Geographical Data Science And Spatial Data Analysis
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Geographical Data Science and Spatial Data Analysis
This book builds on the previous book by the same authors, An Introduction to R for Spatial Analysis and Mapping, to consider Spatial Data (ie the location attached to data), issues of inference, linking Big Data, Geography / GIS / Mapping and Spatial Analytics. A ‘learning by doing’ text book, it covers important theoretical issues and helps to develop practical skills in the reader for addressing these.
Geographic Information, Geospatial Technologies and Spatial Data Science for Health
Geographic information, spatial analysis and geospatial technologies play an important role in understanding changes in planetary health and in defining the drivers contributing to different health outcomes both locally and globally. Patterns influencing health outcomes and disease in the environment are complex and require an understanding of the ecology of the disease and how these interact in space and time. Knowing where and when diseases are prevalent, who is affected and what may be driving these outcomes is important for determining how to respond. In reality, we all would like to be healthy and live in healthy places. In this book, epidemiology and public health are integrated with spatial data science to examine health issues in dynamically changing environments. This is too broad a field to be completely covered in one book, and so, it has been necessary to be selective with the topics, methods and examples used to avoid overwhelming introductory readers while at the same time providing sufficient depth for geospatial experts interested in health and for health professionals interested in integrating geospatial elements for health analysis. A variety of geographic information (some novel, some volunteered, some authoritative, some big and messy) is used with a mix of methods consisting of spatial analysis, data science and spatial statistics to better understand health risks and disease outcomes. Key Features: Makes spatial data science accessible to health Integrates epidemiology and disease ecology with spatial data science Integrates theoretical geographic information science concepts Provides practical and applied approaches for examining and exploring health and disease risks Provides spatial data science skill development ranging from map making to spatial modelling
An Introduction to Spatial Data Analysis
Author: Martin Wegmann
language: en
Publisher: Pelagic Publishing Ltd
Release Date: 2020-09-14
This is a book about how ecologists can integrate remote sensing and GIS in their research. It will allow readers to get started with the application of remote sensing and to understand its potential and limitations. Using practical examples, the book covers all necessary steps from planning field campaigns to deriving ecologically relevant information through remote sensing and modelling of species distributions. An Introduction to Spatial Data Analysis introduces spatial data handling using the open source software Quantum GIS (QGIS). In addition, readers will be guided through their first steps in the R programming language. The authors explain the fundamentals of spatial data handling and analysis, empowering the reader to turn data acquired in the field into actual spatial data. Readers will learn to process and analyse spatial data of different types and interpret the data and results. After finishing this book, readers will be able to address questions such as “What is the distance to the border of the protected area?”, “Which points are located close to a road?”, “Which fraction of land cover types exist in my study area?” using different software and techniques. This book is for novice spatial data users and does not assume any prior knowledge of spatial data itself or practical experience working with such data sets. Readers will likely include student and professional ecologists, geographers and any environmental scientists or practitioners who need to collect, visualize and analyse spatial data. The software used is the widely applied open source scientific programs QGIS and R. All scripts and data sets used in the book will be provided online at book.ecosens.org. This book covers specific methods including: what to consider before collecting in situ data how to work with spatial data collected in situ the difference between raster and vector data how to acquire further vector and raster data how to create relevant environmental information how to combine and analyse in situ and remote sensing data how to create useful maps for field work and presentations how to use QGIS and R for spatial analysis how to develop analysis scripts