As utilizações de dados altimétricos, nesse estudo analisados a partir de modelos digitais de terreno (MDT), são as mais variadas assim como as técnicas de obtenção desse tipo de dado. Pode-se obter MDT por radar de abertura sintética que é utilizado para o levantamento de grandes áreas e de difícil acesso. Também pode-se gerar esse tipo de dado por Fotogrametria, por Topografia utilizando estação total com apoio GNSS (Global Navigation Satellite System). Uma tecnologia mais atual para a obtenção de dados altimétricos é a utilização de tecnologia Lidar (light detection and ranging) que consiste na medição de distância e coordenadas através de um pulso eletromagnético que interage com os alvos. O produto básico dos sistemas que utilizam a tecnologia Lidar, seja em plataformas aéreas ou terrestres, é denominado de nuvem de pontos. Essas nuvens de pontos possuem coordenadas tridimensionais (X, Y e Z) referenciadas ao centro de fase do sensor. Nesse estudo foram realizados experimentos com dois sistemas de varredura a laser terrestre. O primeiro é um sistema de varredura modelo Optech Ilris 3D e outro Faro Focus 3D, nesse estudo denominados de SVLT Optech e SVLT Faro. Assim, o objetivo desse trabalho é estimar a qualidade posicional dos dados altimétricos gerados por dois SVLT. Os estudos foram executados em dois experimentos. No primeiro experimento foram realizados escaneamentos num campo de calibração. Nessa etapa foi gerada uma nuvem de pontos de cada sistema de varredura, e esses dados foram georreferenciados e a partir de pontos de checagem medidos no mesmo e assim foi estimada o controle de qualidade posicional. No segundo experimento, os dois SVLT foram utilizados para efetuar um levantamento topográfico planialtimétrico em um percurso de aproximadamente um quilômetro. Os dados gerados pelos SVLT passaram por um processo de registro, que consiste na junção de pares de nuvens de pontos, e foram georreferenciados a partir de pontos de controle medidos no terreno. Nesse percurso foram realizados circuitos de nivelamento cujos vértices foram utilizados para se estimar o controle de qualidade posicional, planimétrico e altimétrico, das nuvens de pontos oriundas dos dois sistemas de varredura. Assim, após a realização de testes estatísticos, no primeiro experimento, obteve-se valores de acurácia altimétrica de 1,5 cm para o SVLT Faro e de 1,3cm para o SVLT Optech e no segundo experimento acurácia altimétrica de 1,9 cm para o SVLT Faro e de 5,9 cm para o SVLT Optech. / The uses of altimetric data, in this study approached from digital terrain models (TDM) are the most varied as well as the techniques for getting this type of data. It can be get DTM by synthetic aperture radar that is used for surveying wide areas and with difficult access. As well it can be this type of data by Photogrammetry, by conventional Topography using total station with GNSS (Global Navigation Satellite System) support. A more actual technology for obtaining altimetric data is the use of light detection and ranging technology, which consists of measuring distance and coordinates through an electromagnetic pulse that interacts with the targets. The basic product of the systems that use the technology lidar, be it in aerial or terrestrial platforms, is denominated a point cloud. These point clouds have three-dimensional coordinates (X, Y, and Z) referenced to phase center of the sensor. In this study, will be performed experiments with two systems of terrestrial laser scanning (STLS). One STLS of the brand Optech Ilris 3D and another of the brand Faro Focus 3D, in this study called of STLS Faro and STLS Optech. Therefore, the aim of this work is to estimate the positional quality of digital terrain models generated by these two STLS. The studies were executed in two experiments. In the first experiment, scans has been made on a calibration wall. The generated point clouds were georeferenced and from the checkpoints measured in this calibration wall, the positional quality of these data was estimated. In the second experiment, the two STLS were has been made a planialtimetric topographic survey of a course of approximately one kilometer. In this course a leveling network was created and the vertices of this network were used to estimate the positional quality control of the points clouds from the two STLS. Therefore, after realization statistical tests, in the first experiment, it was obtained altimetric accuracy values of 1.5 cm for the STLS Faro and 1.3 cm for the STLS Optech were obtained and in the second experiment, the altimeter accuracy of 1.9 cm for the STLS Faro and 5.9 cm for the Optech STLS.

