A utilização do sistema LiDAR na obtenção de dados da superfície da Terra vem se disseminando cada vez mais pelo alto desempenho na aquisição da informação e pela efetiva utilização dos produtos e subprodutos. Diversos segmentos passaram a adotar os produtos LiDAR como insumo básico e fundamental em suas rotinas de trabalho e estudos. O sucesso em um projeto que envolve aquisição e utilização desse tipo de dado está atrelado diretamente à definição e seu planejamento. O usuário deve ser capaz de definir o escopo básico e as diretrizes técnicas fundamentais que irão garantir que a demanda final seja alcançada. Diante disto se faz necessário elaborar um planejamento estabelecendo a melhor configuração para a aquisição dos dados e também os tipos de informações que serão extraídas destes produtos. Referente ao primeiro aspecto pode-se dizer que este é a base para a todo o projeto. Por meio dele é garantido a obtenção de produtos conforme a necessidade do usuário (resoluções espaciais dos produtos, o nível de detalhamento dos objetos, representação da topografia e outros). Muitos dos usuários que contratam serviços de perfilamento LiDAR não possuem embasamento técnico suficiente para definir a melhor especificação a ser adotada. Isto faz com que a maioria deles opte por adquirir uma alta densidade de pontos que, muitas vezes é desnecessária e ainda que atendam à demanda final tornam o projeto financeiramente oneroso. Esta pesquisa mostra que para um ambiente urbano regular, nuvens de pontos com baixas densidades (4 pts/m² e 8 pts/m²) apresentam uma equivalência na qualidade geométrica para produtos e subprodutos obtidos que serão utilizados para determinadas aplicações, não havendo a necessidade de utilizar nuvens com uma alta densidade (16 pts/m²) em projetos que utilizam estes dados em estudos altimétricos: geração do Modelo Digital de Terreno, curvas de nível, pontos cotados e também planimétricos: Modelo Digital de Elevação (Superfície e Normalizada) e seus derivados (altura e contorno de objetos, imagem de intensidade, cobertura vegetal e outros). / The use of the LiDAR system in obtaining data from the Earth\'s surface has been increasingly disseminated by the high performance in the acquisition of information and the effective use of products and by-products. Several segments started to adopt LiDAR products as basic and fundamental input in their works and studies. Success in a project that involves the acquisition and use of this type of data is directly linked to the definition and its planning. The user must be able to define the basic scope and the fundamental technical guidelines that will guarantee that the final demand is reached . In view of this, it is necessary to prepare a planning establishing the best configuration for the data acquisition and also the types of information that will be extracted from these products. Regarding the first aspect can be said that this is the basis for the whole project. Through it is guaranteed to obtain products according to the user is needs (spatial resolutions of the products, the level of detail of the objects, representation of the topography and others). Many of the users who hire LiDAR profiling services do not have sufficient technical background to define the best specification to adopt. This makes the majority of them choose to acquire a high density of points that is often unnecessary and even if they meet the final demand make the project financially costly. This research shows that for a regular urban environment, low point density clouds (4 pts/m² and 8 pts/m²) present an equivalence in the geometric quality for products and by-products obtained that will be used for certain applications. The need to use clouds with a high density (16 pts/m²) in projects that use this data in altimetric studies: generation of Digital Terrain Model, contourlines, quoted points and also planimetric: Digital Elevation Model (Surface and Normalized) and its derivatives (height and contour of objects, intensity image, vegetation cover and others).

