Design, implementation and application of a generic framework for integrated regional land-use modeling

Land use is a crucial link between human activities and the natural environment and one of the main driving forces of global environmental change. Large parts of the terrestrial land surface are used for agriculture, forestry, settlements and infrastructure. Given the importance of land use, it is essential to understand the multitude of influential factors and resulting land use patterns. An essential methodology to study and quantify such interactions is provided by the adoption of land-use models. By the application of land-use models, it is possible to analyze the complex structure of linkages and feedbacks and to also determine the relevance of driving forces. Modeling land use and land use changes has a long-term tradition. In particular on the regional scale, a variety of models for different regions and research questions has been created. Modeling capabilities grow with steady advances in computer technology, which on the one hand are driven by increasing computing power on the other hand by new methods in software development, e.g. object- and component-oriented architectures. In this thesis, SITE (Simulation of Terrestrial Environments), a novel framework for integrated regional sland-use modeling, will be introduced and discussed. Particular features of SITE are the notably extended capability to integrate models and the strict separation of application and implementation. These features enable efficient development, test and usage of integrated land-use models. On its system side, SITE provides generic data structures (grid, grid cells, attributes etc.) and takes over the responsibility for their administration. By means of a scripting language (Python) that has been extended by language features specific for land-use modeling, these data structures can be utilized and manipulated by modeling applications. The scripting language interpreter is embedded in SITE. The integration of sub models can be achieved via the scripting language or by usage of a generic interface provided by SITE. Furthermore, functionalities important for land-use modeling like model calibration, model tests and analysis support of simulation results have been integrated into the generic framework. During the implementation of SITE, specific emphasis was laid on expandability, maintainability and usability. Along with the modeling framework a land use model for the analysis of the stability of tropical rainforest margins was developed in the context of the collaborative research project STORMA (SFB 552). In a research area in Central Sulawesi, Indonesia, socio-environmental impacts of land-use changes were examined. SITE was used to simulate land-use dynamics in the historical period of 1981 to 2002. Analogous to that, a scenario that did not consider migration in the population dynamics, was analyzed. For the calculation of crop yields and trace gas emissions, the DAYCENT agro-ecosystem model was integrated. In this case study, it could be shown that land-use changes in the Indonesian research area could mainly be characterized by the expansion of agricultural areas at the expense of natural forest. For this reason, the situation had to be interpreted as unsustainable even though increased agricultural use implied economic improvements and higher farmers' incomes. Due to the importance of model calibration, it was explicitly addressed in the SITE architecture through the introduction of a specific component. The calibration functionality can be used by all SITE applications and enables largely automated model calibration. Calibration in SITE is understood as a process that finds an optimal or at least adequate solution for a set of arbitrarily selectable model parameters with respect to an objective function. In SITE, an objective function typically is a map comparison algorithm capable of comparing a simulation result to a reference map. Several map optimization and map comparison methodologies are available and can be combined. The STORMA land-use model was calibrated using a genetic algorithm for optimization and the figure of merit map comparison measure as objective function. The time period for the calibration ranged from 1981 to 2002. For this period, respective reference land-use maps were compiled. It could be shown, that an efficient automated model calibration with SITE is possible. Nevertheless, the selection of the calibration parameters required detailed knowledge about the underlying land-use model and cannot be automated. In another case study decreases in crop yields and resulting losses in income from coffee cultivation were analyzed and quantified under the assumption of four different deforestation scenarios. For this task, an empirical model, describing the dependence of bee pollination and resulting coffee fruit set from the distance to the closest natural forest, was integrated. Land-use simulations showed, that depending on the magnitude and location of ongoing forest conversion, pollination services are expected to decline continuously. This results in a reduction of coffee yields of up to 18% and a loss of net revenues per hectare of up to 14%. However, the study also showed that ecological and economic values can be preserved if patches of natural vegetation are conservated in the agricultural landscape. -----------------------------------------------------------------------

Conceptual knowledge discovery with frequent concept lattices

Knowledge discovery support environments include beside classical data analysis tools also data mining tools. For supporting both kinds of tools, a unified knowledge representation is needed. We show that concept lattices which are used as knowledge representation in Conceptual Information Systems can also be used for structuring the results of mining association rules. Vice versa, we use ideas of association rules for reducing the complexity of the visualization of Conceptual Information Systems.

Acquiring expert knowledge for the design of conceptual information systems

Conceptual Information Systems unfold the conceptual structure of data stored in relational databases. In the design phase of the system, conceptual hierarchies have to be created which describe different aspects of the data. In this paper, we describe two principal ways of designing such conceptual hierarchies, data driven design and theory driven design and discuss advantages and drawbacks. The central part of the paper shows how Attribute Exploration, a knowledge acquisition tool developped by B. Ganter can be applied for narrowing the gap between both approaches.

