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A Multi-Agent System for Simulating Land-Use and Land-Cover Change In A multi-agent system for simulating land-use and land-cover change in the Atankwidi catchment of Upper East Ghana Dissertation zur Erlangung des Doktorgrades (Dr. rer. nat) der Mathematisch-Naturwissenschaftlichen Fakultät der Rheinischen Friedrich-Wilhelms-Universität Bonn vorgelegt von JULIA SCHINDLER aus BASEL Bonn 2009 1. Referent: Prof. Dr. P.L.G. Vlek 2. Referent: Prof. Dr. E. Ehlers Tag der Promotion: 24.09.2009 Erscheinungsjahr: 2009 Diese Dissertation ist auf dem Hochschulschriftenserver der ULB Bonn http://hss.ulb.uni-bonn.de/diss_online elektronisch publiziert Für meinen Vater Hansgeorg Schindler (1943-2001) ABSTRACT Land-use and land-cover change (LUCC), which is a general term for the human modification of the Earth’s terrestrial surface, increasingly gains attention in the scientific community, due to its vast global extent and the role it plays in the Earth system functioning. About one third to one half of the global land surface has been modified by humans, and these changes are highly interrelated with many environmental, economic and social processes and problems. However, studies on LUCC processes are often challenged by the complex nature and unex- pected behavior of both human drivers and natural constraints. Many studies tend to focus either on the human or the environmental part of LUCC systems, thus neglecting the interre- lationships and responses among these two components. Many aspects of complexity can be overcome by a multi-agent based approach, whose design allows an integrated representation of the feedbacks, hierarchies and interdependencies of the coupled human-environment sys- tem of LUCC. A multi-agent simulation model (GH-LUDAS - GHana Land Use DynAmic Simulator) was developed to model this coupled human-environment system in a small-scale catchment in Ghana, thereby providing a simulation tool to predict land-use/cover patterns as related to socio-economic indicators. Apart from pure prediction, the aim of the model is to explore alternative future pathways of LUCC under selected policy, demographic and climatic conditions in order to provide stakeholders with support for making better-informed decisions about land resource management. Multi-agent based modelling is an approach to design computational models for simulating the actions and interactions of autonomous individuals (i.e. agents) in a network, with a view to assessing their effects on the system as a whole. Thus, agent-based modeling can be regarded as a bottom-up modeling approach, as the behavior and interactions of sin- gle agents are specified, and complexity is considered to emerge from these specifications. Following this mindset, GH-LUDAS consists of four modules, which represent the main components of the human-evironment system of LUCC. The Human Module consists of col- lections of human agents (i.e. farm households), which are endowed with a set of attributes and autonomous behavior templates (i.e. the Decision Module), regulating land-use related decisions in response to the human agent’s attributes and those of its environment. The Land- scape Module consists of collections of individual landscape agents (i.e. land patches of size 30 x 30 m), which are characterized by biophysical attributes and ecological mechanisms, which work in response to human decision-making and natural constraints (e.g. crop yield, land-cover change). The Global-policy Module consists of a range of external parameters, which allow the exploration of alternative future pathways of LUCC, and which relate to attributes of both human and landscape agents. The ability to provide an integrated represen- tation of these components is one of the strengths of this approach, and its flexibility allows the upgrading and modification of processes where these have not yet been considered. The developed model was applied to a small-scale catchment in Upper East Ghana, the Atankwidi catchment, which covers an area of about 159 km2. Spatially explicit data were obtained from an ASTER image, digital maps, an extensiveland cover inventory and intensive household surveys. Field data were used to specify attributes and calibrate behavioral sub- models of households and land patches. Considered external factors were the policies of dam construction and credit access, demographic changes, and rainfall change. Simulation outputs consist of a spatially and temporally explicit land use/cover map, visual graphs, and export files of selected land-use and livelihood indicators. These convenient output visualization tools, together with the user-friendly interface of GH-LUDAS, allow stakeholders to simulate and analyze selected scenarios, which can serve as a basis for discussion and communication among stakeholders and