A utilização do sistema LiDAR na obtenção de dados da superfície da Terra vem se disseminando cada vez mais pelo alto desempenho na aquisição da informação e pela efetiva utilização dos produtos e subprodutos. Diversos segmentos passaram a adotar os produtos LiDAR como insumo básico e fundamental em suas rotinas de trabalho e estudos. O sucesso em um projeto que envolve aquisição e utilização desse tipo de dado está atrelado diretamente à definição e seu planejamento. O usuário deve ser capaz de definir o escopo básico e as diretrizes técnicas fundamentais que irão garantir que a demanda final seja alcançada. Diante disto se faz necessário elaborar um planejamento estabelecendo a melhor configuração para a aquisição dos dados e também os tipos de informações que serão extraídas destes produtos. Referente ao primeiro aspecto pode-se dizer que este é a base para a todo o projeto. Por meio dele é garantido a obtenção de produtos conforme a necessidade do usuário (resoluções espaciais dos produtos, o nível de detalhamento dos objetos, representação da topografia e outros). Muitos dos usuários que contratam serviços de perfilamento LiDAR não possuem embasamento técnico suficiente para definir a melhor especificação a ser adotada. Isto faz com que a maioria deles opte por adquirir uma alta densidade de pontos que, muitas vezes é desnecessária e ainda que atendam à demanda final tornam o projeto financeiramente oneroso. Esta pesquisa mostra que para um ambiente urbano regular, nuvens de pontos com baixas densidades (4 pts/m² e 8 pts/m²) apresentam uma equivalência na qualidade geométrica para produtos e subprodutos obtidos que serão utilizados para determinadas aplicações, não havendo a necessidade de utilizar nuvens com uma alta densidade (16 pts/m²) em projetos que utilizam estes dados em estudos altimétricos: geração do Modelo Digital de Terreno, curvas de nível, pontos cotados e também planimétricos: Modelo Digital de Elevação (Superfície e Normalizada) e seus derivados (altura e contorno de objetos, imagem de intensidade, cobertura vegetal e outros). / The use of the LiDAR system in obtaining data from the Earth\'s surface has been increasingly disseminated by the high performance in the acquisition of information and the effective use of products and by-products. Several segments started to adopt LiDAR products as basic and fundamental input in their works and studies. Success in a project that involves the acquisition and use of this type of data is directly linked to the definition and its planning. The user must be able to define the basic scope and the fundamental technical guidelines that will guarantee that the final demand is reached . In view of this, it is necessary to prepare a planning establishing the best configuration for the data acquisition and also the types of information that will be extracted from these products. Regarding the first aspect can be said that this is the basis for the whole project. Through it is guaranteed to obtain products according to the user is needs (spatial resolutions of the products, the level of detail of the objects, representation of the topography and others). Many of the users who hire LiDAR profiling services do not have sufficient technical background to define the best specification to adopt. This makes the majority of them choose to acquire a high density of points that is often unnecessary and even if they meet the final demand make the project financially costly. This research shows that for a regular urban environment, low point density clouds (4 pts/m² and 8 pts/m²) present an equivalence in the geometric quality for products and by-products obtained that will be used for certain applications. The need to use clouds with a high density (16 pts/m²) in projects that use this data in altimetric studies: generation of Digital Terrain Model, contourlines, quoted points and also planimetric: Digital Elevation Model (Surface and Normalized) and its derivatives (height and contour of objects, intensity image, vegetation cover and others).

Utförande av kontroller av olika objekt i byggskedet är av stor betydelse för att undvika onödiga kostnader och förseningar. Betonggolv är en typ av objekt som har toleranskrav avseende lutning och buktighet. I Sverige gäller det svenska referensverket AMA-Hus, där anges toleranser för lutning och buktighet. Buktighet kontrolleras för två olika diametrar på 0,25 m respektive 2 m, i den här studien benämnda som lokal och global buktighet.Avsikten med studien var att identifiera det optimala tillvägagånssättet att kontrollera lutning och buktighet av en horisontell yta samt infallsvinkelns påverkan vid reflektorlösa mätningar. Rutnätsskanning med olika punktavstånd utförd med multistation och laserskanning från multistation och laserskanner har använts för att samla in data. Före mätning placerades konstgjorda upphöjda buktningar ut på golvet. Data från mätningarna interpolerades i Surfer-mjukvara, där kartor med höjdkurvor skapades. Interpolationsmetoden som användes var Kriging. Även ett program för objektiv kontroll av buktighet utvecklades i samarbete med en civilingenjör i datateknik.Vid analys konstaterades det att rutnätsskanningarna med punktavstånden över 12,5 cm ej anses lämpliga för kontroll av buktighet. Rutnätsskanningen med punktavstånd på 12,5 cm eller tätare kan inte heller anses optimal för kontroll av buktighet då tidsåtgången blir för omfattande. Laserskanning med multistationen är det tillvägagångsätt som utifrån resultatet i denna studie, baserat på kontrollbarhet av buktighet och lutning, ger tydligast resultat i förhållande till tidsåtgång.Högre infallsvinkel från mätningar längre bort från instrumentet visade ingen systematisk inverkan på mätningarna i denna studie. Den ökade punkttätheten som påvisats nära instrumentet orsakade något som tolkats som brus i punktmolnet och förhöjd tidsåtgång för utförande av mätningar. / Performing controls of different types of objects in the construction phase of buildings are of great importance to avoid unnecessary costs and delays. Concrete floors are one type of object that has defined tolerances regarding levelness and flatness. In Sweden, the tolerance for levelness and flatness can be found in the national guideline AMA-Hus. Flatness is controlled within two different diameters of 0.25 m and 2 m respectively, in this study referred to as local and global flatness.The aim of this study was to identify the optimal method to control levelness and flatness of a horizontal surface and to determine the effect from the angle of incidence using reflectorless measurements. Grid scanning with different point density performed with a multi station and laser scans from multi station and laser scanner were used to collect the data. Before measurements artificial elevated curvatures where placed on the concrete floor. Data from the measurements where interpolated in Surfer software, and height maps were created. The interpolation method used was Kriging. Software containing an algorithm for objective flatness detection was developed in cooperation with a civil engineer in computer science.Analysis of the grid scanning data revealed that point density over 12.5 cm is not sufficient to detect significant elevation differences when controlling flatness. Grid scanning at 12.5 cm or thicker also cannot be deemed optimal since the time required to perform the measurements are disproportionately long. Laser scanning using the multi station proved, in the conditions of this study, to be the optimal method for levelness and flatness control in respect to time consumption.Steeper angle of incidence from measurements further from the instrument showed no systematical deviations of the measurements in this study. However, the increased point density found close to the instrument caused something that could be considered as noise in the point cloud as well as increased time consumption.

