Spatial Reconstruction of Biological Trees from Point Cloud

Trees are complex systems in nature whose topology and geometry ar

Procedural modelling techniques to configure driving serious game scenes

Esta dissertação tem o objetivo de tratar do problema da segurança rodoviária, a fim de evitar mais acidentes e mortes tanto de motoristas como de pedestres através da criação de uma ferramenta que é capaz de carregar dados do mundo real a partir de localizações selecionadas pelo utilizador e transformá-los em modelos tridimensionais para uso posterior em jogos de condução sérios. Estes modelos são então povoados com os pedestres que andam nos passeios e a capacidade de conduzir um veículo é dada ao utilizador. Além disso, a ferramenta deve ser flexível o suficiente para permitir que os utilizadores configurem diferentes condições, tais como o tempo, hora do dia, opções de renderização, os danos do veículo e densidade de pedestres, a fim de realizar estudos em diferentes condições. O projeto também deve ser de código aberto, para que qualquer pessoa pode editá-lo e expandi-lo para atender as suas necessidades e realizar estudos específicos. Possui integração Oculus Rift, que estende ainda mais a possibilidade de realização de estudos para o motorista humano, através da expanção dessa integração para avaliar os comportamentos do motorista. Outro aspeto importante é a possibilidade de exportar toda a cena procedimentalmente gerada para um formato de ficheiro 3D que pode ser editado numa aplicação externa.Ao fornecer esta ferramenta de forma gratuita, não só marca o início de um gerador do mundo em 3D de código aberto, mas também uma ferramenta capaz de permitir diversos usos diferentes, tais como a realização de estudos, a construção de cenários de jogos de vídeo ou ser usado como uma ferramenta de aprendizagem por uma escola de condução. Esperemos que isto seja capaz de aumentar a segurança rodoviária, se usado com cuidado como uma ferramenta séria.Para fazer isto vamos usar o motor de jogo Unity 5 para desenvolver o projeto, CGIAR-CSI para baixar dados de elevação, o Google Static Maps para as imagens de satélite, OpenStreetMap para os dados de localização e tudo o mais é construído dentro do Unity. Também é usado o UnitySlippyMap, que é um mapa do mundo que trabalha com vários fornecedores de "tiles" que foi integrado no contexto deste projeto para permitir que os utilizadores selecionem um local dentro do Unity.Ao longo deste documento, irá encontrar uma revisão da literatura sobre o tema, incluindo o trabalho relacionado e tentativas de fazer projetos semelhantes, seguido de uma comparação entre outros projetos e este. Irá também encontrar detalhes sobre o desenvolvimento e a arquitetura do sistema, bem como detalhes profundos sobre a implementação. No final pode encontrar algumas capturas de ecrã dos resultados deste projeto e a conclusão que refere a satisfação dos objetivos e trabalho futuro.Palavras Chave: Modelação Procedimental, Simulação de Condução, Locais do Mundo, Jogos Sérios, Segurança RodoviáriaThis dissertation has the objective of tackling the road safety problem in order to further prevent accidents and casualties for both drivers and pedestrians by creating a tool that is capable of loading real world data from user selected locations and render them in 3 dimensional models for further use in serious driving games. These models are then populated with pedestrians that walk around and the ability to drive a vehicle is given to the user. Also the tool should be flexible enough to allow the users to configure the different conditions such as weather, time of day, rendering options, vehicle damage and pedestrian density, in order to conduct studies on different conditions. The project should also be open source, so anyone can edit it and expand it their own way to suit their needs and conduct specific studies. It features Oculus Rift integration, which further extends the possibility of conducting studies to the human driver by giving the possibility to expand this integration to evaluate the driver's behaviours. Another important aspect is the possibility to export the entire procedurally generated scene to a 3D file format that can be edited by an external application.By providing such tool for free, not only marks the beginning of an open source world 3D generator, but also a framework capable of allowing multiple different usages, such as conducting studies, building video game scenarios or be used as a learning tool by a driving school for instance. Hopefully this will increase road safety if used carefully as a serious tool.To do so we'll use the game engine Unity 5 to develop the project, CGIAR-CSI to download elevation data, Google Static Maps for the satellite imagery, OpenStreetMap for the location data and everything else is built inside Unity. Also UnitySlippyMap, which is a world map that works with various tile providers was used and integrated on the context of this project to allow users to select a location inside Unity.Along this document you will find a literature review on the topic, including related work and attempts to do similar projects followed by a comparison between other project and this one. The reader will also find details about development and the system's architecture as well as deep details about implementation. On the end you can find a few screen shots of the results of this project.Key Words: Procedural Modelling, Driving Simulation, World Locations, Serious Games, Road Safet

