Modelling and simulation of a photovoltaic fuel cell hybrid system

A stand-alone power system is an autonomous system that supplies electricity to the user load without being connected to the electric grid. This kind of decentralized system is frequently located in remote and inaccessible areas. It is essential for about one third of the world population which are living in developed or isolated regions and have no access to an electricity utility grid. The most people live in remote and rural areas, with low population density, lacking even the basic infrastructure. The utility grid extension to these locations is not a cost effective option and sometimes technically not feasible. The purpose of this thesis is the modelling and simulation of a stand-alone hybrid power system, referred to as “hydrogen Photovoltaic-Fuel Cell (PVFC) hybrid system”. It couples a photovoltaic generator (PV), an alkaline water electrolyser, a storage gas tank, a proton exchange membrane fuel cell (PEMFC), and power conditioning units (PCU) to give different system topologies. The system is intended to be an environmentally friendly solution since it tries maximising the use of a renewable energy source. Electricity is produced by a PV generator to meet the requirements of a user load. Whenever there is enough solar radiation, the user load can be powered totally by the PV electricity. During periods of low solar radiation, auxiliary electricity is required. An alkaline high pressure water electrolyser is powered by the excess energy from the PV generator to produce hydrogen and oxygen at a pressure of maximum 30bar. Gases are stored without compression for short- (hourly or daily) and long- (seasonal) term. A proton exchange membrane (PEM) fuel cell is used to keep the system’s reliability at the same level as for the conventional system while decreasing the environmental impact of the whole system. The PEM fuel cell consumes gases which are produced by an electrolyser to meet the user load demand when the PV generator energy is deficient, so that it works as an auxiliary generator. Power conditioning units are appropriate for the conversion and dispatch the energy between the components of the system. No batteries are used in this system since they represent the weakest when used in PV systems due to their need for sophisticated control and their short lifetime. The model library, ISET Alternative Power Library (ISET-APL), is designed by the Institute of Solar Energy supply Technology (ISET) and used for the simulation of the hybrid system. The physical, analytical and/or empirical equations of each component are programmed and implemented separately in this library for the simulation software program Simplorer by C++ language. The model parameters are derived from manufacturer’s performance data sheets or measurements obtained from literature. The identification and validation of the major hydrogen PVFC hybrid system component models are evaluated according to the measured data of the components, from the manufacturer’s data sheet or from actual system operation. Then, the overall system is simulated, at intervals of one hour each, by using solar radiation as the primary energy input and hydrogen as energy storage for one year operation. A comparison between different topologies, such as DC or AC coupled systems, is carried out on the basis of energy point of view at two locations with different geographical latitudes, in Kassel/Germany (Europe) and in Cairo/Egypt (North Africa). The main conclusion in this work is that the simulation method of the system study under different conditions could successfully be used to give good visualization and comparison between those topologies for the overall performance of the system. The operational performance of the system is not only depending on component efficiency but also on system design and consumption behaviour. The worst case of this system is the low efficiency of the storage subsystem made of the electrolyser, the gas storage tank, and the fuel cell as it is around 25-34% at Cairo and 29-37% at Kassel. Therefore, the research for this system should be concentrated in the subsystem components development especially the fuel cell.

Research through DESIGN through research - a problem statement and a conceptual sketch

This paper re-addresses the issue of a lacking genuine design research paradigm. It tries to sketch an operational model of such a paradigm, based upon a generic design process model, which is derived from basic notions of evolution and learning in different domains of knowing (and turns out to be not very different from existing ones). It does not abandon the scientific paradigm but concludes that the latter has to be embedded into / subordinated under a design paradigm.

Soil organic carbon management for sustainable land use in Sudano-Sahelian West Africa

Judged by their negative nutrient balances, low soil cover and low productivity, the predominant agro-pastoral farming systems in the Sudano-Sahelian zone of West Africa are highly unsustainable for crop production intensification. With kaolinite as the main clay type, the cation exchange capacity of the soils in this region, often less than 1 cmol_c kg^-1 soil, depends heavily on the organic carbon (Corg) content. However, due to low carbon sequestration and to the microbe, termite and temperature-induced rapid turnover rates of organic material in the present land-use systems, Corg contents of the topsoil are very low, ranging between 1 and 8 g kg^-1 in most soils. For sustainable food production, the availability of phosphorus (P) and nitrogen (N) has to be increased considerably in combination with an improvement in soil physical properties. Therefore, the adoption of innovative management options that help to stop or even reverse the decline in Corg typically observed after cultivating bush or rangeland is of utmost importance. To maintain food production for a rapidly growing population, targeted applications of mineral fertilisers and the effective recycling of organic amendments as crop residues and manure are essential. Any increase in soil cover has large effects in reducing topsoil erosion by wind and water and favours the accumulation of wind-blown dust high in bases which in turn improves P availability. In the future decision support systems, based on GIS, modelling and simulation should be used to combine (i) available fertiliser response data from on-station and on-farm research, (ii) results on soil productivity restoration with the application of mineral and organic amendments and (iii) our present understanding of the cause-effect relationships governing the prevailing soil degradation processes. This will help to predict the effectiveness of regionally differentiated soil fertility management approaches to maintain or even increase soil Corg levels.