Höjddata av god kvalitet är av stor betydelse i många sammanhang, inte minst i samhällets anpassning till ett förändrat klimat. Laserdata Skog är höjddata insamlade från flygburen laserskanning och kommer i färdigt skick att täcka större delen av Sveriges yta. För att sådana data ska kunna användas på bästa sätt är det viktigt att ha kännedom om deras kvalitet. För data från flygburen laserskanning finns det många parametrar som orsakar variation i kvaliteten, där terrängtypens inverkan hör till de mest betydande.  Denna studie utförs på uppdrag av Lantmäteriet och syftar till att undersöka kvaliteten i Laserdata Skog. Fokus ligger på osäkerhet i höjd och punkttäthet, samt hur dessa faktorer varierar mellan olika terrängtyper. Höjdosäkerheten har undersökts genom jämförelser mellan laserdata och terrestra kontrollmätningar, medan punkttätheten har bestämts med beräkningar och observationer i laserdata. Fyra terrängtyper ingår i studien: Hårdgjord yta, Gräsyta, Barrskog och Lövskog. Varje terrängtyp representeras av tre olika provytor, fördelade på olika skanningsområden. Osäkerheten i höjd påverkades av både trädskikt och markvegetation, medan det enbart var variation i trädskiktet som orsakade synbar påverkan på punkttätheten. Osäkerheten i höjd för enskilda provytor varierade mellan 0,011 och 0,183 m (RMS). Punkttätheten varierade mellan 0,66 och 2,09 punkter/m2. För osäkerheten i höjd påträffades ett betydande bidrag från inpassningen av punktmolnet, vilket försvårade analysen av terrängtypens inverkan. / High quality elevation data is of great importance in many contexts, for example in society’s adaptation to climate change. Laser data forest (Laserdata Skog) is elevation data collected from airborne laserscanning, and will cover most of Sweden’s surface when completed. In order for this data to be used in the best possible way, knowledge of its quality is important. Many parameters causes variation in quality for airborne laserdata, and the impact of vegetation is one of the most significant. This study is conducted by request from Lantmäteriet (the Swedish mapping, cadastral and land registration authority) and aims to investigate the quality of Laser data Forest. Uncertainty in height and point density is the main focus, as well as how these factors vary in different types of terrain. Uncertainty in height has been investigated by comparisons between laser data and terrestrial control measurements, while point density has been determined by calculations and observations in laser data. Four types of terrain is included in the study: Impervious surface, Grass, Coniferous forest and Deciduous forest. Each type of terrain is represented by three test surfaces, one in each of three different scanning areas. Uncertainty in height was affected by both trees and ground cover, while the vegetational impact on point density was caused by trees alone. Uncertainty in height for individual test sites varied between 0,011 and 0,183 m (RMS). Point density varied between 0,66 and 2,09 points/m2. For the uncertainty in height, a considerable contribution was found to originate from the alignment of the point clouds, which made the analysis of the impact of the terrain more difficult.

