Wilson J. Spatial Data Science 2024 torrent

Textbook in PDF format

Spatial Data Science will show GIS scientists and practitioners how to add and use new analytical methods from Data Science in their existing GIS platforms. By explaining how the spatial domain can provide many of the building blocks, it's critical for transforming data into information, knowledge, and solutions.
Spatial Data Science покажет ученым и практикам ГИС, как добавлять и использовать новые аналитические методы из Data Science в их существующих платформах ГИС. Объясняя, как пространственная область может предоставить множество строительных блоков, она имеет решающее значение для преобразования данных в информацию, знания и решения.
This book is for those using or studying GIS and the computer scientists, engineers, statisticians, and information and library scientists leading the development and deployment of Data Science.
Spatial Data Science consists of six chapters. The first chapter introduces the book and describes its two complementary goals. The first goal is to show spatial scientists and practitioners how they can enhance their current use of geographic information systems (GIS), Global Positioning System (GPS), and remote sensing by adding and using geospatial Big Data and Data Science methods to extend their existing toolboxes. The second goal is to show data scientists how they can better realize the potential of Big Data and Data Science by using spatial perspectives and geospatial technologies to discover new knowledge.
The second chapter traces the emergence of the spatial sciences as a new and integrative field over the past 50 years. This chapter describes the two core threads: (1) the representation, measurement, and manipulation of geospatial information, and (2) the significance and meaning of place for the functioning of the earth and human well-being. The ArcGIS sections show how GIS has moved from stand-alone software platforms to open and distributed systems during the past several years. The rapid growth and elaboration of the spatial science community is also described through the lens of professional organizations and academic journals that cover theory, practice, and technology. The chapter closes by noting what is missing and what needs to be added to advance the work of spatial scientists and practitioners in the future.
The third chapter looks beyond the spatial sciences that I grew up with to the digital era and the rise of cloud computing, Big Data, Data Science, and open science during the past few decades. These fields represent important innovations and help set the stage for how the geospatial community will need to evolve in the next few years to sustain its success.
The fourth chapter describes the rise of geospatial Big Data and the various types of digital data that spatial scientists and practitioners can use to inform and guide their work. These types of data include location-based devices and services; volunteered and ambient geographic information; remote sensing; sensor networks and the Internet of Things (IoT); and 3D modeling, video, and virtual and augmented reality systems. This chapter describes how we all live and work in an era that is awash with geospatial data.
Preface
Introduction
The emergence of the spatial sciences as a new and integrative field
Cloud computing, big data, data science, and open science in the digital era
Geospatial big data
The Esri geospatial cloud
Conclusions and future prospects