Statistical Methods For Spatial Planning And Monitoring

The book aims to investigate methods and techniques for spatial statistical analysis suitable to model spatial information in support of decision systems. Over the last few years there has been a considerable interest in these tools and in the role they can play in spatial planning and environmental modelling. One of the earliest and most famous definition of spatial planning was “a geographical expression to the economic, social, cultural and ecological policies of society”: borrowing from this point of view, this text shows how an interdisciplinary approach is an effective way to an harmonious integration of national policies with regional and local analysis. A wide range of spatial models and techniques is, also, covered: spatial data mining, point processes analysis, nearest neighbor statistics and cluster detection, Fuzzy Regression model and local indicators of spatial association; all of these tools provide the policy-maker with a valuable support to policy development.

Understanding spatial statistics requires tools from applied and mathematical statistics, linear model theory, regression, time series, and stochastic processes. It also requires a mindset that focuses on the unique characteristics of spatial data and the development of specialized analytical tools designed explicitly for spatial data analysis. Statistical Methods for Spatial Data Analysis answers the demand for a text that incorporates all of these factors by presenting a balanced exposition that explores both the theoretical foundations of the field of spatial statistics as well as practical methods for the analysis of spatial data. This book is a comprehensive and illustrative treatment of basic statistical theory and methods for spatial data analysis, employing a model-based and frequentist approach that emphasizes the spatial domain. It introduces essential tools and approaches including: measures of autocorrelation and their role in data analysis; the background and theoretical framework supporting random fields; the analysis of mapped spatial point patterns; estimation and modeling of the covariance function and semivariogram; a comprehensive treatment of spatial analysis in the spectral domain; and spatial prediction and kriging. The volume also delivers a thorough analysis of spatial regression, providing a detailed development of linear models with uncorrelated errors, linear models with spatially-correlated errors and generalized linear mixed models for spatial data. It succinctly discusses Bayesian hierarchical models and concludes with reviews on simulating random fields, non-stationary covariance, and spatio-temporal processes. Additional material on the CRC Press website supplements the content of this book. The site provides data sets used as examples in the text, software code that can be used to implement many of the principal methods described and illustrated, and updates to the text itself.

This book discusses a broad range of statistical design and analysis methods that are particularly well suited to pollution data. It explains key statistical techniques in easy-to-comprehend terms and uses practical examples, exercises, and case studies to illustrate procedures. Dr. Gilbert begins by discussing a space-time framework for sampling pollutants. He then shows how to use statistical sample survey methods to estimate average and total amounts of pollutants in the environment, and how to determine the number of field samples and measurements to collect for this purpose. Then a broad range of statistical analysis methods are described and illustrated. These include: * determining the number of samples needed to find hot spots * analyzing pollution data that are lognormally distributed * testing for trends over time or space * estimating the magnitude of trends * comparing pollution data from two or more populations New areas discussed in this sourcebook include statistical techniques for data that are correlated, reported as less than the measurement detection limit, or obtained from field-composited samples. Nonparametric statistical analysis methods are emphasized since parametric procedures are often not appropriate for pollution data. This book also provides an illustrated comprehensive computer code for nonparametric trend detection and estimation analyses as well as nineteen statistical tables to permit easy application of the discussed statistical techniques. In addition, many publications are cited that deal with the design of pollution studies and the statistical analysis of pollution data. This sourcebook will be a useful tool for applied statisticians, ecologists, radioecologists, hydrologists, biologists, environmental engineers, and other professionals who deal with the collection, analysis, and interpretation of pollution in air, water, and soil.

This book is a collection of original research papers that focus on recent developments in Spatial Analysis and Modelling with direct relevance to settlements and infrastructure. Topics include new types of data (such as simulation data), applications of methods to support decision-making, and investigations of human-environment data in order to recognize significance for structures, functions and processes of attributes. Research incorporated ranges from theoretical through methodological to applied work. It is subdivided into four main parts: the first focusing on the research of settlements and infrastructure, the second studies aspects of Geographic Data Mining, the third presents contributions in the field of Spatial Modelling, System Dynamics and Geosimulation, and the fourth part is dedicated to Multi-Scale Representation and Analysis. The book is valuable to those with a scholarly interest in spatial sciences, urban and spatial planning, as well as anyone interested in spatial analysis and the planning of human settlements and infrastructure. Most of the selected papers were originally presented at the “International Land Use Symposium (ILUS 2015): Trends in Spatial Analysis and Modelling of Settlements and Infrastructure” November 11-13 2015, in Dresden, Germany.

In September 1977 a "Regional Science Symposium" was held at the Faculty of Economics of the University of Goningen in the Netherlands. The impetus in organizing this symposium was the recent estab lishmen t at the F acuIty of Economics of a group engaged in teaching and research within the field of regional science. The aim of the symposium was to familiarize university members with regional science and to introduce the new group to both the national and international scene. Two separate topics of potential interest to both researchers and policy-makers were selected. The first theme, spatial inequalities and regional development, was chosen because of its central place in regional science. Authors from several disciplines were asked to approach this theme from a general, policy-oriented point of view. This ensured the spotlighting of the various dimensions of spatial inequality and its implications for regional policy. The results of their efforts have been collected in a volume entitled Spatial Inequalities and Regional Development. The second theme focussed on spatial statistical analysis. This branch of statistics is a relatively new one. It is receiving growing attention from researchers in the field of applied regional science. The conference dealing with this topic concentrated on recent research results related to the use of appropriate statistical and econometric methods for analyzing spatial data. The papers con cerned have been collected in another volume, entitled Exploratory and Explanatory Statistical Analysis of Spatial Data.