Conselho Nacional de Desenvolvimento Científico e Tecnológico / The objective of the work was to study the relationship between the density of trees per hectare and the average diameter to a Deciduous Forest, as well as adjust the model to describe this behavior Reineke. The study area is located in the town of Silveira Martins, in the central region of Rio Grande do Sul and is in early stages of succession after agriculture. The information about the number of the trees per hectare and the average diameter were obtained by the method of density-off proposed by Spurr. These plots were sampled in the early stages of a secondary forest, picking up areas where the predominant Camboatá-vermelho (Cupania vernalis). As natural forests have irregular spacing, density is highly variable, therefore, to select only high-density plots were chosen in areas that there was the occurrence of dead individuals. Were tested different methods to estimate the upper limit of the self thinning line: regression analysis (for all data and relative density greater than 60%), correcting the intercept so that the wastes were negative, the manual adjustment, the relative density (DR> 90%) and stochastic frontier analysis. The method that estimated the maximum density was regression analysis with data from at least 60% of maximum density, obtaining a slope of -1.563 for the model of Reineke. There was no significant difference between the powers provided by the different methods. The maximum Stand Density Index was 1779 trees per hectare, to a dg of 25 cm. The density management diagram was constructed on the basis of basal area, number of trees per hectare and diameter of the tree of average basal area. Were used the densities of 15% and 60%, to close the canopy, and the induction of mortality, respectively. The densities were determined proportionally to the maximum density by stand density index (PDI) for a reference diameter of 25 cm in different classes of index 200, since the IDP 1700, to a minimum of 300. Populations whose density is greater than 60% of the maximum were considered overstocked, between 60 and 15% fully stocked, and below 15% under stocked. They recommended a combination of Dendrogram generated in this study with the method of Spurr to guide interventions in the Deciduous Forest. / O objetivo deste trabalho foi estudar a relação entre a densidade de árvores por hectare e o diâmetro médio para uma Floresta Estacional Decidual, bem como, ajustar o modelo Reineke para descrever este comportamento. A área de estudo localiza-se no município de Silveira Martins, na região central do Rio Grande do Sul e encontra-se em estágio inicial de sucessão, após uso agrícola. As informações referentes ao número de árvores por hectare e o diâmetro médio foram obtidas por meio do método de densidade pontual proposto por Spurr. Estas parcelas foram amostradas nos estágios iniciais de uma floresta secundária, escolhendo-se áreas onde predominava o camboatá-vermelho (Cupania vernalis). Como as florestas naturais apresentam espaçamento irregular, a densidade é bastante variável, assim sendo, para selecionar apenas parcelas em alta densidade, foram escolhidas áreas em que se verificava a ocorrência de indivíduos mortos. Foram testados diferentes métodos para estimar o limite superior da linha de autodesbaste: a análise de regressão (para todos os dados e densidade relativa maior que 60%), corrigindo o intercepto para que os resíduos fossem negativos; o ajuste manual; o de densidade relativa (DR>90%) e a análise de fronteira estocástica. O método que melhor estimou a máxima densidade foi a análise de regressão com dados de no mínimo 60% da densidade máxima, obtendo um coeficiente angular de -1,563 para o modelo de Reineke. Não houve diferença significativa entre as potências fornecidas pelos diferentes métodos. O Índice de Densidade de Povoamento máximo foi de 1779 árvores por hectare, para o dg de 25 cm. O diagrama de manejo da densidade foi construído em função da área basal, do número de árvores por hectare e do diâmetro da árvore de área basal média. Foram utilizadas as densidades de 15% e 60%, para o fechamento das copas, e a indução da mortalidade, respectivamente. Os níveis de densidade foram determinados, proporcionalmente, à máxima densidade por índice de densidade do povoamento (IDP), para um diâmetro de referência de 25 cm, em classes de índice de 200, desde o IDP de 1700, até o mínimo de 300. Populações cuja densidade for maior que 60% da máxima foram consideradas superestocadas, entre 60 e 15% estocadas, e abaixo de 15% subestocadas. Recomendou-se a combinação do Dendrograma gerado neste estudo com o método de Spurr para guiar as intervenções na Floresta Estacional Decidual.

Coral reefs are an important resource world-wide. Unfortunately, coral reef conditions are declining in many areas due to both global and local stressors. The objective of this study was to survey stakeholders in southeast Florida to better understand reef use in the region. Stakeholders spatially identified where and how often they conducted their activities. These data were compiled and analyzed in GIS to determine spatial use patterns. Both location and intensity of use were analyzed to determine which areas may be under greater stress from recreational activities. It was found that reef use was not evenly distributed in the region but clustered around inlets and piers. Reef use differed between user groups (i.e. SCUBA divers, fishers) and demographics. It was also found that use in the Broward-Miami Coral Reef Ecosystem Region was spread out over a wider spatial scale than the use in the regions north and south.. These data are important as they have the potential to inform the recommendations being made to improve coral reef management in southeast Florida. The study can provide a better understanding of human-environmental relationships and the trade-offs involved so that recommendations can better decrease user conflicts, maximize economic productivity, and preserve the environment.

