Joseph L. Awange - Böcker

This second edition of Mathematical Geosciences book adds five new topics: Solution equations with uncertainty, which proposes two novel methods for solving nonlinear geodetic equations as stochastic variables when the parameters of these equations have uncertainty characterized by probability distribution.

This second edition of Mathematical Geosciences book adds five new topics: Solution equations with uncertainty, which proposes two novel methods for solving nonlinear geodetic equations as stochastic variables when the parameters of these equations have uncertainty characterized by probability distribution.

This book provides numerous examples of linear and nonlinear model applications. Here, we present a nearly complete treatment of the Grand Universe of linear and weakly nonlinear regression models within the first 8 chapters. Our point of view is both an algebraic view and a stochastic one. For example, there is an equivalent lemma between a best, linear uniformly unbiased estimation (BLUUE) in a Gauss–Markov model and a least squares solution (LESS) in a system of linear equations. While BLUUE is a stochastic regression model, LESS is an algebraic solution. In the first six chapters, we concentrate on underdetermined and overdetermined linear systems as well as systems with a datum defect. We review estimators/algebraic solutions of type MINOLESS, BLIMBE, BLUMBE, BLUUE, BIQUE, BLE, BIQUE, and total least squares. The highlight is the simultaneous determination of the first moment and the second central moment of a probability distribution in an inhomogeneous multilinear estimationby the so-called E-D correspondence as well as its Bayes design. In addition, we discuss continuous networks versus discrete networks, use of Grassmann–Plucker coordinates, criterion matrices of type Taylor–Karman as well as FUZZY sets. Chapter seven is a speciality in the treatment of an overjet. This second edition adds three new chapters:(1)  Chapter on integer least squares that covers (i) model for positioning as a mixed integer linear  model which includes integer parameters. (ii) The general integer least squares problem is formulated, and the optimality of the least squares solution  is shown. (iii) The relation to the closest vector problem is considered, and the notion of reduced lattice basis is introduced. (iv) The famous LLL algorithm for generating a Lovasz reduced basis is explained.(2) Bayes methods  that covers (i) general principle of Bayesian modeling. Explain the notion of prior distribution and posterior distribution. Choose the pragmatic approach  for exploring the advantages of iterative Bayesian calculations and hierarchical modeling. (ii) Present the Bayes methods for linear models with normal distributed errors, including noninformative priors, conjugate priors, normal gamma distributions and (iii) short outview to modern application of Bayesian modeling. Useful in case of nonlinear models or linear models with no normal distribution: Monte Carlo (MC), Markov chain Monte Carlo (MCMC), approximative Bayesian computation (ABC)  methods.(3) Error-in-variables models, which cover: (i) Introduce the error-in-variables (EIV) model, discuss the difference to least squares estimators (LSE), (ii) calculate the total least squares (TLS) estimator. Summarize the properties of TLS, (iii) explain the idea of simulation extrapolation (SIMEX) estimators, (iv) introduce the symmetrized SIMEX (SYMEX) estimator and its relation to TLS, and (v) short outview to nonlinear EIV models. The chapter onalgebraic solution of nonlinear system of equations has also been updated in line with the new emerging field of hybrid numeric-symbolic solutions to systems of nonlinear equations, ermined system of nonlinear equations on curved manifolds. The von Mises–Fisher distribution is characteristic for circular or (hyper) spherical data. Our last chapter is devoted to probabilistic regression, the special Gauss–Markov model with random effects leading to estimators of type BLIP and VIP including Bayesian estimation. A great part of the work is presented in four appendices. Appendix A is a treatment, of tensor algebra, namely linear algebra, matrix algebra, and multilinear algebra. Appendix B is devoted to sampling distributions and their use in terms of confidence intervals and confidence regions. Appendix C reviews the elementary notions of statistics, namely random events and stochastic processes. Appendix D introduces the basics of Groebner basis algebra, its careful definition, the Buchberger algorithm, especially the C. F. Gauss combinatorial algorithm.