Interferometric Synthetic Aperture Radar (InSAR) is an established technique which has been applied to Earth surface displacement analysis and topographic reconstruction. Two complex coherent SAR acquisitions of the same scene are combined to form an interferogram from which surface displacement or terrain measurements are made. The similarities between both SAR signals is captured in the coherence and its magnitude is determined by the spatial separation between acquiring antennas and the changes (if any) to the physical characteristics of the scattering target in the duration between both SAR acquisitions. Both of these products derivable from the interferometric process have been applied in this study with the aim of enhancing monitoring and assessing changes in the coastal environment, with emphasis on the coastal geomorphology. A combination of remote sensing data acquired for Montrose Bay, NE Scotland, has been used to analyze changes to the geomorphology of the beach and dune system in terms of sediment volume analysis, erosion and accretion processes and shoreline changes over a short-term period of 4 years. The interferometric coherence was applied to detect changes to the dune morphology, which have been actively eroding at the southern flank of the Bay. The interferometric analysis presented in this thesis was based on SAR data acquired by the Sentinel-1 SAR antenna and the results demonstrated the limitations of the sensor for terrain mapping and DEM reconstruction. In addition, the significance of the vegetation on the interferometric coherence was demonstrated. However, the results have shown that temporal baseline remained a significant consideration in the application of interferometric coherence in highly dynamic environments such as the coastal environment.

The purpose of this study is comparing elevation models from Terrestrial laser scanner (TLS) and Unmanned aerial system (UAS) photogrammetry focusing on detecting microtopography and the relationship between elevation differences and image textures. The soils on agricultural lands are permanently modified by intensive farming activities almost every year. The microtopography of the soil, that plays an important role in the surface runoff and infiltration, depends on cultivation practices and the field environment. By way of example: crop residues, furrows, tillage direction, and slope may impact the soil nutrient and erosion. To better understand and prevent soil degradation via erosion, 3-D reconstructions of high-resolution soil monitoring are required. In this study, we try to circumnavigate the soil roughness associated with sustainable practices and physical characteristics of fields by collecting soil datasets from non-contacted remote sensing platforms. The amount of soil roughness was observed environmental conditions derived from the Terrestrial Laser Scanner (TLS) and the Unmanned Aerial System (UAS) photogrammetry within harvested fields in Eastern Central Iowa. Additionally, by focusing on local relief detections and the relationship between outlier distributions and image textures, the two datasets were compared. Both TLS and UAS derived point clouds successfully reconstructed digital elevation models ~ 5cm RMSE after the registration and merge process, and these models showed local reliefs of study areas with fine details. However, several outlier cluster points were detected in the comparisons between TLS and UAS derived DEMs. To discover the outlier distributions, image texture was addressed with global and local block analysis. Since there were no significant correlations, most of the study sites show that poor texture of ground may trigger high elevation errors. To enhance the texture of images, several possible solutions are described, such as local contrast enhancement using the Wallis filter.

Currently the Iowa Flood Center (IFC) of the University of Iowa is working in conjunction with the Iowa Department of Natural Resources (IDNR) to create statewide floodplain maps. The IFC has set up a four year plan to construct flood inundation maps for 85 of the 99 counties within the state of Iowa, with the final goal of creating maps acceptable by FEMA. High resolution statewide LiDAR information provides a base dataset from which floodplain maps are produced. Stream centerline data is extracted from a DEM produced by the LiDAR dataset. The centerline information is used in both this project and as a replacement for the USGS NHD streamline for the state. Stream flow estimation for a range of annual exceedance discharges are produced through a USGS recommended combination of regional regression analysis weighted by gage influence. Water surface elevations are produced for each of the annual exceedance discharges through the use of a HEC-RAS one dimensional steady flow model. Flood boundaries are the final product created by HEC-GeoRAS though a comparison of a TIN produced from the water surface elevations and the ground surface DEM. Final FEMA acceptable DFIRM's are produce by the IDNR and submitted to FEMA for adoption into the NFIP.

