Exploring Spatial Scale in Geography

A ground-up approach to explaining dynamic spatial modelling for an interdisciplinary audience. Across broad areas of the environmental and social sciences, simulation models are an important way to study systems inaccessible to scientific experimental and observational methods, and also an essential complement to those more conventional approaches. The contemporary research literature is teeming with abstract simulation models whose presentation is mathematically demanding and requires a high level of knowledge of quantitative and computational methods and approaches. Furthermore, simulation models designed to represent specific systems and phenomena are often complicated, and, as a result, difficult to reconstruct from their descriptions in the literature. This book aims to provide a practical and accessible account of dynamic spatial modelling, while also equipping readers with a sound conceptual foundation in the subject, and a useful introduction to the wide-ranging literature. Spatial Simulation: Exploring Pattern and Process is organised around the idea that a small number of spatial processes underlie the wide variety of dynamic spatial models. Its central focus on three ‘building-blocks’ of dynamic spatial models – forces of attraction and segregation, individual mobile entities, and processes of spread – guides the reader to an understanding of the basis of many of the complicated models found in the research literature. The three building block models are presented in their simplest form and are progressively elaborated and related to real world process that can be represented using them. Introductory chapters cover essential background topics, particularly the relationships between pattern, process and spatiotemporal scale. Additional chapters consider how time and space can be represented in more complicated models, and methods for the analysis and evaluation of models. Finally, the three building block models are woven together in a more elaborate example to show how a complicated model can be assembled from relatively simple components. To aid understanding, more than 50 specific models described in the book are available online at patternandprocess.org for exploration in the freely available Netlogo platform. This book encourages readers to develop intuition for the abstract types of model that are likely to be appropriate for application in any specific context. Spatial Simulation: Exploring Pattern and Process will be of interest to undergraduate and graduate students taking courses in environmental, social, ecological and geographical disciplines. Researchers and professionals who require a non-specialist introduction will also find this book an invaluable guide to dynamic spatial simulation.

SPATIAL ANALYSIS Explore the foundations and latest developments in spatial statistical analysis In Spatial Analysis, two distinguished authors deliver a practical and insightful exploration of the statistical investigation of the interdependence of random variables as a function of their spatial proximity. The book expertly blends theory and application, offering numerous worked examples and exercises at the end of each chapter. Increasingly relevant to fields as diverse as epidemiology, geography, geology, image analysis, and machine learning, spatial statistics is becoming more important to a wide range of specialists and professionals. The book includes: Thorough introduction to stationary random fields, intrinsic and generalized random fields, and stochastic models Comprehensive exploration of the estimation of spatial structure Practical discussion of kriging and the spatial linear model Spatial Analysis is an invaluable resource for advanced undergraduate and postgraduate students in statistics, data science, digital imaging, geostatistics, and agriculture. It’s also an accessible reference for professionals who are required to use spatial models in their work.

Provides up-to-date developments in the field of remote sensing by assessing scale issues in land surface, properties, patterns, and processes Scale is a fundamental and crucial issue in remote sensing studies and image analysis. GIS and remote sensing scientists use various scaling techniques depending on the types of remotely sensed images and geospatial data used. Scaling techniques affect image analysis such as object identification and change detection. This book offers up-to-date developments, methods, and techniques in the field of GIS and remote sensing and features articles from internationally renowned authorities on three interrelated perspectives of scaling issues: scale in land surface properties, land surface patterns, and land surface processes. It also visits and reexamines the fundamental theories of scale and scaling by well-known experts who have done substantial research on the topics. Edited by a prominent authority in the geographic information science community, Scale Issues in Remote Sensing: Offers an extensive examination of the fundamental theories of scale issues along with current scaling techniques Studies scale issues from three interrelated perspectives: land surface properties, patterns, and processes Addresses the impact of new frontiers in Earth observation technology (high-resolution, hyperspectral, Lidar sensing, and their synergy with existing technologies) and advances in remote sensing imaging science (object-oriented image analysis and data fusion) Prospects emerging and future trends in remote sensing and their relationship with scale Scale Issues in Remote Sensing is ideal as a professional reference for practicing geographic information scientists and remote sensing engineers as well as supplemental reading for graduate level students.