Evolving Distributed Algorithms with Genetic Programming

Distributed systems are one of the most vital components of the economy. The most prominent example is probably the internet, a constituent element of our knowledge society. During the recent years, the number of novel network types has steadily increased. Amongst others, sensor networks, distributed systems composed of tiny computational devices with scarce resources, have emerged. The further development and heterogeneous connection of such systems imposes new requirements on the software development process. Mobile and wireless networks, for instance, have to organize themselves autonomously and must be able to react to changes in the environment and to failing nodes alike. Researching new approaches for the design of distributed algorithms may lead to methods with which these requirements can be met efficiently. In this thesis, one such method is developed, tested, and discussed in respect of its practical utility. Our new design approach for distributed algorithms is based on Genetic Programming, a member of the family of evolutionary algorithms. Evolutionary algorithms are metaheuristic optimization methods which copy principles from natural evolution. They use a population of solution candidates which they try to refine step by step in order to attain optimal values for predefined objective functions. The synthesis of an algorithm with our approach starts with an analysis step in which the wanted global behavior of the distributed system is specified. From this specification, objective functions are derived which steer a Genetic Programming process where the solution candidates are distributed programs. The objective functions rate how close these programs approximate the goal behavior in multiple randomized network simulations. The evolutionary process step by step selects the most promising solution candidates and modifies and combines them with mutation and crossover operators. This way, a description of the global behavior of a distributed system is translated automatically to programs which, if executed locally on the nodes of the system, exhibit this behavior. In our work, we test six different ways for representing distributed programs, comprising adaptations and extensions of well-known Genetic Programming methods (SGP, eSGP, and LGP), one bio-inspired approach (Fraglets), and two new program representations called Rule-based Genetic Programming (RBGP, eRBGP) designed by us. We breed programs in these representations for three well-known example problems in distributed systems: election algorithms, the distributed mutual exclusion at a critical section, and the distributed computation of the greatest common divisor of a set of numbers. Synthesizing distributed programs the evolutionary way does not necessarily lead to the envisaged results. In a detailed analysis, we discuss the problematic features which make this form of Genetic Programming particularly hard. The two Rule-based Genetic Programming approaches have been developed especially in order to mitigate these difficulties. In our experiments, at least one of them (eRBGP) turned out to be a very efficient approach and in most cases, was superior to the other representations.

Molekulare Studien zur Evolution der Myrmekophytie in der Gattung Macaranga (Euphorbiaceae)