Stream flowline delineation from high-resolution digital elevation models (HRDEMs) can be problematic due to the fine representation of terrain features as well as anthropogenic drainage structures (e.g., bridges, culverts) within the grid surface. The anthropogenic drainage structures (ADS) may create digital dams while delineating stream flowlines from HRDEMs. The study assessed the effects of ADS locations, spatial resolution (ranged from 1m to 10m), depression processing methods, and flow direction algorithms (D8, D-Infinity, and MFD-md) on hydrologic connectivity through digital dams using HRDEMs in Nebraska. The assessment was conducted based on the offset distances between modeled stream flowlines and original ADS locations using kernel density estimation (KDE) and calculated frequency of ADS samples within offset distances. Three major depression processing techniques (i.e., depression filling, stream breaching, and stream burning) were considered for this study. Finally, an automated method, constrained burning was proposed for HRDEMs which utilizes ancillary datasets to create underneath stream crossings at possible ADS locations and perform DEM reconditioning. The results suggest that coarser resolution DEMs with depression filling and breaching can produce better hydrologic connectivity through ADS compared with finer resolution DEMs with different flow direction algorithms. It was also found that stream burning with known stream crossings at ADS locations outperformed depression filling and breaching techniques for HRDEMs in terms of hydrologic connectivity. The flow direction algorithms combining with depression filling and breaching techniques do not have significant effects on the hydrologic connectivity of modeled stream flowlines. However, for stream burning methods, D8 was found as the best performing flow direction algorithm in HRDEMs with statistical significance. The stream flowlines delineated using the proposed constrained burning method from the HRDEM was found better than depression filling and breaching techniques. This method has an overall accuracy of 78.82% in detecting possible ADS locations within the study area.

Current karst hazard maps in Kentucky reflect the general lithology of the state and ignore or significantly reduce the impact of the actual sinkholes present within these areas. These maps rely on equal weighting, by area, of the Karst Potential Index (KPI) map and the sinkhole inventory map. The KPI is based on a 1:500,000 geologic map and less than 500 data points of carbonate rocks. The sinkhole inventory is derived from topographic maps updated in the 1970s with approximately 10-foot resolution. This method gives a preferential weighting of the KPI over the sinkhole data. Consequently, the current method is broad in scope and ineffective in hazard assessment. There is a need for a reliable karst hazard map for land use planners, government emergency planning agencies, and other stakeholders. In this study, more detailed geology information and LiDAR (Light Detection and Ranging) data are applied to three counties (Bullitt, Logan, and Woodford) to generate a more accurate assessment of karst hazard. An assessment method based on sinkhole density is also tested. By refining the hazard score to more precise areas of concern, future stakeholders will find this data useful in emergency planning and land assessment.

Autonomous Vehicle are coming. But mass adoption is at least ten years away according to consensus compiled from interviews conducted with industry thought lenders. Questions remain as to what technology those vehicles will contain as there is no universal platform for autonomous vehicle technology, since manufacturers, hardware and software companies are developing their own proprietary products. A/V technology is expected to improve productivity, and provide a plethora of societal benefits, but while we await the closure of the time gap the US will lose almost 40,000 citizens each year with traffic fatalities. Connected vehicle technology, which is currently completing pilot studies, has been shown to reduce automobile accidents. This technology is not as complex as autonomous vehicle technology and is available now. Semi-autonomous vehicles which is Level 1 through Level 3 on the Society of Automobile Executives (SAE) scale is available on American automobiles today and has proven to be very popular amongst consumers. Technology convergence of semi-autonomous vehicle and connected vehicles can bridge the time gap until mass adoption of autonomous vehicle and contribute to reducing annual traffic fatalities. Combining these technologies will give drivers additional safety features thus providing them with the opportunity of making better decisions.

Methods used to process raw Light Detection and Ranging (LiDAR) data can sometimes obscure the digital signatures indicative of an archaeological site. This thesis explains the negative effects that certain LiDAR data processing procedures can have on the preservation of an archaeological site. This thesis also presents methods for effectively integrating LiDAR with other forms of mapping data in a Geographic Information Systems (GIS) environment in order to improve LiDAR archaeological signatures by examining several pre-Columbian Native American shell middens located in Canaveral National Seashore Park (CANA).

