Agent Based Evacuation Simulation Using Leader-Follower Model

Agent based simulation is a widely developing area in artificial intelligence.The simulation studies are extensively used in different areas of disaster management. This work deals with the study of an agent based evacuation simulation which is being done to handle the various evacuation behaviors.Various emergent behaviors of agents are addressed here. Dynamic grouping behaviors of agents are studied. Collision detection and obstacle avoidances are also incorporated in this approach.Evacuation is studied with single exits and multiple exits and efficiency is measured in terms of evacuation rate, collision rate etc.Net logo is the tool used which helps in the efficient modeling of scenarios in evacuation

Unconstrained Handwritten Malayalam Character Recognition using Wavelet Transform and Support vector Machine Classifier

This paper presents the application of wavelet processing in the domain of handwritten character recognition. To attain high recognition rate, robust feature extractors and powerful classifiers that are invariant to degree of variability of human writing are needed. The proposed scheme consists of two stages: a feature extraction stage, which is based on Haar wavelet transform and a classification stage that uses support vector machine classifier. Experimental results show that the proposed method is effective

Using Neural Network Classifier Support Vector Machine Regression for the prediction of Melting Point of Drug – like compounds

In our study we use a kernel based classification technique, Support Vector Machine Regression for predicting the Melting Point of Drug – like compounds in terms of Topological Descriptors, Topological Charge Indices, Connectivity Indices and 2D Auto Correlations. The Machine Learning model was designed, trained and tested using a dataset of 100 compounds and it was found that an SVMReg model with RBF Kernel could predict the Melting Point with a mean absolute error 15.5854 and Root Mean Squared Error 19.7576

Quantile based entropy function

Quantile functions are efficient and equivalent alternatives to distribution functions in modeling and analysis of statistical data (see Gilchrist, 2000; Nair and Sankaran, 2009). Motivated by this, in the present paper, we introduce a quantile based Shannon entropy function. We also introduce residual entropy function in the quantile setup and study its properties. Unlike the residual entropy function due to Ebrahimi (1996), the residual quantile entropy function determines the quantile density function uniquely through a simple relationship. The measure is used to define two nonparametric classes of distributions

Quantile based reliability aspects of partial moments

Partial moments are extensively used in literature for modeling and analysis of lifetime data. In this paper, we study properties of partial moments using quantile functions. The quantile based measure determines the underlying distribution uniquely. We then characterize certain lifetime quantile function models. The proposed measure provides alternate definitions for ageing criteria. Finally, we explore the utility of the measure to compare the characteristics of two lifetime distributions

Enhancement of Calcifications in Mammograms using Volterra Series based Quadratic Filter

The paper summarizes the design and implementation of a quadratic edge detection filter, based on Volterra series, for enhancing calcifications in mammograms. The proposed filter can account for much of the polynomial nonlinearities inherent in the input mammogram image and can replace the conventional edge detectors like Laplacian, gaussian etc. The filter gives rise to improved visualization and early detection of microcalcifications, which if left undetected, can lead to breast cancer. The performance of the filter is analyzed and found superior to conventional spatial edge detectors

A New Fast Fractal Modeling Approach for the Detection of Microcalcifications in Mammograms

In this paper, a novel fast method for modeling mammograms by deterministic fractal coding approach to detect the presence of microcalcifications, which are early signs of breast cancer, is presented. The modeled mammogram obtained using fractal encoding method is visually similar to the original image containing microcalcifications, and therefore, when it is taken out from the original mammogram, the presence of microcalcifications can be enhanced. The limitation of fractal image modeling is the tremendous time required for encoding. In the present work, instead of searching for a matching domain in the entire domain pool of the image, three methods based on mean and variance, dynamic range of the image blocks, and mass center features are used. This reduced the encoding time by a factor of 3, 89, and 13, respectively, in the three methods with respect to the conventional fractal image coding method with quad tree partitioning. The mammograms obtained from The Mammographic Image Analysis Society database (ground truth available) gave a total detection score of 87.6%, 87.6%, 90.5%, and 87.6%, for the conventional and the proposed three methods, respectively.