Presents an overview of the complex biological systems used within a global public health setting and features a focus on malaria analysis Bridging the gap between agent-based modeling and simulation (ABMS) and geographic information systems (GIS), Spatial Agent-Based Simulation Modeling in Public Health: Design, Implementation, and Applications for Malaria Epidemiology provides a useful introduction to the development of agent-based models (ABMs) by following a conceptual and biological core model of Anopheles gambiae for malaria epidemiology. Using spatial ABMs, the book includes mosquito (vector) control interventions and GIS as two example applications of ABMs, as well as a brief description of epidemiology modeling. In addition, the authors discuss how to most effectively integrate spatial ABMs with a GIS. The book concludes with a combination of knowledge from entomological, epidemiological, simulation-based, and geo-spatial domains in order to identify and analyze relationships between various transmission variables of the disease. Spatial Agent-Based Simulation Modeling in Public Health: Design, Implementation, and Applications for Malaria Epidemiology also features: Location-specific mosquito abundance maps that play an important role in malaria control activities by guiding future resource allocation for malaria control and identifying hotspots for further investigation Discussions on the best modeling practices in an effort to achieve improved efficacy, cost-effectiveness, ecological soundness, and sustainability of vector control for malaria An overview of the various ABMs, GIS, and spatial statistical methods used in entomological and epidemiological studies, as well as the model malaria study A companion website with computer source code and flowcharts of the spatial ABM and a landscape generator tool that can simulate landscapes with varying spatial heterogeneity of different types of resources including aquatic habitats and houses Spatial Agent-Based Simulation Modeling in Public Health: Design, Implementation, and Applications for Malaria Epidemiology is an excellent reference for professionals such as modeling and simulation experts, GIS experts, spatial analysts, mathematicians, statisticians, epidemiologists, health policy makers, as well as researchers and scientists who use, manage, or analyze infectious disease data and/or infectious disease-related projects. The book is also ideal for graduate-level courses in modeling and simulation, bioinformatics, biostatistics, public health and policy, and epidemiology.

The first book of its kind to introduce the fundamentals, basic features and models, potential applications and novel phenomena and its important applications in liquid crystal technology. Recognized leader in the field Gaetano Assanto outlines the peculiar characteristics of nematicons and the promise they have for the future growth of this captivating new field.

This book collects a wealth of information about spatial audio coding into one comprehensible volume. It is a thorough reference to the 3GPP and MPEG Parametric Stereo standards and the MPEG Surround multi-channel audio coding standard. It describes key developments in coding techniques, which is an important factor in the optimization of advanced entertainment, communications and signal processing applications. Until recently, technologies for coding audio signals, such as redundancy reduction and sophisticated source and receiver models did not incorporate spatial characteristics of source and receiving ends. Spatial audio coding achieves much higher compression ratios than conventional coders. It does this by representing multi-channel audio signals as a downmix signal plus side information that describes the perceptually-relevant spatial information. Written by experts in spatial audio coding, Spatial Audio Processing: reviews psychoacoustics (the relationship between physical measures of sound and the corresponding percepts) and spatial audio sound formats and reproduction systems; brings together the processing, acquisition, mixing, playback, and perception of spatial audio, with the latest coding techniques; analyses algorithms for the efficient manipulation of multiple, discrete and combined spatial audio channels, including both MP3 and MPEG Surround; shows how the same insights on source and receiver models can also be applied for manipulation of audio signals, such as the synthesis of virtual auditory scenes employing head-related transfer function (HRTF) processing and stereo to N-channel audio upmix. Audio processing research engineers and audio coding research and implementation engineers will find this an insightful guide. Academic audio and psychoacoustic researchers, including post-graduate and third/fourth year students taking courses in signal processing, audio and speech processing, and telecommunications, will also benefit from the information inside.

Any architect doing small or medium scaled projects who is also vested in sustainable design but is not yet doing BIM will enjoy this book's overall focus.-Architosh.com This work is the leading guide to architectural design within a building information modeling (BIM) workflow, giving the practitioner a clear procedure when designing climate-load dominated buildings. The book incorporates new information related to BIM, integrated practice, and sustainable design, as well information on how designers can incorporate the latest technological tools. Each chapter addresses specific topics, such as natural ventilation for cooling, passive solar heating, rainwater harvesting and building hydrology, optimizing material use and reducing construction waste, and collaborating with consultants or other building professionals such as engineers and energy modelers.

This book provides an introduction to spatial analyses concerning disaggregated (or micro) spatial data. Particular emphasis is put on spatial data compilation and the structuring of the connections between the observations. Descriptive analysis methods of spatial data are presented in order to identify and measure the spatial, global and local dependency. The authors then focus on autoregressive spatial models, to control the problem of spatial dependency between the residues of a basic linear statistical model, thereby contravening one of the basic hypotheses of the ordinary least squares approach. This book is a popularized reference for students looking to work with spatialized data, but who do not have the advanced statistical theoretical basics.