Enhanced understanding of forest stocks and dynamics can be gained through improved forest measurement, which is required to assist with sustainable forest management decisions, meet Australian and international reporting needs, and improve research efforts to better respond to a changing climate. Integrated sampling schemes that utilise a multi-scale approach, with a range of data sourced from both field and remote sensing, have been identified as a way to generate the required forest information. Given the multi-scale approach proposed by these schemes, it is important to understand how scale potentially affects the interpretation and reporting of forest from a range of data. ¶ To provide improved forest assessment at a range of scales, this research has developed a strategy for facilitating tree and stand level retrieval of structural attributes within an integrated multi-scale analysis framework. The research investigated the use of fine-scale (~1m) airborne Light Detection and Ranging (LiDAR) data (1,125 ha in central Queensland, and 60,000 ha in NE Victoria) to calibrate other remotely sensed data at the two study sites. The strategy refines forest structure mapping through three-dimensional (3D) modelling combined with empirical relationships, allowing improved estimation of maximum and predominant height, as well as foliage and crown cover at multiple scales. Tree stems (including those in the sub-canopy) were located using a height scaled crown openness index (HSCOI), which integrated the 3D density of canopy elements within the vertical profile into a two-dimensional spatial layer. The HSCOI modelling also facilitated the reconstruction of the 3D distribution of foliage and branches (of varying size and orientation) within the forest volume. ¶ Comparisons between forests at the Queensland and NE Victorian study sites indicated that accurate and consistent retrieval of cover and height metrics could be achieved at multiple scales, with the algorithms applicable for semi-automated use in other forests with similar structure. This information has facilitated interpretation and evaluation of Landsat imagery and ICESat satellite laser data for forest height and canopy cover retrieval. The development of a forest cover translation matrix allows a range of data and metrics to be compared at the plot scale, and has initiated the development of continuous transfer functions between the metrics and datasets. These data have been used subsequently to support interpretation of SAR data, by providing valuable input to 2D and 3D radar simulation models. Scale effects have been identified as being significant enough to influence national forest class reporting in more heterogeneous forests, thus allowing the most appropriate use and integration of remote sensed data at a range of scales. An empirically based forest minimum mapping area of 1 ha for reporting is suggested. The research has concluded that LiDAR can provide calibration information just as detailed and possibly more accurately than field measurements for many required forest attributes. Therefore the use of LiDAR data offers a unique opportunity to bridge the gap between accurate field plot structural information and stand to landscape scale sampling, to provide enhanced forest assessment in Australia.

Le GPS est la technique de positionnement global la plus utilisée ; sa précision planimétrique en mode géodésique atteint le niveau millimétrique. Cependant, une limite importante réside dans la détermination de la composante verticale (3-15~mm pour des sessions de 24~h) dont l'estimation est dégradée par la perturbation de la propagation des signaux lors de la traversée de la troposphère.<br />L'action NIGPS, menée en collaboration par l'IGN et le SA (CNRS), vise à développer une correction de ces effets atmosphériques basée sur le sondage de l'humidité à l'aide d'un lidar Raman vapeur d'eau à visée multi-angulaire. Ce travail de thèse s'inscrit dans la continuité des travaux présentés en 2005 par Jérôme Tarniewicz et consiste à poursuivre l'étude méthodologique, les développements instrumentaux et la validation expérimentale de l'analyse conjointe des observations GPS et lidar.<br />Après l'étude à partir de simulations numériques de l'effet de la troposphère sur le GPS et de sa correction, nous nous intéressons à la restitution précise de mesures de vapeur d'eau par lidar Raman. Les données acquises lors de la campagne VAPIC permettent de vérifier l'impact de la troposphère sur le GPS. La comparaison des observations lidar à celles issues d'autres instruments permet de valider la mesure lidar et souligne la capacité de cette technique à restituer des variations rapides de vapeur d'eau. Une première évaluation de la correction des observations GPS par des mesures lidar au zénith est réalisée sur des sessions GPS de 6 h et montre l'apport de cette technique sur les cas considérés. Ces résultats devraient cependant être améliorés grâce la prise en compte de visées lidar obliques.