This book provides numerous examples of linear and nonlinear model applications. Here, we present a nearly complete treatment of the Grand Universe of linear and weakly nonlinear regression models within the first 8 chapters. Our point of view is both an algebraic view and a stochastic one. For example, there is an equivalent lemma between a best, linear uniformly unbiased estimation (BLUUE) in a Gauss–Markov model and a least squares solution (LESS) in a system of linear equations. While BLUUE is a stochastic regression model, LESS is an algebraic solution. In the first six chapters, we concentrate on underdetermined and overdetermined linear systems as well as systems with a datum defect. We review estimators/algebraic solutions of type MINOLESS, BLIMBE, BLUMBE, BLUUE, BIQUE, BLE, BIQUE, and total least squares. The highlight is the simultaneous determination of the first moment and the second central moment of a probability distribution in an inhomogeneous multilinear estimationby the so-called E-D correspondence as well as its Bayes design. In addition, we discuss continuous networks versus discrete networks, use of Grassmann–Plucker coordinates, criterion matrices of type Taylor–Karman as well as FUZZY sets. Chapter seven is a speciality in the treatment of an overjet. This second edition adds three new chapters:(1)  Chapter on integer least squares that covers (i) model for positioning as a mixed integer linear  model which includes integer parameters. (ii) The general integer least squares problem is formulated, and the optimality of the least squares solution  is shown. (iii) The relation to the closest vector problem is considered, and the notion of reduced lattice basis is introduced. (iv) The famous LLL algorithm for generating a Lovasz reduced basis is explained.(2) Bayes methods  that covers (i) general principle of Bayesian modeling. Explain the notion of prior distribution and posterior distribution. Choose the pragmatic approach  for exploring the advantages of iterative Bayesian calculations and hierarchical modeling. (ii) Present the Bayes methods for linear models with normal distributed errors, including noninformative priors, conjugate priors, normal gamma distributions and (iii) short outview to modern application of Bayesian modeling. Useful in case of nonlinear models or linear models with no normal distribution: Monte Carlo (MC), Markov chain Monte Carlo (MCMC), approximative Bayesian computation (ABC)  methods.(3) Error-in-variables models, which cover: (i) Introduce the error-in-variables (EIV) model, discuss the difference to least squares estimators (LSE), (ii) calculate the total least squares (TLS) estimator. Summarize the properties of TLS, (iii) explain the idea of simulation extrapolation (SIMEX) estimators, (iv) introduce the symmetrized SIMEX (SYMEX) estimator and its relation to TLS, and (v) short outview to nonlinear EIV models. The chapter onalgebraic solution of nonlinear system of equations has also been updated in line with the new emerging field of hybrid numeric-symbolic solutions to systems of nonlinear equations, ermined system of nonlinear equations on curved manifolds. The von Mises–Fisher distribution is characteristic for circular or (hyper) spherical data. Our last chapter is devoted to probabilistic regression, the special Gauss–Markov model with random effects leading to estimators of type BLIP and VIP including Bayesian estimation. A great part of the work is presented in four appendices. Appendix A is a treatment, of tensor algebra, namely linear algebra, matrix algebra, and multilinear algebra. Appendix B is devoted to sampling distributions and their use in terms of confidence intervals and confidence regions. Appendix C reviews the elementary notions of statistics, namely random events and stochastic processes. Appendix D introduces the basics of Groebner basis algebra, its careful definition, the Buchberger algorithm, especially the C. F. Gauss combinatorial algorithm.

This second edition of the book presents Artificial Intelligence (AI)-based Lake Victoria Basin (LVB)’s water monitoring products that stretches over 50 years from the Gravity Recovery and Climate Exchange (GRACE) and its Follow-on (GRACE-FO) satellite missions, investigates the lake's floating islands that disrupts power production, analyses LVB's groundwater, and unravels the causes of the 2018-2019 rise of its water level.In a unique cross-disciplinary approach, the book articulates the various climatic impacts and explanations from natural and anthropogenic origins, which affected Lake Victoria and its vicinity, including the drastic increase and depletion of water level in the Lake and dams, floods and droughts, water quality/security, crop health, food security, and economic implications. The book is recommended for readers from a diverse discipline, including physical and social sciences, policy, law, engineering, and disaster management. Professor C.K. Shum, Ohio State University.

It is unique in that it clearly distinguishes between environmental project management (EnvPM) and green project management (GreenPM), and presents an amalgamation of environmental management and project management concepts, using geospatial methods to form an EnvPM concept.

It is unique in that it clearly distinguishes between environmental project management (EnvPM) and green project management (GreenPM), and presents an amalgamation of environmental management and project management concepts, using geospatial methods to form an EnvPM concept.

The course has been designed to run over about 6 weeks of a semester, providing a half unit load which complements a computer aided design (CAD) based design project.

This book showcases powerful new hybrid methods that combine numerical and symbolic algorithms.

Recently, there has been, and continues to be, a tremendous interest on Lake Victoria and its environs, both locally and internationally. A casual browsing on the Internet indicates that the entries on the Lake have been rising phenomenally. At the same time, the issues discussed are as diverse as they are varied in their treatment of the subject, both in terms of depth and comprehensiveness. The information on Lake Victoria and its environ is scattered, isolated, and sometimes confusing even though documentation on the subject are available. Despite this situation, the fact remains that various people (e. g. , secondary and universitystudents,researchers,practitioners,etc. ,)wouldliketoaccess and know more about the Lake and its environs. Aware of the existing information gap about this world’s second largest fresh water Lake, this book is intended to provide readers with up-to-date information pertaining the Lake. The book gives an in-depth coverage of environmental issues, - source endowment, poverty amidst plenty, development opportunities, challenges and other related issues facing the Lake and its environs. It aims at providing information on the above variables, which hopefully will address the needs of various users. We have attempted to present the materials in a simple and straight forward way that will be und- standable to undergraduate students as well as advanced researchers. YetweareawarethatmostparametersoftheLakearechangingrapidly. We have therefore attempted to provide as accurate and up-to-date - formation up to the time of publishing.