Multifinger Feature Level Fusion Based Fingerprint Identification

Fingerprint based authentication systems are one of the cost-effective biometric authentication techniques employed for personal identification. As the data base population increases, fast identification/recognition algorithms are required with high accuracy. Accuracy can be increased using multimodal evidences collected by multiple biometric traits. In this work, consecutive fingerprint images are taken, global singularities are located using directional field strength and their local orientation vector is formulated with respect to the base line of the finger. Feature level fusion is carried out and a 32 element feature template is obtained. A matching score is formulated for the identification and 100% accuracy was obtained for a database of 300 persons. The polygonal feature vector helps to reduce the size of the feature database from the present 70-100 minutiae features to just 32 features and also a lower matching threshold can be fixed compared to single finger based identification

Design of a Knowledge-Based Geographic Information System

A GIS has been designed with limited Functionalities; but with a novel approach in Aits design. The spatial data model adopted in the design of KBGIS is the unlinked vector model. Each map entity is encoded separately in vector fonn, without referencing any of its neighbouring entities. Spatial relations, in other words, are not encoded. This approach is adequate for routine analysis of geographic data represented on a planar map, and their display (Pages 105-106). Even though spatial relations are not encoded explicitly, they can be extracted through the specially designed queries. This work was undertaken as an experiment to study the feasibility of developing a GIS using a knowledge base in place of a relational database. The source of input spatial data was accurate sheet maps that were manually digitised. Each identifiable geographic primitive was represented as a distinct object, with its spatial properties and attributes defined. Composite spatial objects, made up of primitive objects, were formulated, based on production rules defining such compositions. The facts and rules were then organised into a production system, using OPS5

Reliability Estimation of Open Source Software based Computational Systems

Software systems are progressively being deployed in many facets of human life. The implication of the failure of such systems, has an assorted impact on its customers. The fundamental aspect that supports a software system, is focus on quality. Reliability describes the ability of the system to function under specified environment for a specified period of time and is used to objectively measure the quality. Evaluation of reliability of a computing system involves computation of hardware and software reliability. Most of the earlier works were given focus on software reliability with no consideration for hardware parts or vice versa. However, a complete estimation of reliability of a computing system requires these two elements to be considered together, and thus demands a combined approach. The present work focuses on this and presents a model for evaluating the reliability of a computing system. The method involves identifying the failure data for hardware components, software components and building a model based on it, to predict the reliability. To develop such a model, focus is given to the systems based on Open Source Software, since there is an increasing trend towards its use and only a few studies were reported on the modeling and measurement of the reliability of such products. The present work includes a thorough study on the role of Free and Open Source Software, evaluation of reliability growth models, and is trying to present an integrated model for the prediction of reliability of a computational system. The developed model has been compared with existing models and its usefulness of is being discussed.

Study on period search methods of variable stars: Application to ASAS and CRTS databases

Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.