policy-makers. Simulation results suggest that, among others, the policy of dam construction had much less effect on average annual income than that of credit provision, although it is the much more costly option in comparison to a credit scheme. Furthermore, a decline in annual rainfall seemed to trigger a shift towards cash cropping and non-farm activities, which could compensate for the losses in harvest caused by decreased precipitation. All simulated spatio- temporal data developed by these simulations can be used for further scientific analyses using GIS and statistical packages, thereby providing a basis for further understanding of local LUCC processes in Northern Ghana. KURZFASSUNG Ein agenten-basiertes Modell zur Simulierung von Landnutzungs- und Landbedeck- ungsänderungen im Einzugsgebiet des Atankwidi in Nordost-Ghana Landnutzungs- und Landbedeckungsänderungen, die die durch den Menschen verursachte Modifizierung der Landoberfläche der Erde bezeichnen, erfahren zunehmende Aufmerk- samkeit in der wissenschaftlichen Welt, aufgrund ihres weltweiten Ausmaßes und der Rolle, die sie für die Funktionsweise der Erde spielen. Zwischen einem Drittel und der Hälfte der Landoberfläche sind bereits durch menschliche Einflüsse verändert worden, wobei diese Änderungen wichtige Wechselbeziehungen mit ökologischen, ökonomischen und sozialen Prozessen und Problematiken aufweisen. Studien, die sich mit Landnutzungs- und Landbe- deckungsänderungen befassen, repräsentieren die Komplexität menschlicher Verhaltensweisen und ökologischer Bedingungen oft nur in unzureichender Weise. Viele Studien tendieren dazu, nur eine Komponente des ökologischen Systems, das aus menschlichen wie aus umweltbe- dingten Prozessen besteht, zu erfassen, und vernachlässigen dabei die Wechselbeziehungen zwischen diesen beiden Komponenten. Der agenten-basierte Modellierungsansatz hat die Fähigkeit, viele Eigenschaften von komplexen Systemen zu integrieren, und ermöglicht die Modellierung von Rückkopplungen, Wechselbeziehungen und skalen-abhängigen Prozessen des ökologischen Systems. In dieser Arbeit wurde ein agenten-basiertes Modell namens GH-LUDAS (Ghana - Land Use DynAmic Simulator) entwickelt, das Landnutzungs- und Landbedeckungsänderungen sowie zugehörige sozio-ökonomische Indikatoren in einem Flus- seinzugsgebiet des White Volta in Nord-Ghana simuliert. Das Ziel des Modells ist sowohl die Prognostizierung von Landbedeckungs-/Landnutzungsänderungen als auch die Evaluierung von möglichen Zukunftsverläufen unter gegebenen politischen Maßnahmen, demographis- chen Veränderungen sowie Klimawandel. Die Simulierung solcher Szenarien kann die Entschei- dungsfindungen lokaler Akteure bezüglich Landnutzung unterstützen und als Ausgangspunkt für Diskussionen unter lokalen Entscheidungsträgern dienen. Der agenten-basierte Modellansatz kennzeichnet sich durch die Modellierung der Aktionen und der Interaktionen einzelner Individuen (i.e. Agenten), deren Spezifikationen in komplexe Phänomene auf Systemebene resultieren. Agenten-basierte Modellierung kann daher als ein ’bottom-up approach’ bezeichnet werden, da die Systembeziehungen nicht auf oberster Ebene spezifiziert werden, sondern von den Prozessen zwischen einzelnen Agen- ten reguliert werden. Dieser Philosophie folgend, gliedert sich GH-LUDAS in vier Haupt- module. Das soziale Modul besteht aus einer Kollektion von menschlichen Agenten, die landwirtschaftliche Haushalte repräsentieren, und die mit einer Reihe von Attributen und Entscheidungsalgorithmen ausgestattet sind. Diese Algorithmen, die innerhalb des Entschei- dungmoduls spezifiziert sind, regulieren Reaktionen auf persönliche wie auf umweltbed- ingte Attribute und Prozesse. Das Umweltmodul besteht aus landschaftlichen Agenten, die aus Pixeln von 30 m x 30 m bestehen, und die mit eigenen Attributen sowie ökologischen Mechanismen, die auf menschliche Entscheidungen sowie auf natürliche Prozesse reagieren (z.B. Ernteertrag, Landbedeckungsänderungen), ausgestattet sind. Das globale Modul besteht aus einer Reihe von externen Parametern, die von Modellnutzern reguliert werden können, und die Attribute von menschlichen und landschaftlichen Agenten direkt beeinflussen. Die Fähigkeit, diese Komponenten zu verbinden und miteinander zu integrieren, ist eine der Stärken des agenten-basierten Ansatzes, und seine Flexibilität erlaubt die Integrierung von Prozessen, wo diese (noch) nicht berücksichtigt worden sind. Das Modell wurde speziell für das Flusseinzugsgebiet des Atankwidi in Nordost- Ghana entwickelt, das eine Fläche von etwa 159 km2 aufweist. Räumlich explizite Daten wurden auf der Basis eines ASTER Satellitenbildes, digitalen Karten, einer weiträumigen Be- standsaufnahme von Landbedeckung, und fokussierten Haushaltsbefragungen generiert. Auf diesen Felddaten basierend, wurden die Attribute sowie die
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