East African states have historically shared several resources including energy and common heritage of its people. This book provides information on available sources of energy in the region and how the energy suppliers can exploit them in an integrated form to produce the right blend of energy for various applications e.g., industrial, domestic and recreational uses. We provide an in-depth analysis of the advantages and disadvantages of different energy sources in-terms of environmental, industrialization, distribution costs and impacts. We hope that the book will contribute towards a sustainable exploitation of energy resources for the improvement of the people’s quality of life.

Recently, there has been, and continues to be, a tremendous interest on Lake Victoria and its environs, both locally and internationally. A casual browsing on the Internet indicates that the entries on the Lake have been rising phenomenally. At the same time, the issues discussed are as diverse as they are varied in their treatment of the subject, both in terms of depth and comprehensiveness. The information on Lake Victoria and its environ is scattered, isolated, and sometimes confusing even though documentation on the subject are available. Despite this situation, the fact remains that various people (e. g. , secondary and universitystudents,researchers,practitioners,etc. ,)wouldliketoaccess and know more about the Lake and its environs. Aware of the existing information gap about this world’s second largest fresh water Lake, this book is intended to provide readers with up-to-date information pertaining the Lake. The book gives an in-depth coverage of environmental issues, - source endowment, poverty amidst plenty, development opportunities, challenges and other related issues facing the Lake and its environs. It aims at providing information on the above variables, which hopefully will address the needs of various users. We have attempted to present the materials in a simple and straight forward way that will be und- standable to undergraduate students as well as advanced researchers. YetweareawarethatmostparametersoftheLakearechangingrapidly. We have therefore attempted to provide as accurate and up-to-date - formation up to the time of publishing.

East African states have historically shared several resources including energy and common heritage of its people. This book provides information on available sources of energy in the region and how the energy suppliers can exploit them in an integrated form to produce the right blend of energy for various applications e.g., industrial, domestic and recreational uses. We provide an in-depth analysis of the advantages and disadvantages of different energy sources in-terms of environmental, industrialization, distribution costs and impacts. We hope that the book will contribute towards a sustainable exploitation of energy resources for the improvement of the people’s quality of life.

This book reviews the key conceptions and economic theories of poverty, explains poverty-environment nexus, and finally offers innovative socio-economic and scientific geospatial solutions for the 21st Century.  The book makes it possible for our readers to understand poverty thorough a concise review of the major theoretical economic frameworks, measures of poverty, and points out the need to understand rural-urban dichotomy of poverty. We find the theories and measures to be less-than perfect and therefore point out the need to treat these measures and theories as convenient tools lacking perfect accuracy and utmost scientific reliability. It follows then that the supposedly knowledgeably crafted poverty reduction and environmental preservation solutions are inherently imperfect.The economic solutions proposed in this book transcend extant humdrum macroeconomic and policy measures targeting poverty and environmental issues. We point to a new paradigm in which private sector and other stakeholders can create new and inclusive markets where value is co-created and shared. Above all, this book offers timely state-of-the-art geospatial solutions targeting the most pressing global problems of water, e.g., the use of the Gravity Recovery and Climate Experiment (GRACE) missions to estimate changes in stored water in the water-poverty-environment nexus, pollution, agriculture and disaster management, where geospatial techniques are appliedunder strong environmental impact assessment regulatory regimes. This book provides a good summary of economic theories of poverty as well as a vivid depiction of the state of environmental degradation in the world. People often work separately on different issues that are, in fact, closely intertwined. The principle of holism is that the whole is greater than the sum of its parts, and I believe that this joint-venture of two experts on poverty and environment has produced something more than a sum of two separate monographs on the issues. Various points raised in this volume are worth heeding when we think of formulation and implementation of a truly effective post-MDGs development agenda.Yoichi Mine, Professor of Human Security and African Area Study, Graduate School of Global Studies, Doshisha University, Japan

While preparing and teaching ‘Introduction to Geodesy I and II’ to undergraduate students at Stuttgart University, we noticed a gap which motivated the writing of the present book: Almost every topic that we taught required some skills in algebra, and in particular, computer algebra! From positioning to transformation problems inherent in geodesy and geoinformatics, knowledge of algebra and application of computer algebra software were required. In preparing this book therefore, we have attempted to put together basic concepts of abstract algebra which underpin the techniques for solving algebraic problems. Algebraic computational algorithms useful for solving problems which require exact solutions to nonlinear systems of equations are presented and tested on various problems. Though the present book focuses mainly on the two ?elds, the concepts and techniques presented herein are nonetheless applicable to other ?elds where algebraic computational problems might be encountered. In Engineering for example, network densi?cation and robotics apply resection and intersection techniques which require algebraic solutions. Solution of nonlinear systems of equations is an indispensable task in almost all geosciences such as geodesy, geoinformatics, geophysics (just to mention but a few) as well as robotics. These equations which require exact solutions underpin the operations of ranging, resection, intersection and other techniques that are normally used. Examples of problems that require exact solutions include; • three-dimensional resection problem for determining positions and orientation of sensors, e. g. , camera, theodolites, robots, scanners etc.