Air-gap based vertical cavity micro-opto-electro-mechanical Fabry-Perot filters

Mikrooptische Filter sind heutzutage in vielen Bereichen in der Telekommunikation unersetzlich. Wichtige Einsatzgebiete sind aber auch spektroskopische Systeme in der Medizin-, Prozess- und Umwelttechnik. Diese Arbeit befasst sich mit der Technologieentwicklung und Herstellung von luftspaltbasierenden, vertikal auf einem Substrat angeordneten, oberflächenmikromechanisch hergestellten Fabry-Perot-Filtern. Es werden zwei verschiedene Filtervarianten, basierend auf zwei verschiedenen Materialsystemen, ausführlich untersucht. Zum einen handelt es sich dabei um die Weiterentwicklung von kontinuierlich mikromechanisch durchstimmbaren InP / Luftspaltfiltern; zum anderen werden neuartige, kostengünstige Siliziumnitrid / Luftspaltfilter wissenschaftlich behandelt. Der Inhalt der Arbeit ist so gegliedert, dass nach einer Einleitung mit Vergleichen zu Arbeiten und Ergebnissen anderer Forschergruppen weltweit, zunächst einige theoretische Grundlagen zur Berechnung der spektralen Reflektivität und Transmission von beliebigen optischen Schichtanordnungen aufgezeigt werden. Auß erdem wird ein kurzer theoretischer Ü berblick zu wichtigen Eigenschaften von Fabry-Perot-Filtern sowie der Möglichkeit einer mikromechanischen Durchstimmbarkeit gegeben. Daran anschließ end folgt ein Kapitel, welches sich den grundlegenden technologischen Aspekten der Herstellung von luftspaltbasierenden Filtern widmet. Es wird ein Zusammenhang zu wichtigen Referenzarbeiten hergestellt, auf denen diverse Weiterentwicklungen dieser Arbeit basieren. Die beiden folgenden Kapitel erläutern dann ausführlich das Design, die Herstellung und die Charakterisierung der beiden oben erwähnten Filtervarianten. Abgesehen von der vorangehenden Epitaxie von InP / GaInAs Schichten, ist die Herstellung der InP / Luftspaltfilter komplett im Institut durchgeführt worden. Die Herstellungsschritte sind ausführlich in der Arbeit erläutert, wobei ein Schwerpunktthema das trockenchemische Ä tzen von InP sowie GaInAs, welches als Opferschichtmaterial für die Herstellung der Luftspalte genutzt wurde, behandelt. Im Verlauf der wissenschaftlichen Arbeit konnten sehr wichtige technische Verbesserungen entwickelt und eingesetzt werden, welche zu einer effizienteren technologischen Herstellung der Filter führten und in der vorliegenden Niederschrift ausführlich dokumentiert sind. Die hergestellten, für einen Einsatz in der optischen Telekommunikation entworfenen, elektrostatisch aktuierbaren Filter sind aus zwei luftspaltbasierenden Braggspiegeln aufgebaut, welche wiederum jeweils 3 InP-Schichten von (je nach Design) 357nm bzw. 367nm Dicke aufweisen. Die Filter bestehen aus im definierten Abstand parallel übereinander angeordneten Membranen, die über Verbindungsbrücken unterschiedlicher Anzahl und Länge an Haltepfosten befestigt sind. Da die mit 357nm bzw. 367nm vergleichsweise sehr dünnen Schichten freitragende Konstrukte mit bis zu 140 nm Länge bilden, aber trotzdem Positionsgenauigkeiten im nm-Bereich einhalten müssen, handelt es sich hierbei um sehr anspruchsvolle mikromechanische Bauelemente. Um den Einfluss der zahlreichen geometrischen Strukturparameter studieren zu können, wurden verschiedene laterale Filterdesigns implementiert. Mit den realisierten Filter konnte ein enorm weiter spektraler Abstimmbereich erzielt werden. Je nach lateralem Design wurden internationale Bestwerte für durchstimmbare Fabry-Perot-Filter von mehr als 140nm erreicht. Die Abstimmung konnte dabei kontinuierlich mit einer angelegten Spannung von nur wenigen Volt durchgeführt werden. Im Vergleich zu früher berichteten Ergebnissen konnten damit sowohl die Wellenlängenabstimmung als auch die dafür benötigte Abstimmungsspannung signifikant verbessert werden. Durch den hohen Brechungsindexkontrast und die geringe Schichtdicke zeigen die Filter ein vorteilhaftes, extrem weites Stopband in der Größ enordnung um 550nm. Die gewählten, sehr kurzen Kavitätslängen ermöglichen einen freien Spektralbereich des Filters welcher ebenfalls in diesen Größ enordnungen liegt, so dass ein weiter spektraler Einsatzbereich ermöglicht wird. Während der Arbeit zeigte sich, dass Verspannungen in den freitragenden InPSchichten die Funktionsweise der mikrooptischen Filter stark beeinflussen bzw. behindern. Insbesondere eine Unterätzung der Haltepfosten und die daraus resultierende Verbiegung der Ecken an denen sich die Verbindungsbrücken befinden, führte zu enormen vertikalen Membranverschiebungen, welche die Filtereigenschaften verändern. Um optimale Ergebnisse zu erreichen, muss eine weitere Verbesserung der Epitaxie erfolgen. Jedoch konnten durch den zusätzlichen Einsatz einer speziellen Schutzmaske die Unterätzung der Haltepfosten und damit starke vertikale Verformungen reduziert werden. Die aus der Verspannung resultierenden Verformungen und die Reaktion einzelner freistehender InP Schichten auf eine angelegte Gleich- oder Wechselspannung wurde detailliert untersucht. Mittels Weisslichtinterferometrie wurden lateral identische Strukturen verglichen, die aus unterschiedlich dicken InP-Schichten (357nm bzw. 1065nm) bestehen. Einen weiteren Hauptteil der Arbeit stellen Siliziumnitrid / Luftspaltfilter dar, welche auf einem neuen, im Rahmen dieser Dissertation entwickelten, technologischen Ansatz basieren. Die Filter bestehen aus zwei Braggspiegeln, die jeweils aus fünf 590nm dicken, freistehenden Siliziumnitridschichten aufgebaut sind und einem Abstand von 390nm untereinander aufweisen. Die Filter wurden auf Glassubstraten hergestellt. Der Herstellungsprozess ist jedoch auch mit vielen anderen Materialien oder Prozessen kompatibel, so dass z.B. eine Integration mit anderen Bauelemente relativ leicht möglich ist. Die Prozesse dieser ebenfalls oberflächenmikromechanisch hergestellten Filter wurden konsequent auf niedrige Herstellungskosten optimiert. Als Opferschichtmaterial wurde hier amorph abgeschiedenes Silizium verwendet. Der Herstellungsprozess beinhaltet die Abscheidung verspannungsoptimierter Schichten (Silizium und Siliziumnitrid) mittels PECVD, die laterale Strukturierung per reaktiven Ionenätzen mit den Gasen SF6 / CHF3 / Ar sowie Fotolack als Maske, die nasschemische Unterätzung der Opferschichten mittels KOH und das Kritisch-Punkt-Trocken der Proben. Die Ergebnisse der optischen Charakterisierung der Filter zeigen eine hohe Ü bereinstimmung zwischen den experimentell ermittelten Daten und den korrespondierenden theoretischen Modellrechnungen. Weisslichtinterferometermessungen der freigeätzten Strukturen zeigen ebene Filterschichten und bestätigen die hohe vertikale Positioniergenauigkeit, die mit diesem technologischen Ansatz erreicht werden kann.

