This book constitutes the proceedings of the Second International Conference on Spatial Data and Intelligence, SpatialDI 2021, which was held during April 22-24, 2021 in Hangzhou, China. The 14 full papers and 7 short papers presented in this volume were carefully reviewed and selected from 72 submissions. They are organized in the topical sections named: traffic management, data science, and city analysis.
This book constitutes the proceedings of the First International Conference on Spatial Data and Intelligence, SpatialDI 2020, which was held on May 8-9, 2020. The conference was planned to take place in Shenzhen, China, and changed to an online format due to the COVID-19 pandemic. The 21 full papers presented in this volume were carefully reviewed and selected from 50 submissions. They were organized in topical sections named: traffic management; data science; and visualization science.
Decision makers, such as government officials, need to better understand human activity in order to make informed decisions. With the ability to measure and explore geographic space through the use of geospatial intelligence data sources including imagery and mapping data, they are better able to measure factors affecting the human population. As a broad field of study, geospatial research has applications in a variety of fields including military science, environmental science, civil engineering, and space exploration. Geospatial Intelligence: Concepts, Methodologies, Tools, and Applications explores multidisciplinary applications of geographic information systems to describe, assess, and visually depict physical features and to gather data, information, and knowledge regarding human activity. Highlighting a range of topics such as geovisualization, spatial analysis, and landscape mapping, this multi-volume book is ideally designed for data scientists, engineers, government agencies, researchers, and graduate-level students in GIS programs.
This book constitutes the proceedings of the Second International Conference on Spatial Data and Intelligence, SpatialDI 2021, which was held during April 22-24, 2021 in Hangzhou, China. The 14 full papers and 7 short papers presented in this volume were carefully reviewed and selected from 72 submissions. They are organized in the topical sections named: traffic management, data science, and city analysis.
This book explores cutting-edge methods combining geospatial technologies and artificial intelligence related to several fields such as smart farming, urban planning, geology, transportation, and 3D city models. It introduces techniques which range from machine and deep learning to remote sensing for geospatial data analysis. The book consists of two main parts that include 13 chapters contributed by promising authors. The first part deals with the use of artificial intelligence techniques to improve spatial data analysis, whereas the second part focuses on the use of artificial intelligence with remote sensing in various fields. Throughout the chapters, the interest for the use of artificial intelligence is demonstrated for different geospatial technologies such as aerial imagery, drones, Lidar, satellite remote sensing, and more. The work in this book is dedicated to the scientific community interested in the coupling of geospatial technologies and artificial intelligence and exploring the synergetic effects of both fields. It offers practitioners and researchers from academia, the industry and government information, experiences and research results about all aspects of specialized and interdisciplinary fields on geospatial intelligence.
This book constitutes the refereed proceedings of the Third International Conference, SpatialDI 2022, Wuhan, China, August 5–7, 2022, Revised Selected Papers. The 19 full papers and 1 short paper included in this book were carefully reviewed and selected from 77 submissions. They were organized in topical sections as follows: Traffic Management, Data science, City Analysis.
Discover the power of location data to build effective, intelligent data models with Geospatial ecosystems Key FeaturesManipulate location-based data and create intelligent geospatial data modelsBuild effective location recommendation systems used by popular companies such as UberA hands-on guide to help you consume spatial data and parallelize GIS operations effectivelyBook Description Data scientists, who have access to vast data streams, are a bit myopic when it comes to intrinsic and extrinsic location-based data and are missing out on the intelligence it can provide to their models. This book demonstrates effective techniques for using the power of data science and geospatial intelligence to build effective, intelligent data models that make use of location-based data to give useful predictions and analyses. This book begins with a quick overview of the fundamentals of location-based data and how techniques such as Exploratory Data Analysis can be applied to it. We then delve into spatial operations such as computing distances, areas, extents, centroids, buffer polygons, intersecting geometries, geocoding, and more, which adds additional context to location data. Moving ahead, you will learn how to quickly build and deploy a geo-fencing system using Python. Lastly, you will learn how to leverage geospatial analysis techniques in popular recommendation systems such as collaborative filtering and location-based recommendations, and more. By the end of the book, you will be a rockstar when it comes to performing geospatial analysis with ease. What you will learnLearn how companies now use location dataSet up your Python environment and install Python geospatial packagesVisualize spatial data as graphsExtract geometry from spatial dataPerform spatial regression from scratchBuild web applications which dynamically references geospatial dataWho this book is for Data Scientists who would like to leverage location-based data and want to use location-based intelligence in their data models will find this book useful. This book is also for GIS developers who wish to incorporate data analysis in their projects. Knowledge of Python programming and some basic understanding of data analysis are all you need to get the most out of this book.
We are in an age of big data where all of our everyday interactions and transactions generate data. Much of this data is spatial – it is collected some-where – and identifying analytical insight from trends and patterns in these increasing rich digital footprints presents a number of challenges. Whilst other books describe different flavours of Data Analytics in R and other programming languages, there are none that consider Spatial Data (i.e. the location attached to data), or that consider issues of inference, linking Big Data, Geography, GIS, Mapping and Spatial Analytics. This is a ‘learning by doing’ textbook, building on the previous book by the same authors, An Introduction to R for Spatial Analysis and Mapping. It details the theoretical issues in analyses of Big Spatial Data and developing practical skills in the reader for addressing these with confidence.
Regional Intelligence is an emerging field that leverages the lessons learned through decades of regional science. By merging spatial analysis with quantitative analytical techniques in the Anthropocene, this book contributes to the multidisciplinary understanding of regional issues. The locational aspects of regional paradigms are explored through various empirical studies that promote a rich and diversified understanding of regional issues concerning policy, governance, land use, and territorial decisions. Given its scope, the book will appeal to scholars and students of regional and spatial sciences and geography, as well as practitioners and decision makers engaged in regional planning and policymaking, looking for new methodological approaches that offer insights into sustainable development, regional prosperity, and livability. As a unique contribution, this book challenges the status quo on how complex spatial problems at an international level and at multiple scales can be comprehended.
Spatial Intelligence examines public and professional conceptions of the relationships between thinking about spatial attributes and active engagement in spatially related constructions and designs. Even though children’s and adolescents’ spatial propensities in constructive activities parallel the skills needed by professionals in both established and emerging fields, spatial education is often missing from K–12 curricula and is easily impeded by teachers, parents, or other individuals who do not provide contexts in formalized settings, such as schools, to nurture its potential. This book bridges the gap by linking the natural spatial inclinations, interests, and proclivities of individuals from a variety of cultures with professional training and expertise in engineering, architecture, science, and mathematics. Educators will be better able to achieve the skills and awareness necessary to provide children and young adults with the vital opportunities inherent in spatial education.