Im Rahmen der vorliegenden Arbeit wurde eine detaillierte phylogenetische Analyse der Ameisenpflanzen aus der Gattung Macaranga (Euphorbiaceae) und ihres verwandtschaftlichen Umfelds mit Hilfe von AFLP-Fingerprinting („amplified fragment length polymorphisms“) sowie vergleichender Analyse von mehreren nichtkodierenden Chloroplasten-DNA-Loci vorgenommen. Anhand dieser Untersuchungen sollten im Wesentlichen die folgenden Fragen geklärt werden: (1) Wie stellen sich die Verwandtschaftsverhältnisse zwischen den myrmekophytischen Macaranga-Sektionen Pachystemon, Winklerianae und Pruinosae dar? (2) Wie sind die einzelnen Arten dieser Sektionen miteinander verwandt? (3) Wie oft ist die Lebensweise ”Myrmekophytie” unabhängig voneinander entstanden? Gibt es Hinweise auf Reversionen? (4) Wo liegt genealogisch und auch geographisch der Ursprung der Symbiose zwischen den myrmekophytischen Macaranga-Arten und ihren Partnerameisen? (5) Welche Bedeutung spielen koevolutive Entwicklungen für das Macaranga-Crematogaster-Symbiosesystem? Ist Myrmekophytie im Sinne einer Schlüsselinnovation (Givnish, 1997) als Stimulus für eine adaptive Radiation zu betrachten? (1) Für die AFLP-Analyse wurden 108 Proben aus 43 Macaranga-Arten und 5 unbeschriebenen Morphospezies in die phylogenetische Untersuchung einbezogen. Auf der Basis von 426 Merkmalen wurden Phänogramme sowie Kladogramme rekonstruiert. Zur statistischen Absicherung wurden Bootstrap-Analysen durchgeführt und im Falle der Kladogramme darüber hinaus der „consistency“-Index bestimmt. Die AFLP-Datensätze wurden zusätzlich einer Hauptkomponentenanalyse unterzogen. Mit Hilfe der verschiedenen Untersuchungsmethoden konnten weitgehend übereinstimmende Gruppierungen bzw. evolutive Linien identifiziert werden. Die Sektionen Pachystemon und Pruinosae bilden eine jeweils gut gestützte monophyletische Gruppe. Beide sind vermutlich Schwestergruppen und damit gleich alt. Für die Monophylie der nur aus zwei Arten bestehenden Sektion Winklerianae ergab sich keine Unterstützung. Die Arten der Sektion Pruinosae sind im AFLP-Baum gut aufgelöst. Die nicht myrmekophytische M. gigantea sitzt dabei an der Basis und ist Schwestergruppe zu den myrmekophytischen Arten. Innerhalb der Sektion Pachystemon wurden mit Hilfe der AFLP-Analyse vier gut gestützte Gruppen identifiziert. Für die puncticulata-Gruppe konnte hier erstmals auf molekularer Ebene eine Zugehörigkeit zur Sekt. Pachystemon nachgewiesen werden. Der von Davies (2001) vorgenommene Ausschluss von M. recurvata aus der Sekt. Pachystemon konnte bestätigt werden. Die Verwandtschaftsbeziehungen einzelner Arten zueinander sind in den AFLP-Bäumen nicht aufgelöst. (2) Für die vergleichende Chloroplasten-Sequenzierung wurden nach Maßgabe der Sequenzvariabilität in Testsequenzierungen die Bereiche atpB-rbcL und psbI-trnS für die phylogenetische Untersuchung ausgewählt. Für die Chloroplasten-Phylogenie wurden für jeden Locus mehr als 100 Sequenzen analysiert. Neben 29 Pachystemon-Arten inkl. vier unbekannter Morphospezies, acht Pruinosae-Arten inkl. eines möglichen Hybriden und den beiden Arten der Sekt. Winklerianae wurden 22 weitere Macaranga- und 10 Mallotus-Arten in die Untersuchung einbezogen. Zwischen den südostasiatischen Arten bestanden nur geringe Sequenzunterschiede. Maximum-Parsimonie-Kladogramme wurden rekonstruiert und die Sequenzen der beiden Loci wurden sowohl einzeln, als auch kombiniert ausgewertet. Indels wurden kodiert und als separate Merkmalsmatrix an die Sequenzdaten angehangen. Innerhalb von Macaranga konnten nur wenige abgesicherte Gruppen identifiziert werden. Deutlich war die Zusammengehörigkeit der afrikanischen Arten und ihr Entstehung aus den südostasiatischen Arten. Die von Davies (2001) der Sektion Pruinosae zugeordnete M. siamensis steht deutlich außerhalb dieser Sektion. Die Arten der Sektionen Pruinosae, Pachystemon und Winklerianae bilden keine statistisch gesicherten monophyletischen Gruppen. Während der Pilotstudien stellte sich heraus, dass die Chloroplastensequenzen nahe verwandter Arten der Sektion Pachystemon weniger nach den Artgrenzen, sondern vielmehr nach geographischen Kriterien gruppierten. (3) Es wurde daher zusätzlich eine phylogeographische Analyse der Chloroplasten-Sequenzen auf der Basis eines Parsimonie-Netzwerks durchgeführt. Neben dem atpB-rbcL-Spacer und einer Teilsequenze des psbI-trnS-Locus (ccmp2) wurde dafür zusätzlich der ccmp6-Locus (ein Abschnitt des ycf3-Introns) sequenziert. Die phylogeographische Untersuchung wurde mit 144 Proben aus 41 Macaranga-Arten durchgeführt. Darin enthalten waren 29 Arten (inkl. vier Morphospezies) mit 112 Proben der Sektion Pachystemon, sieben 7 Arten (inkl. eines potentiellen Hybriden) mit 22 Proben der Sekt. Pruinosae und zwei Arten mit 5 Proben der Sekt. Winklerianae. Das voll aufgelöste statistische Parsimonie-Netzwerk umfasste 88 Haplotypen. Die Sektionen Pachystemon und Pruinosae bilden jeweils eine monophyletische Gruppe. Das geographische Arrangement der Haplotypen unabhängig von der Artzugehörigkeit könnte durch Introgression und/oder „lineage sorting“ bedingt sein. Mit Hilfe der im Rahmen dieser Arbeit gewonnenen Ergebnisse kann man davon ausgehen, dass eine enge Ameisen-Pflanzen-Symbiose innerhalb der Gattung Macaranga mindestens drei-, möglicherweise viermal unabhängig voneinander entstanden ist Eine Reversion hat mindestens einmal, möglicherweise häufiger in der bancana-Gruppe stattgefunden. Ob sich die Symbiose dabei in Westmalaysia oder in Borneo entwickelt hat, kann man nicht sicher sagen; Ob und inwieweit die große Artenzahl in der bancana-Gruppe als eine Folge der Myrmekophytie anzusehen ist, bleibt zunächst offen. Wesentliche Teile der vorliegenden Arbeit liegen bereits in publizierter Form vor (AFLP-Analyse: Bänfer et al. 2004; Chloroplasten-Analyse: Vogel et al. 2003; Bänfer et al. 2006).