This book addresses challenges and opportunities in the Energy-Water-Environment (EWE) nexus, with a particular focus on research and technology development requirements in harsh desert climates. Its chapters include selected contributions presented during the 1st international conference on sustainable Energy-Water-Environment nexus in desert climates (ICSEWEN-19) held at the Qatar Environment and Energy Research Institute (QEERI) in Doha, Qatar in December 2019. This volume is comprised of three main chapters, each describing important case studies and progress on water, energy and environmental questions. A fourth chapter on policies and community outreach on these three areas is also included. This compilation aims to bridge the gap between research and industry to address the socioeconomic impacts of the nexus imbalance as perceived by scientists, industrial partners, and policymakers. The content of this book is of particular importance to graduate students, researchers and decision makers interested in understanding water, energy and environmental challenges in arid areas. Re searchers in environmental and civil engineering, chemistry, hydrology and environmental science can also find unique in-situ observations of the current nexus imbalance in deserts climate to validate their investigations. It is also an invaluable guide for industry professionals working in water, energy, environment and food sectors to understand the rapidly evolving landscape of the EWE nexus in arid areas. The analyses, observations and lessons-learned summarized herein are applicable to other arid areas outside North Africa and the Arabian Peninsula as well, such as central Australia, the southwest of the United States and deserts in central Asia.

At 5 percent, Canada’s population growth was the highest of all G7 countries when the most recent census was taken. But only a handful of large cities drove that growth, attracting human and monetary capital from across the country and leaving myriad social, economic, and environmental challenges behind. Quietly Shrinking Cities investigates this trend and the practical challenges associated with population loss in smaller urban centres. Maxwell Hartt meticulously demonstrates that shrinking cities need to rethink their planning and development strategies in response to a new demographic reality, questioning whether population loss and prosperity are indeed mutually exclusive.

New powerful technologies, such as geographic information systems (GIS), have been evolving and are quickly becoming part of a worldwide emergent digital infrastructure. Spatial analysis is becoming more important than ever because enormous volumes of spatial data are available from different sources, such as social media and mobile phones. When locational information is provided, spatial analysis researchers can use it to calculate statistical and mathematical relationships through time and space. This book aims to demonstrate how computer methods of spatial analysis and modeling, integrated in a GIS environment, can be used to better understand reality and give rise to more informed and, thus, improved planning. It provides a comprehensive discussion of spatial analysis, methods, and approaches related to planning.

The Handbook is written for academics, researchers, practitioners and advanced graduate students. It has been designed to be read by those new or starting out in the field of spatial analysis as well as by those who are already familiar with the field. The chapters have been written in such a way that readers who are new to the field will gain important overview and insight. At the same time, those readers who are already practitioners in the field will gain through the advanced and/or updated tools and new materials and state-of-the-art developments included. This volume provides an accounting of the diversity of current and emergent approaches, not available elsewhere despite the many excellent journals and te- books that exist. Most of the chapters are original, some few are reprints from the Journal of Geographical Systems, Geographical Analysis, The Review of Regional Studies and Letters of Spatial and Resource Sciences. We let our contributors - velop, from their particular perspective and insights, their own strategies for m- ping the part of terrain for which they were responsible. As the chapters were submitted, we became the first consumers of the project we had initiated. We gained from depth, breadth and distinctiveness of our contributors’ insights and, in particular, the presence of links between them.

Spatial epidemiology is the description and analysis of the geographical distribution of disease. It is more important now than ever, with modern threats such as bio-terrorism making such analysis even more complex. This second edition of Statistical Methods in Spatial Epidemiology is updated and expanded to offer a complete coverage of the analysis and application of spatial statistical methods. The book is divided into two main sections: Part 1 introduces basic definitions and terminology, along with map construction and some basic models. This is expanded upon in Part II by applying this knowledge to the fundamental problems within spatial epidemiology, such as disease mapping, ecological analysis, disease clustering, bio-terrorism, space-time analysis, surveillance and infectious disease modelling. Provides a comprehensive overview of the main statistical methods used in spatial epidemiology. Updated to include a new emphasis on bio-terrorism and disease surveillance. Emphasizes the importance of space-time modelling and outlines the practical application of the method. Discusses the wide range of software available for analyzing spatial data, including WinBUGS, SaTScan and R, and features an accompanying website hosting related software. Contains numerous data sets, each representing a different approach to the analysis, and provides an insight into various modelling techniques. This text is primarily aimed at medical statisticians, researchers and practitioners from public health and epidemiology. It is also suitable for postgraduate students of statistics and epidemiology, as well professionals working in government agencies.