Organic field-effect transistors and phototransistors based on amorphous materials

A comparison between the charge transport properties in low molecular amorphous thin films of spiro-linked compound and their corresponding parent compound has been demonstrated. The field-effect transistor method is used for extracting physical parameters such as field-effect mobility of charge carriers, ON/OFF ratios, and stability. In addition, phototransistors have been fabricated and demonstrated for the first time by using organic materials. In this case, asymmetrically spiro-linked compounds are used as active materials. The active materials used in this study can be divided into three classes, namely Spiro-linked compounds (symmetrically spiro-linked compounds), the corresponding parent-compounds, and photosensitive spiro-linked compounds (asymmetrically spiro-linked com-pounds). Some of symmetrically spiro-linked compounds used in this study were 2,2',7,7'-Tetrakis-(di-phenylamino)-9,9'-spirobifluorene (Spiro-TAD),2,2',7,7'-Tetrakis-(N,N'-di-p-methylphenylamino)-9,9'-spirobifluorene (Spiro-TTB), 2,2',7,7'-Tetra-(m-tolyl-phenylamino)-9,9'-spirobifluorene (Spiro-TPD), and 2,2Ž,7,7Ž-Tetra-(N-phenyl-1-naphtylamine)-9,9Ž-spirobifluorene (Spiro alpha-NPB). Related parent compounds of the symmetrically spiro-linked compound used in this study were N,N,N',N'-Tetraphenylbenzidine (TAD), N,N,N',N'-Tetrakis(4-methylphenyl)benzidine (TTB), N,N'-Bis(3-methylphenyl)-(1,1'-biphenyl)-4,4'-diamine (TPD), and N,N'-Diphenyl-N,N'-bis(1-naphthyl)-1,1'-biphenyl-4,4'-diamine (alpha-NPB). The photosensitive asymmetrically spiro-linked compounds used in this study were 2,7-bis-(N,N'-diphenylamino)-2',7'-bis(biphenyl-4-yl)-9,9'-spirobifluorene (Spiro-DPSP), and 2,7-bis-(N,N'-diphenylamino)-2',7'-bis(spirobifluorene-2-yl)-9,9'-spirobifluorene (Spiro-DPSP^2). It was found that the field-effect mobilities of charge carriers in thin films of symmetrically spiro-linked compounds and their corresponding parent compounds are in the same order of magnitude (~10^-5 cm^2/Vs). However, the thin films of the parent compounds were easily crystallized after the samples have been exposed in ambient atmosphere and at room temperature for three days. In contrast, the thin films and the transistor characteristics of symmetrically spiro-linked compound did not change significantly after the samples have been stored in ambient atmosphere and at room temperature for several months. Furthermore, temperature dependence of the mobility was analyzed in two models, namely the Arrhenius model and the Gaussian Disorder model. The Arrhenius model tends to give a high value of the prefactor mobility. However, it is difficult to distinguish whether the temperature behaviors of the material under consideration follows the Arrhenius model or the Gaussian Disorder model due to the narrow accessible range of the temperatures. For the first time, phototransistors have been fabricated and demonstrated by using organic materials. In this case, asymmetrically spiro-linked compounds are used as active materials. Intramolecular charge transfer between a bis(diphenylamino)biphenyl unit and a sexiphenyl unit leads to an increase in charge carrier density, providing the amplification effect. The operational responsivity of better than 1 A/W can be obtained for ultraviolet light at 370 nm, making the device interesting for sensor applications. This result offers a new potential application of organic thin film phototransistors as low-light level and low-cost visible blind ultraviolet photodetectors.