Here we present a nearly complete treatment of the Grand Universe of linear and weakly nonlinear regression models within the first 8 chapters. Our point of view is both an algebraic view as well as a stochastic one. For example, there is an equivalent lemma between a best, linear uniformly unbiased estimation (BLUUE) in a Gauss-Markov model and a least squares solution (LESS) in a system of linear equations. While BLUUE is a stochastic regression model, LESS is an algebraic solution. In the first six chapters we concentrate on underdetermined and overdeterimined linear systems as well as systems with a datum defect. We review estimators/algebraic solutions of type MINOLESS, BLIMBE, BLUMBE, BLUUE, BIQUE, BLE, BIQUE and Total Least Squares. The highlight is the simultaneous determination of the first moment and the second central moment of a probability distribution in an inhomogeneous multilinear estimation by the so called E-D correspondence as well as its Bayes design. In addition, we discuss continuous networks versus discrete networks, use of Grassmann-Pluecker coordinates, criterion matrices of type Taylor-Karman as well as FUZZY sets. Chapter seven is a speciality in the treatment of an overdetermined system of nonlinear equations on curved manifolds. The von Mises-Fisher distribution is characteristic for circular or (hyper) spherical data. Our last chapter eight is devoted to probabilistic regression, the special Gauss-Markov model with random effects leading to estimators of type BLIP and VIP including Bayesian estimation.A great part of the work is presented in four Appendices. Appendix A is a treatment, of tensor algebra, namely linear algebra, matrix algebra and multilinear algebra. Appendix B is devoted to sampling distributions and their use in terms of confidence intervals and confidence regions. Appendix C reviews the elementary notions of statistics, namely random events and stochastic processes. Appendix D introduces the basics of Groebner basis algebra, its careful definition, the Buchberger Algorithm, especially the C. F. Gauss combinatorial algorithm.

Global Navigation Satellite Systems (GNSS) are revolutionizing the world in a way their original developers never envisaged.  From being military “war” tools, GNSS satellites are rapidly becoming “peace” tools that play a potentially critical role in enabling changing environmental phenomenon that do not permit direct measurements to be remotely observed via their all-weather, highly accurate and continuously updatable positional time series.  This is evident, for example, in their use in emerging environmental monitoring methods that are considered in this book. These include: GPS-based radio telemetry, which is enhancing ecological and conservation monitoring by more accurately mapping animal movements, their behaviours, and  their impact on the environment; GNSS-meteorology, which is contributing to weather and climate change studies;  GNSS-remote sensing, which, for example, allows the rapid monitoring of changes in fresh water resources and cryosphere; Geosensor network techniques, which are earning a crucial role in disaster response management; Epidemiology, for improved efficiency in tracking and studying the spread of infectious diseases and climate change effects on vector-borne diseases; and Economics, to provide data for the econometric modelling of  casual impact of policies. In Environmental Impact Assessments (EIA), Strategic Environmental Assessments (SEA), and Sustainability Assessments (SA), GNSS, together with other spaced-based remote sensing techniques, are emerging, not only as modern tools that connect the developers to the community, but also provide information that support Multi-Criteria Analysis (MCA) methods, which inform decision making and policy formulations. By bringing the two fields of geodesy (the parent of GNSS technology) and environmental studies (potential users of this technology), this bookpresents the concepts of GNSS in a simplified way that can, on the one hand, be understood and utilised by environmentalists, while on the other, outlines its potential applications to environmental monitoring and management for those engaged more with its technology, which hopefully will further energise the already innovative research that is being carried out.  Lastly, this book is most relevant to all the professionals whose work is related to the environment such as hydrologists, meteorologists, epidemiologists, economist, and engineers, to name just a few.A comprehensive yet candid and compelling presentation of Global Navigation Satellite Systems and its application to environmental monitoring and a host of other socio-economic activities. This is an essential and new ground breaking reading for all professional practitioners and even academics seeking to study and become involved in using Global Navigation Satellite Systems in diverse fields ranging from environmental monitoring to economic activities such as monitoring weather and climate in order to design crop failure insurance. Nathaniel O. Agola, Professor of Business and Financial Economics, Ritsumeikan University, Japan