Spatial Analysis

Statistics, Visualization, and Computational Methods
1. Auflage 2015
ISBN: 978-1-4987-0763-3
Verlag: CRC Press

Buch, Englisch, 323 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 744 g

An introductory text for the next generation of geospatial analysts and data scientists, Spatial Analysis: Statistics, Visualization, and Computational Methods focuses on the fundamentals of spatial analysis using traditional, contemporary, and computational methods. Outlining both non-spatial and spatial statistical concepts, the authors present practical applications of geospatial data tools, techniques, and strategies in geographic studies. They offer a problem-based learning (PBL) approach to spatial analysis—containing hands-on problem-sets that can be worked out in MS Excel or ArcGIS—as well as detailed illustrations and numerous case studies.

The book enables readers to:

Identify types and characterize non-spatial and spatial data
Demonstrate their competence to explore, visualize, summarize, analyze, optimize, and clearly present statistical data and results
Construct testable hypotheses that require inferential statistical analysis
Process spatial data, extract explanatory variables, conduct statistical tests, and explain results
Understand and interpret spatial data summaries and statistical tests

Spatial Analysis: Statistics, Visualization, and Computational Methods incorporates traditional statistical methods, spatial statistics, visualization, and computational methods and algorithms to provide a concept-based problem-solving learning approach to mastering practical spatial analysis. Topics covered include: spatial descriptive methods, hypothesis testing, spatial regression, hot spot analysis, geostatistics, spatial modeling, and data science.

Autoren/Hrsg.

Oyana, Tonny J.

Margai, Florence

Fachgebiete

• Technische Wissenschaften Umwelttechnik | Umwelttechnologie Umwelttechnik
• Mathematik | Informatik Mathematik Stochastik
• Geowissenschaften Umweltwissenschaften Umwelttechnik
• Geowissenschaften Geologie Geologie

Inhaltsverzeichnis

The Context and Relevance of Spatial Analysis. Scientific Observations and Measurements in Spatial Analysis. Using Statistical Measures to Analyze Data Distributions. Exploratory Data Analysis, Visualization, and Hypothesis Testing. Analyzing Spatial Statistical Relationships. Engaging in Point Pattern Analysis. Engaging in Areal Pattern Analysis Using Global and Local Statistics. Engaging in Geostatistical Analysis. Data Science: Understanding Computing Systems and Analytics for Big Data.

Über Autor(innen)

Dr. Tonny J. Oyana received his Ph.D and his postdoctoral training from the University of Buffalo, New York, USA. He is currently the director of spatial analytics and informatics, Research Center for Health Disparities, Equity, and the Exposome; and a professor of spatial information systems in the Department of Preventive Medicine at the University of Tennessee Health Science Center, Knoxville, USA. His research focuses on establishing the relationship between environmental health and exposure; advancing GIS methods, algorithm design, and spatial analytical methods; and understanding the factors that contribute toward land systems change. In addition, he has authored more than 80 scientific works.

Dr. Florence M. Margai (now deceased) was a professor in the Department of Geography at Binghamton University, New York, USA, where she taught courses that reflected her areas of specialization: advanced statistics, environmental health hazards, health disparities, and environmental analysis using geospatial and visualization technologies. She also served as the associate dean of Harpur College of Arts and Sciences, Vestal, New York, USA. Margai obtained her Ph.D from Kent State University, Ohio, USA, and worked with nonprofit organizations to assist in the geographic targeting of vulnerable population groups for disease intervention and health promotional campaigns, sustainability, and capacity development initiatives.