Simulating maize/bean polycultures using functional-structural plant modelling

Climate change, a growing global population and soil degradation put significant stress on food production and threaten food security, both on a global scale and in individual agricultural communities. This necessitates studies that explore sustainable agricultural intensification. Traditional farming systems have received increased attention, as aspects of these systems (such as niche complementarity) might provide sustainable solutions. This work centers around the three sisters, a polyculture of maize (Zea mays), bean (Phaseolus vulgaris) and squash (Cucurbita spp.), and the milpa, a complex Maya polyculture centered around maize and bean. Building on an existing functional-structural plant (FSP) model for maize, a novel FSP model for common bean is developed (in the XL language, on the GroIMP platform), encompassing twining behaviour and physical plant-plant interactions. This allows us to simulate maize/bean polycultures, where common bean climbs upwards around the maize stalk. As the model contains many input parameters, of which some are difficult or costly to parameterise, a global sensitivity analysis (GSA) is paramount for identifying (un)important parameters in the model. This decreases dimensionality of the large model parameter space. Efforts can then be concentrated on accurately estimating the most important input parameters. GSA is therefore performed on monocultures of maize and common bean (growing on poles). To this end, the popular Elementary Effects GSA method is adapted to make it suitable for models with dimensional inputs, inputs taking values on arbitrary intervals or discrete inputs. Our results show the benefit of performing GSA on plant models: for both maize and bean, less than 30% of input parameters where classified as important for most model outputs. In addition, performing GSA on plant models leads to new insights about both the model and the plant developmental processes it describes. The hope is that this work will inspire more plant modellers to routinely incorporate sensitivity analysis in their research. Subsequently, the model for maize and bean is used to assess architectural facilitation in light capture in maize/bean polycultures. Simulation results agree with experimental observations in the literature of overyielding in polycultures including maize and climbing bean. This indicates that aboveground processes (also) play an important role in the phenomenon of overperforming. In addition, it confirms that such agricultural systems may play a role in sustainable agricultural intensification. The maize/bean model presented in this work is one of the first examples of an aboveground FSP model of a polyculture with complex physical plant-plant interaction. Our results suggest that FSP modelling could be a valuable tool to investigate such agricultural systems. In this work, we have shown that it is possible to model maize/bean crop mixtures, making an aboveground model of the three sisters only a small step away

Simulating maize/bean polycultures using functional-structural plant modelling

Climate change, a growing global population and soil degradation put significant stress on food production and threaten food security, both on a global scale and in individual agricultural communities. This necessitates studies that explore sustainable agricultural intensification. Traditional farming systems have received increased attention, as aspects of these systems (such as niche complementarity) might provide sustainable solutions. This work centers around the three sisters, a polyculture of maize (Zea mays), bean (Phaseolus vulgaris) and squash (Cucurbita spp.), and the milpa, a complex Maya polyculture centered around maize and bean. Building on an existing functional-structural plant (FSP) model for maize, a novel FSP model for common bean is developed (in the XL language, on the GroIMP platform), encompassing twining behaviour and physical plant-plant interactions. This allows us to simulate maize/bean polycultures, where common bean climbs upwards around the maize stalk. As the model contains many input parameters, of which some are difficult or costly to parameterise, a global sensitivity analysis (GSA) is paramount for identifying (un)important parameters in the model. This decreases dimensionality of the large model parameter space. Efforts can then be concentrated on accurately estimating the most important input parameters. GSA is therefore performed on monocultures of maize and common bean (growing on poles). To this end, the popular Elementary Effects GSA method is adapted to make it suitable for models with dimensional inputs, inputs taking values on arbitrary intervals or discrete inputs. Our results show the benefit of performing GSA on plant models: for both maize and bean, less than 30% of input parameters where classified as important for most model outputs. In addition, performing GSA on plant models leads to new insights about both the model and the plant developmental processes it describes. The hope is that this work will inspire more plant modellers to routinely incorporate sensitivity analysis in their research. Subsequently, the model for maize and bean is used to assess architectural facilitation in light capture in maize/bean polycultures. Simulation results agree with experimental observations in the literature of overyielding in polycultures including maize and climbing bean. This indicates that aboveground processes (also) play an important role in the phenomenon of overperforming. In addition, it confirms that such agricultural systems may play a role in sustainable agricultural intensification. The maize/bean model presented in this work is one of the first examples of an aboveground FSP model of a polyculture with complex physical plant-plant interaction. Our results suggest that FSP modelling could be a valuable tool to investigate such agricultural systems. In this work, we have shown that it is possible to model maize/bean crop mixtures, making an aboveground model of the three sisters only a small step away