Conceptual knowledge discovery and data analysis

In this paper, we discuss Conceptual Knowledge Discovery in Databases (CKDD) in its connection with Data Analysis. Our approach is based on Formal Concept Analysis, a mathematical theory which has been developed and proven useful during the last 20 years. Formal Concept Analysis has led to a theory of conceptual information systems which has been applied by using the management system TOSCANA in a wide range of domains. In this paper, we use such an application in database marketing to demonstrate how methods and procedures of CKDD can be applied in Data Analysis. In particular, we show the interplay and integration of data mining and data analysis techniques based on Formal Concept Analysis. The main concern of this paper is to explain how the transition from data to knowledge can be supported by a TOSCANA system. To clarify the transition steps we discuss their correspondence to the five levels of knowledge representation established by R. Brachman and to the steps of empirically grounded theory building proposed by A. Strauss and J. Corbin.

Conceptual knowledge processing with formal concept analysis and ontologies

Among many other knowledge representations formalisms, Ontologies and Formal Concept Analysis (FCA) aim at modeling ‘concepts’. We discuss how these two formalisms may complement another from an application point of view. In particular, we will see how FCA can be used to support Ontology Engineering, and how ontologies can be exploited in FCA applications. The interplay of FCA and ontologies is studied along the life cycle of an ontology: (i) FCA can support the building of the ontology as a learning technique. (ii) The established ontology can be analyzed and navigated by using techniques of FCA. (iii) Last but not least, the ontology may be used to improve an FCA application.

Content aggregation on knowledge bases using graph clustering

Recently, research projects such as PADLR and SWAP have developed tools like Edutella or Bibster, which are targeted at establishing peer-to-peer knowledge management (P2PKM) systems. In such a system, it is necessary to obtain provide brief semantic descriptions of peers, so that routing algorithms or matchmaking processes can make decisions about which communities peers should belong to, or to which peers a given query should be forwarded. This paper proposes the use of graph clustering techniques on knowledge bases for that purpose. Using this clustering, we can show that our strategy requires up to 58% fewer queries than the baselines to yield full recall in a bibliographic P2PKM scenario.

Matter fluxes in mountain oases of Al Jabal Al Akhdar, Oman

Since 1970 when Sultan Qaboos bin Said Al Said took over power from this father, agriculture in Oman has undergone major transformations as a consequence of rapid population and economic growth. In this process groundwater extraction has dramatically increased to meet domestic and agricultural needs. Recently, the agro-ecosystem of ancient mountain oases of Oman have received greater attention as interest has grown to understand the causes of their often millennia old sustainable productivity. Particularly little is known about the carbon (C) and nutrient turnover in these intensive landuse systems. This is partly due to the difficulties to measure such processes in the often remote fields. To fill the existing gap of knowledge, field studies were conducted in five oases at different altitudes of Al Jabal Al Akhdar, the highest agricultural area in Oman, to determine C and nutrient fluxes as well as nutrient use efficiencies for two different cropping systems as affected by temperature, irrigation, and manure quality. The results of this study indicated that water scarcity as a result of low precipitation and an increase in urban water consumption is a major threat to the sustainability of agriculture in these oases. Optimizing the use of irrigation water is a major challenge for agriculture in these oases, particularly given ever increasing competition for this most limiting resource. Traditionally, farmers of these oases adapt to variation of irrigation water supply by minimizing the growing area of annual crops, leaving these areas uncultivated through drought seasons (Luedeling and Buerkert 2008). In this study, a remarkable reduction in annual crop area was observed in 2009 for all oases. Our results suggested that water scarcity as a result of low precipitation and the increase in urban water consumption cause such changes in land use. The data also underline the intensive C and nutrient turnover in the man-made irrigated agroecosystems and confirmed the importance of the large manure quantities applied continuously to the terraces as a key factor responsible for sustainable soil productivity. To trace the fate of C and plant nutrients that are released from the large amount of manure applied by oasis farmers, more detailed studies under controlled conditions, using isotope signatures, would be needed.

Sensorische Erfassung von Grünlandbiomassen als Grundlage für ein teilflächenspezifisches Management im Ökologischen Landbau

