Spatial Statistics and Analysis: Techniques and Applications 1ed

Spatial Statistics and Analysis: Techniques and Applications is an essential resource for anyone interested in the theory and application of spatial statistics. This comprehensive text delves into the principles, tools, and methods used in spatial analysis, making it invaluable for undergraduate and graduate students, researchers, and professionals across various fields including geography, public health, engineering, and social sciences. With hands-on exercises, the book guides readers through complex topics and ensures a deep understanding of spatial data analysis. In addition to covering key terms and tools, this valuable resource explores scales of measurement, data distributions, and spatial dataset visualizations.

Other sections examine spatial statistical relationships, point and areal pattern analysis, complex spatial patterns, and geostatistical analysis. The text also addresses spatial error and uncertainty and includes practical applications of Markov chains. Supplementary resources such as instructional slides, lab activities, data sets, and graphic illustrations are provided to aid both teaching and learning.

• Covers the theoretical and practical aspects of spatial statistics and analysis in comprehensive depth by using case studies and methodological applications
• Functions as a one-stop source and provides detailed theoretical information and lab assignments using up to date resources
• Uses most current U.S. Census, environmental, and economic data for hands-on laboratory assignments for students
• Includes high-quality illustrations and PowerPoint slides for instructors, and a key for lab activities for both students and instructors

Dr.Anzhelika Antipova is an urban geographer with broad research interests in travel behavior and transportation, medical/health geography and wellbeing, and economic geography. She is using traditional statistical techniques, spatial statistics and analysis, and geographic information system (GIS) as tools in her research. Her work contributes to important techniques that can be applied by other researchers and practitioners towards their research objectives. She improved consistent criteria for employment delineation and job-rich areas (job center, sub-center, job cluster) and applied towards the Memphis Aerotropolis identification in Memphis, TN. She developed the Social Disadvantage Index (SDI) that can identify communities vulnerable to pandemics such as the COVID-19 based on the risk factors for severe disease outcomes. At the University of Memphis, she teaches Quantitative methods, Spatial Statistics, Urban Geography, Transportation geography, Economic and Social Geography and GIS, and Cultural geography.