A Modeling Analysis of Changing Global Land Use as affected by Changing Demands for Wood Products

The 21st century has brought new challenges for forest management at a time when globalization in world trade is increasing and global climate change is becoming increasingly apparent. In addition to various goods and services like food, feed, timber or biofuels being provided to humans, forest ecosystems are a large store of terrestrial carbon and account for a major part of the carbon exchange between the atmosphere and the land surface. Depending on the stage of the ecosystems and/or management regimes, forests can be either sinks, or sources of carbon. At the global scale, rapid economic development and a growing world population have raised much concern over the use of natural resources, especially forest resources. The challenging question is how can the global demands for forest commodities be satisfied in an increasingly globalised economy, and where could they potentially be produced? For this purpose, wood demand estimates need to be integrated in a framework, which is able to adequately handle the competition for land between major land-use options such as residential land or agricultural land. This thesis is organised in accordance with the requirements to integrate the simulation of forest changes based on wood extraction in an existing framework for global land-use modelling called LandSHIFT. Accordingly, the following neuralgic points for research have been identified: (1) a review of existing global-scale economic forest sector models (2) simulation of global wood production under selected scenarios (3) simulation of global vegetation carbon yields and (4) the implementation of a land-use allocation procedure to simulate the impact of wood extraction on forest land-cover. Modelling the spatial dynamics of forests on the global scale requires two important inputs: (1) simulated long-term wood demand data to determine future roundwood harvests in each country and (2) the changes in the spatial distribution of woody biomass stocks to determine how much of the resource is available to satisfy the simulated wood demands. First, three global timber market models are reviewed and compared in order to select a suitable economic model to generate wood demand scenario data for the forest sector in LandSHIFT. The comparison indicates that the ‘Global Forest Products Model’ (GFPM) is most suitable for obtaining projections on future roundwood harvests for further study with the LandSHIFT forest sector. Accordingly, the GFPM is adapted and applied to simulate wood demands for the global forestry sector conditional on selected scenarios from the Millennium Ecosystem Assessment and the Global Environmental Outlook until 2050. Secondly, the Lund-Potsdam-Jena (LPJ) dynamic global vegetation model is utilized to simulate the change in potential vegetation carbon stocks for the forested locations in LandSHIFT. The LPJ data is used in collaboration with spatially explicit forest inventory data on aboveground biomass to allocate the demands for raw forest products and identify locations of deforestation. Using the previous results as an input, a methodology to simulate the spatial dynamics of forests based on wood extraction is developed within the LandSHIFT framework. The land-use allocation procedure specified in the module translates the country level demands for forest products into woody biomass requirements for forest areas, and allocates these on a five arc minute grid. In a first version, the model assumes only actual conditions through the entire study period and does not explicitly address forest age structure. Although the module is in a very preliminary stage of development, it already captures the effects of important drivers of land-use change like cropland and urban expansion. As a first plausibility test, the module performance is tested under three forest management scenarios. The module succeeds in responding to changing inputs in an expected and consistent manner. The entire methodology is applied in an exemplary scenario analysis for India. A couple of future research priorities need to be addressed, particularly the incorporation of plantation establishments; issue of age structure dynamics; as well as the implementation of a new technology change factor in the GFPM which can allow the specification of substituting raw wood products (especially fuelwood) by other non-wood products.