Vor dem Hintergund der Integration des wissensbasierten Managementsystems Precision Farming in den Ökologischen Landbau wurde die Umsetzung bestehender sowie neu zu entwickelnder Strategien evaluiert und diskutiert. Mit Blick auf eine im Precision Farming maßgebende kosteneffiziente Ertragserfassung der im Ökologischen Landbau flächenrelevanten Leguminosen-Grasgemenge wurden in zwei weiteren Beiträgen die Schätzgüten von Ultraschall- und Spektralsensorik in singulärer und kombinierter Anwendung analysiert. Das Ziel des Precision Farming, ein angepasstes Management bezogen auf die flächeninterne Variabilität der Standorte umzusetzen, und damit einer Reduzierung von Betriebsmitteln, Energie, Arbeit und Umwelteffekten bei gleichzeitiger Effektivitätssteigerung und einer ökonomischen Optimierung zu erreichen, deckt sich mit wesentlichen Bestrebungen im Ökogischen Landbau. Es sind vorrangig Maßnahmen zur Erfassung der Variabilität von Standortfaktoren wie Geländerelief, Bodenbeprobung und scheinbare elektrische Leitfähigkeit sowie der Ertragserfassung über Mähdrescher, die direkt im Ökologischen Landbau Anwendung finden können. Dagegen sind dynamisch angepasste Applikationen zur Düngung, im Pflanzenschutz und zur Beseitigung von Unkräutern aufgrund komplexer Interaktionen und eines eher passiven Charakters dieser Maßnahmen im Ökologischen Landbau nur bei Veränderung der Applikationsmodelle und unter Einbindung weiterer dynamischer Daten umsetzbar. Beispiele hiefür sind einzubeziehende Mineralisierungsprozesse im Boden und organischem Dünger bei der Düngemengenberechnung, schwer ortsspezifisch zuzuordnende präventive Maßnamen im Pflanzenschutz sowie Einflüsse auf bodenmikrobiologische Prozesse bei Hack- oder Striegelgängen. Die indirekten Regulationsmechanismen des Ökologischen Landbaus begrenzen daher die bisher eher auf eine direkte Wirkung ausgelegten dynamisch angepassten Applikationen des konventionellen Precision Farming. Ergänzend sind innovative neue Strategien denkbar, von denen die qualitätsbezogene Ernte, der Einsatz hochsensibler Sensoren zur Früherkennung von Pflanzenkrankheiten oder die gezielte teilflächen- und naturschutzorientierte Bewirtschaftung exemplarisch in der Arbeit vorgestellt werden. Für die häufig große Flächenanteile umfassenden Leguminosen-Grasgemenge wurden für eine kostengünstige und flexibel einsetzbare Ertragserfassung die Ultraschalldistanzmessung zur Charakterisierung der Bestandeshöhe sowie verschiedene spektrale Vegetationsindices als Schätzindikatoren analysiert. Die Vegetationsindices wurden aus hyperspektralen Daten nach publizierten Gleichungen errechnet sowie als „Normalized Difference Spectral Index“ (NDSI) stufenweise aus allen möglichen Wellenlängenkombinationen ermittelt. Die Analyse erfolgte für Ultraschall und Vegetationsindices in alleiniger und in kombinierter Anwendung, um mögliche kompensatorische Effekte zu nutzen. In alleiniger Anwendung erreichte die Ultraschallbestandeshöhe durchweg bessere Schätzgüten, als alle einzelnen Vegetationsindices. Bei den letztgenannten erreichten insbesondere auf Wasserabsorptionsbanden basierende Vegetationsindices eine höhere Schätzgenauigkeit als traditionelle Rot/Infrarot-Indices. Die Kombination beider Sensorda-ten ließ eine weitere Steigerung der Schätzgüte erkennen, insbesondere bei bestandesspezifischer Kalibration. Hierbei kompensieren die Vegetationsindices Fehlschätzungen der Höhenmessung bei diskontinuierlichen Bestandesdichtenänderungen entlang des Höhengradienten, wie sie beim Ährenschieben oder durch einzelne hochwachsende Arten verursacht werden. Die Kombination der Ultraschallbestandeshöhe mit Vegetationsindices weist das Potential zur Entwicklung kostengünstiger Ertragssensoren für Leguminosen-Grasgemenge auf. Weitere Untersuchungen mit hyperspektralen Vegetationsindices anderer Berechnungstrukturen sowie die Einbindung von mehr als zwei Wellenlängen sind hinsichtlich der Entwicklung höherer Schätzgüten notwendig. Ebenso gilt es, Kalibrierungen und Validationen der Sensorkombination im artenreichen Grasland durchzuführen. Die Ertragserfassung in den Leguminosen-Grasgemengen stellt einen wichtigen Beitrag zur Erstellung einer Ertragshistorie in den vielfältigen Fruchtfolgen des Ökologischen Landbaus dar und ermöglicht eine verbesserte Einschätzung von Produktionspotenzialen und Defizitarealen für ein standortangepasstes Management.

Indigenous Knowledge (IK) of Water Resources Management in West Sumatra, Indonesia

This study was aim to describe the indigenous knowledge of farmers at Nagari Padang laweh Malalo (NPLM) and their adaptability to climate change. Not only the water scarcity is feared, but climate change is also affecting their food security. Local food security can be achieved if biodiversity in their surrounding area is suitable to the local needs. The study was conducted by using Participatory Rural Appraisal (PRA) such as observation and discussion. The combination of in depth interview, life history, semi structure questionnaire, pictures, mapping and expert interviews was implemented. Data was analyzed by using MAXQDA 10 and F4 audio analysis software. The result shows awareness of the people and scarcity of water conditions has allowed the people of NPLM to face this challenge with wisdom. Aia adat (water resources controlled and regulate by custom) is one of their strategies to distribute the water. The general rule is that irrigation will flow from 6 pm – 6 am regularly to all farm land under supervision of kapalo banda. When rains occur, water resources can be used during the day without special supervision. They were used traditional knowledge to manage water resources for their land and daily usage. This study may be helpful for researcher and other farmers in different region to learn encounter water scarcity.