Enterprise Modelling Approach based on Maturity and Business Scope perspectives

This paper introduces a framework that supports users to implement enterprise modelling within collaborative companies. These enterprise models are the basis for a holistic interoperability measurement and management methodology which will be presented in the second part of the paper. The discipline of enterprise modelling aims at capturing all dimensions of an enterprise in a simplified model. Thus enterprise models are the appropriate basis for managing collaborative enterprise as they reduce the complexity of interoperability problems. Therefore, a first objective of this paper is to present an approach that enables companies to get the most effect out of enterprise modelling in a collaborative environment based on the maturity of their organisation relative to modelling. Within this first step, the user will get recommendations e.g. for the correct modelling language as well as the right level of detail.

Climate-Adaptive Community Water Management for Food Security: Experiences from the UNDP Community Water Initiative

Facing the double menace of climate change threats and water crisis, poor communities have now encountered ever more severe challenges in ensuring agricultural productivity and food security. Communities hence have to manage these challenges by adopting a comprehensive approach that not only enhances water resource management, but also adapts agricultural activities to climate variability. Implemented by the Global Environment Facility’s Small Grants Programme, the Community Water Initiative (CWI) has adopted a distinctive approach to support demand-driven, innovative, low cost and community-based water resource management for food security. Experiences from CWI showed that a comprehensive, locally adapted approach that integrates water resources management, poverty reduction, climate adaptation and community empowerment provides a good model for sustainable development in poor rural areas.

The Human in the Loop: User Participation in Self-Adaptive Software

Self-adaptive software provides a profound solution for adapting applications to changing contexts in dynamic and heterogeneous environments. Having emerged from Autonomic Computing, it incorporates fully autonomous decision making based on predefined structural and behavioural models. The most common approach for architectural runtime adaptation is the MAPE-K adaptation loop implementing an external adaptation manager without manual user control. However, it has turned out that adaptation behaviour lacks acceptance if it does not correspond to a user’s expectations – particularly for Ubiquitous Computing scenarios with user interaction. Adaptations can be irritating and distracting if they are not appropriate for a certain situation. In general, uncertainty during development and at run-time causes problems with users being outside the adaptation loop. In a literature study, we analyse publications about self-adaptive software research. The results show a discrepancy between the motivated application domains, the maturity of examples, and the quality of evaluations on the one hand and the provided solutions on the other hand. Only few publications analysed the impact of their work on the user, but many employ user-oriented examples for motivation and demonstration. To incorporate the user within the adaptation loop and to deal with uncertainty, our proposed solutions enable user participation for interactive selfadaptive software while at the same time maintaining the benefits of intelligent autonomous behaviour. We define three dimensions of user participation, namely temporal, behavioural, and structural user participation. This dissertation contributes solutions for user participation in the temporal and behavioural dimension. The temporal dimension addresses the moment of adaptation which is classically determined by the self-adaptive system. We provide mechanisms allowing users to influence or to define the moment of adaptation. With our solution, users can have full control over the moment of adaptation or the self-adaptive software considers the user’s situation more appropriately. The behavioural dimension addresses the actual adaptation logic and the resulting run-time behaviour. Application behaviour is established during development and does not necessarily match the run-time expectations. Our contributions are three distinct solutions which allow users to make changes to the application’s runtime behaviour: dynamic utility functions, fuzzy-based reasoning, and learning-based reasoning. The foundation of our work is a notification and feedback solution that improves intelligibility and controllability of self-adaptive applications by implementing a bi-directional communication between self-adaptive software and the user. The different mechanisms from the temporal and behavioural participation dimension require the notification and feedback solution to inform users on adaptation actions and to provide a mechanism to influence adaptations. Case studies show the feasibility of the developed solutions. Moreover, an extensive user study with 62 participants was conducted to evaluate the impact of notifications before and after adaptations. Although the study revealed that there is no preference for a particular notification design, participants clearly appreciated intelligibility and controllability over autonomous adaptations.

