and b) an ordinary/partial differential equation (ODE/PDE)-based shape detection algorithm that is immune to discontinuous sign boundaries in a cluttered background. The second focus of the study is to explore a new traffic sign retroreflectivity condition assessment methodology to develop a mobile method that uses emerging computer vision and mobile light detection and ranging (LiDAR) technologies to assess traffic sign retroreflectivity conditions. The proposed methodology includes a) an image-LiDAR registration method employing camera calibration and point co-planarity to register the 3D LiDAR point cloud with 2D video log images, b) a theoretical-empirical normalization scheme to adjust the magnitude of the LiDAR retro-intensity values with respect to LiDAR beam distance and incidence angle based on the radiometric responses, and c) a population-based retroreflectivity condition assessment method to evaluate the adequacy of a traffic sign retroreflectivity condition based on the correlation between the normalized LiDAR retro-intensity and the retroreflectivity values. For the proposed traffic sign detection methodology, comprehensive tests using representative datasets (e.g. with different road functions, data collection sources, and data qualities) were conducted to validate the performance of the two enhanced algorithms and the complete methodology. For the proposed retroreflectivity condition assessment methodology, the fundamental behavior of LiDAR retro-intensity was comprehensively tested and simulated under a controlled lab and roadway environment to quantify the impact of beam distance and incidence angle. A preliminary test on Type 1 engineer grade stop signs was conducted in the field to validate the performance of the proposed sign retroreflectivity condition assessment method. The results from both of the proposed methodologies are promising.

Terrain attributes computed from Digital Elevation Models (DEMs) are widely used in hydrology and hydrologic modeling. It is important to consider that the values of the attributes can be different depending on the resolution of the DEM from which they are derived. The question arises as to how much exactly the high-resolution DEMs created through LIDAR remote sensing techniques change the values of the terrain attributes when compared to lower resolution DEMs.In this thesis a LIDAR-derived DEM of 20 feet resolution was resampled using a nearest-neighbour algorithm to various coarser resolutions to examine and quantify the effect of DEM resolution upon a series of hydrologically significant terrain attributes including slope, surface curvature, topographic wetness index, stream power index and stream networks. Values for slope and surface curvature are found to be smaller when computed from lower resolution DEMs; values for the topographic wetness index and stream power index are found to increase as DEM cell size increases.The derived stream networks for each resolution were compared in terms of length per stream order, drainage density, bifurcation ratio, and overall accuracy indicating a loss of small detail, but only a modest change in the overall stream network morphometry. This research suggests that it is possible to establish relationships that quantify the effects of DEM resolution upon hydrologically significant terrain attributes, which can then be considered when processing DEMs from various resolutions for the purpose of parameterizing hydrologic models.

ITC/USA 2014 Conference Proceedings / The Fiftieth Annual International Telemetering Conference and Technical Exhibition / October 20-23, 2014 / Town and Country Resort & Convention Center, San Diego, CA / Massive amounts of data are typically acquired in third generation full-waveform (FW) LIDAR systems to generate image-like depthmaps of a scene of acceptable quality. The sampling systems acquiring this data, however, seldom take into account the low information rate generally present in the FW signals and, consequently, they sample very inefficiently. Our main goal here is to compare two efficient sampling models and processes for the individual time-resolved FW signals collected by a LIDAR system. Specifically, we compare two approaches of sub-Nyquist sampling of the continuous-time LIDAR FW return pulses: (i) modeling FW signals as short-duration pulses with multiple bandlimited echoes, and (ii) modeling them as signals with finite rates of innovation (FRI).