Modeling the interplay between land use, bioenergy production and climate change

Land use has become a force of global importance, considering that 34% of the Earth’s ice-free surface was covered by croplands or pastures in 2000. The expected increase in global human population together with eminent climate change and associated search for energy sources other than fossil fuels can, through land-use and land-cover changes (LUCC), increase the pressure on nature’s resources, further degrade ecosystem services, and disrupt other planetary systems of key importance to humanity. This thesis presents four modeling studies on the interplay between LUCC, increased production of biofuels and climate change in four selected world regions. In the first study case two new crop types (sugarcane and jatropha) are parameterized in the LPJ for managed Lands dynamic global vegetation model for calculation of their potential productivity. Country-wide spatial variation in the yields of sugarcane and jatropha incurs into substantially different land requirements to meet the biofuel production targets for 2015 in Brazil and India, depending on the location of plantations. Particularly the average land requirements for jatropha in India are considerably higher than previously estimated. These findings indicate that crop zoning is important to avoid excessive LUCC. In the second study case the LandSHIFT model of land-use and land-cover changes is combined with life cycle assessments to investigate the occurrence and extent of biofuel-driven indirect land-use changes (ILUC) in Brazil by 2020. The results show that Brazilian biofuels can indeed cause considerable ILUC, especially by pushing the rangeland frontier into the Amazonian forests. The carbon debt caused by such ILUC would result in no carbon savings (from using plant-based ethanol and biodiesel instead of fossil fuels) before 44 years for sugarcane ethanol and 246 years for soybean biodiesel. The intensification of livestock grazing could avoid such ILUC. We argue that such an intensification of livestock should be supported by the Brazilian biofuel sector, based on the sector’s own interest in minimizing carbon emissions. In the third study there is the development of a new method for crop allocation in LandSHIFT, as influenced by the occurrence and capacity of specific infrastructure units. The method is exemplarily applied in a first assessment of the potential availability of land for biogas production in Germany. The results indicate that Germany has enough land to fulfill virtually all (90 to 98%) its current biogas plant capacity with only cultivated feedstocks. Biogas plants located in South and Southwestern (North and Northeastern) Germany might face more (less) difficulties to fulfill their capacities with cultivated feedstocks, considering that feedstock transport distance to plants is a crucial issue for biogas production. In the fourth study an adapted version of LandSHIFT is used to assess the impacts of contrasting scenarios of climate change and conservation targets on land use in the Brazilian Amazon. Model results show that severe climate change in some regions by 2050 can shift the deforestation frontier to areas that would experience low levels of human intervention under mild climate change (such as the western Amazon forests or parts of the Cerrado savannas). Halting deforestation of the Amazon and of the Brazilian Cerrado would require either a reduction in the production of meat or an intensification of livestock grazing in the region. Such findings point out the need for an integrated/multicisciplinary plan for adaptation to climate change in the Amazon. The overall conclusions of this thesis are that (i) biofuels must be analyzed and planned carefully in order to effectively reduce carbon emissions; (ii) climate change can have considerable impacts on the location and extent of LUCC; and (iii) intensification of grazing livestock represents a promising venue for minimizing the impacts of future land-use and land-cover changes in Brazil.