Adaptive Real-time Anomaly-based Intrusion Detection using Data Mining and Machine Learning Techniques

Die zunehmende Vernetzung der Informations- und Kommunikationssysteme führt zu einer weiteren Erhöhung der Komplexität und damit auch zu einer weiteren Zunahme von Sicherheitslücken. Klassische Schutzmechanismen wie Firewall-Systeme und Anti-Malware-Lösungen bieten schon lange keinen Schutz mehr vor Eindringversuchen in IT-Infrastrukturen. Als ein sehr wirkungsvolles Instrument zum Schutz gegenüber Cyber-Attacken haben sich hierbei die Intrusion Detection Systeme (IDS) etabliert. Solche Systeme sammeln und analysieren Informationen von Netzwerkkomponenten und Rechnern, um ungewöhnliches Verhalten und Sicherheitsverletzungen automatisiert festzustellen. Während signatur-basierte Ansätze nur bereits bekannte Angriffsmuster detektieren können, sind anomalie-basierte IDS auch in der Lage, neue bisher unbekannte Angriffe (Zero-Day-Attacks) frühzeitig zu erkennen. Das Kernproblem von Intrusion Detection Systeme besteht jedoch in der optimalen Verarbeitung der gewaltigen Netzdaten und der Entwicklung eines in Echtzeit arbeitenden adaptiven Erkennungsmodells. Um diese Herausforderungen lösen zu können, stellt diese Dissertation ein Framework bereit, das aus zwei Hauptteilen besteht. Der erste Teil, OptiFilter genannt, verwendet ein dynamisches "Queuing Concept", um die zahlreich anfallenden Netzdaten weiter zu verarbeiten, baut fortlaufend Netzverbindungen auf, und exportiert strukturierte Input-Daten für das IDS. Den zweiten Teil stellt ein adaptiver Klassifikator dar, der ein Klassifikator-Modell basierend auf "Enhanced Growing Hierarchical Self Organizing Map" (EGHSOM), ein Modell für Netzwerk Normalzustand (NNB) und ein "Update Model" umfasst. In dem OptiFilter werden Tcpdump und SNMP traps benutzt, um die Netzwerkpakete und Hostereignisse fortlaufend zu aggregieren. Diese aggregierten Netzwerkpackete und Hostereignisse werden weiter analysiert und in Verbindungsvektoren umgewandelt. Zur Verbesserung der Erkennungsrate des adaptiven Klassifikators wird das künstliche neuronale Netz GHSOM intensiv untersucht und wesentlich weiterentwickelt. In dieser Dissertation werden unterschiedliche Ansätze vorgeschlagen und diskutiert. So wird eine classification-confidence margin threshold definiert, um die unbekannten bösartigen Verbindungen aufzudecken, die Stabilität der Wachstumstopologie durch neuartige Ansätze für die Initialisierung der Gewichtvektoren und durch die Stärkung der Winner Neuronen erhöht, und ein selbst-adaptives Verfahren eingeführt, um das Modell ständig aktualisieren zu können. Darüber hinaus besteht die Hauptaufgabe des NNB-Modells in der weiteren Untersuchung der erkannten unbekannten Verbindungen von der EGHSOM und der Überprüfung, ob sie normal sind. Jedoch, ändern sich die Netzverkehrsdaten wegen des Concept drif Phänomens ständig, was in Echtzeit zur Erzeugung nicht stationärer Netzdaten führt. Dieses Phänomen wird von dem Update-Modell besser kontrolliert. Das EGHSOM-Modell kann die neuen Anomalien effektiv erkennen und das NNB-Model passt die Änderungen in Netzdaten optimal an. Bei den experimentellen Untersuchungen hat das Framework erfolgversprechende Ergebnisse gezeigt. Im ersten Experiment wurde das Framework in Offline-Betriebsmodus evaluiert. Der OptiFilter wurde mit offline-, synthetischen- und realistischen Daten ausgewertet. Der adaptive Klassifikator wurde mit dem 10-Fold Cross Validation Verfahren evaluiert, um dessen Genauigkeit abzuschätzen. Im zweiten Experiment wurde das Framework auf einer 1 bis 10 GB Netzwerkstrecke installiert und im Online-Betriebsmodus in Echtzeit ausgewertet. Der OptiFilter hat erfolgreich die gewaltige Menge von Netzdaten in die strukturierten Verbindungsvektoren umgewandelt und der adaptive Klassifikator hat sie präzise klassifiziert. Die Vergleichsstudie zwischen dem entwickelten Framework und anderen bekannten IDS-Ansätzen zeigt, dass der vorgeschlagene IDSFramework alle anderen Ansätze übertrifft. Dies lässt sich auf folgende Kernpunkte zurückführen: Bearbeitung der gesammelten Netzdaten, Erreichung der besten Performanz (wie die Gesamtgenauigkeit), Detektieren unbekannter Verbindungen und Entwicklung des in Echtzeit arbeitenden Erkennungsmodells von Eindringversuchen.