“Vision Zero,” first adopted by Sweden in 1997, is a road safety policy that aims to achieve a transportation system having zero fatalities or serious injuries for all modes of transportation. It takes a proactive approach to road safety system by identifying risk and taking steps to prevent injuries. Historically, traffic related crashes have disproportionately impacted vulnerable communities and system users including people of color, low income individuals, seniors, children, and pedestrians, bicyclists, and transit users (who typically walk to and from public transport). These inequities are addressed in the Vision Zero framework by prioritizing interventions in areas that need safety improvements the most. In 2016, the Alexandria City Council voted unanimously to develop a “Vision Zero” policy and program as a part of its updated transportation master plan. It required an initial equity analysis to assess the impact of traffic crashes on the traditionally underserved communities / groups (groups from at least one of these categories: low-income; minority; elderly; children; limited English proficiency; persons with disabilities; and/or pedestrians/ bicyclists/ transit users). This study combines three different methods to investigate the equity issues regarding traffic safety: 1) descriptive analysis of the spatial pattern of crashes and their relationship with the demographic profiles of neighborhoods at census block group level (for 2010-2014 period); 2) descriptive analysis of the crash trends in Alexandria; and 3) exploratory regression analyses for two different units of analysis (an aggregate regression analysis of crashes at census block group, and a disaggregate regression analysis of the individual level crash reports of traffic crashes). The analysis found that the elderly, school aged children, rail/subway users, and pedestrians had a higher risk of fatalities and severe injuries in traffic crashes. Higher job densities, alcohol impairment, and speeding were significantly related to higher KSI, whereas, smaller block sizes (higher number of street segments per sq. mile area of census block group), higher housing density, and use of safety equipment were related to lower KSI. / Master of Urban and Regional Planning

Point datasets that relate to highly populated places, such as ones retrieved from social media or volunteered geographic information in general, can often result in dense point clusters when presented on maps. Therefore, it can be useful to visualize the relevant point density information directly on the urban geometry to tackle the problem of point counting and density range identification in highly cluttered areas. One solution is to relate each point to the nearest geometry object. While this is a straightforward approach, its major drawback is that local point clusters could disappear by assigning them to larger objects, e.g., long roads. To address this issue, we introduce two new point density visualization approaches by which points are related to the underlying geometry objects. In this process, we use grid cells and heatmap contour lines to divide roads, squares, and pedestrian zones into subgeometry units. Comparison of our visualization approaches with conventional density visualization methods shows that our approaches provide a more comprehensive insight into the point distribution over space, i.e., over existing urban geometry. / Wenn Punktdatensätze, die sich auf dicht bevölkerte Räume beziehen – beispielsweise räumliche Daten aus Sozialen Medien oder von VGI-Plattformen – auf Karten dargestellt werden, kommt es häufig zu dichten Punktclustern, was Aussagen über die Anzahl der Punkte oder die Intensität der Punktdichte an bestimmten Orten schwierig bis unmöglich macht. Daher kann es nützlich sein, relevante Informationen über die Punktdichte direkt mit Bezug zu urbanen Geometrien zu visualisieren. Eine Lösung besteht darin, jeden Punkt dem nächstgelegenen Geometrieobjekt zuzuordnen. Ein großer Nachteil dieses Ansatzes ist jedoch, dass lokale Punktcluster verschwinden könnten, indem sie größeren Objekten, z. B. langen Straßen, zugewiesen werden. Um dieses Problem zu lösen, werden zwei neue Ansätze zur Visualisierung der Punktdichte eingeführt, bei denen die Punkte mit den urbanen Geometrieobjekten in Beziehung gesetzt werden, lokale räumliche Eigenschaften jedoch erhalten bleiben. Dafür werden Straßen, Plätze und Fußgängerzonen mithilfe von Rasterzellen und Konturlinien von Kerndichteschätzungen in Teilgeometrieeinheiten unterteilt. Der Vergleich dieser Visualisierungsansätze mit herkömmlichen Dichtevisualisierungsmethoden zeigt, dass die vorgestellten Ansätze einen detaillierteren Einblick in die räumliche Punktverteilung mit Bezug zur bestehenden urbanen Geometrie liefern können.