Extracting Urban Food Potential: design-based methods for digital and bodily cartography

Sweden’s recent report on Urban Sustainable Development calls out a missing link between the urban design process and citizens. This paper investigates if engaging citizens as design agents by providing a platform for alternate participation can bridge this gap, through the transfer of spatial agency and new modes of critical cartography. To assess whether this is the case, the approaches are applied to Stockholm’s urban agriculture movement in a staged intervention. The aim of the intervention was to engage citizens in locating existing and potential places for growing food and in gathering information from these sites to inform design in urban agriculture. The design-based methodologies incorporated digital and bodily interfaces for this cartography to take place. The Urban CoMapper, a smartphone digital app, captured real-time perspectives through crowd-sourced mapping. In the bodily cartography, participant’s used their bodies to trace the site and reveal their sensorial perceptions. The data gathered from these approaches gave way to a mode of artistic research for exploring urban agriculture, along with inviting artists to be engaged in the dialogues. In sum, results showed that a combination of digital and bodily approaches was necessary for a critical cartography if we want to engage citizens holistically into the urban design process as spatial agents informing urban policy. Such methodologies formed a reflective interrogation and encouraged a new intimacy with nature, in this instance, one that can transform our urban conduct by questioning our eating habits: where we get our food from and how we eat it seasonally.

Reinventing the academic conference: how delegates design productive cities

During the 6th International Sustainable Food Planning Conference, the so-called Design LABs partly replaced the regular parallel sessions. The reason for this change was twofold. On the one hand it aims to break through an endless series of parallel presentations, and on the other hand the LAB’s aim was to produce innovative design solutions for increasing the amount of food production in the city. This article describes this experiment to enhance the delivery of urban design concepts, which could substantially produce more food than current models. During the conference each of the parallel sessions half of the time consisted of a design-LAB, in which participants were brought together around a map with the task to design a substantial amount of food productive spaces in the case study site. The results of this experiment were dual: 1. a very committed attitude of delegates to this part of the conference and 2. the design tasks resulted in innovative design results. These results not only emphasise the potential design measures onsite but also pledged for a strong and more intensive connectivity with the city and the landscape around it. This makes it possible to link the supply and use of resources with the typology of the region, hence determining an effective and productive urban agriculture system.

Cultivating the City: Infrastructures of abundance in urban Brazil

Urban agriculture, if it is to become integrated into the city, needs landscape architectural thinking in order to be woven into the larger urban fabric. Thinking at the scale of ecosystems running through a city creates a framework for spatial change; thinking in assemblages of stakeholders and actors creates a framework for social investment and development. These overlapping frameworks are informed and perhaps even defined by the emergent field of landscape democracy. Cultivating the City is a prospective design project seeking to embody landscape democratic principles. The intention is to reclaim the meaning of landscape as the relationship between people and place, both shaping each other. The design in question is a proposed network of urban agriculture typologies in Porto Alegre, Brazil. These hypothetical designs, emphasizing agroforestry with native species, serve as a basis for dialogue between potential stakeholders and as catalysts for future projects. This landscape architecture project sets out to be a mediator in processes of spatial evolution in order to envision just and sustainable urban landscapes.