Geospatial data acquisition and analysis techniques have experienced tremendous growth in the last few years, providing an opportunity to solve previously unsolved environmental- and natural resource-related problems. However, a variety of challenges are encountered in processing the highly voluminous geospatial data in a scalable and efficient manner. Technological advancements in high-performance computing, computer vision, and big data analytics are enabling the processing of big geospatial data in an efficient and timely manner. Many geospatial communities have already adopted these techniques in multidisciplinary geospatial applications around the world. This book is a single source that offers a comprehensive overview of the state of the art and future developments in this domain. FEATURES Demonstrates the recent advances in geospatial analytics tools, technologies, and algorithms Provides insight and direction to the geospatial community regarding the future trends in scalable and intelligent geospatial analytics Exhibits recent geospatial applications and demonstrates innovative ways to use big geospatial data to address various domain-specific, real-world problems Recognizes the analytical and computational challenges posed and opportunities provided by the increased volume, velocity, and veracity of geospatial data This book is beneficial to graduate and postgraduate students, academicians, research scholars, working professionals, industry experts, and government research agencies working in the geospatial domain, where GIS and remote sensing are used for a variety of purposes. Readers will gain insights into the emerging trends on scalable geospatial data analytics.

Amid an unprecedented digital revolution, our society grapples with profound challenges, from the upheaval of traditional global systems to the ethical implications of technology's inexorable advance. As academic scholars seek a comprehensive understanding of this dynamic environment, Driving Decentralization and Disruption With Digital Technologies emerges as a beacon of insight. This compelling book confronts the intricate issues spawned by decentralization, de-globalization, and the transformative power of digital technologies, providing a roadmap for traversing the complexities of our digitally connected world. The book starts by unraveling the disruptive forces at play, shedding light on the threats posed to existing hierarchies and the potential consequences for disadvantaged groups. Digital disintermediation, driven by platforms and peer-to-peer networks, shakes the foundations of traditional economic systems, leaving banks and markets in flux. As global relationships redefine themselves in the face of decentralized markets, supply chains, and economic ties, scholars grapple with the profound implications for the future.

Remote Sensing and GIS in Peri-Urban Research: Perspectives on Global Change, Sustainability and Resilience, Eleventh Edition provides the most recent methods and techniques, incorporating geoinformatics-based practices to map, evaluate, and model urban landscape attributes and changes. The book provides theory, methodology, and future perspectives of remote sensing and GIS techniques applied to peri-urban modelling, analysis and sustainability through the use of spatio-temporal geospatial datasets. It also includes case studies of real-world data sets, with applicable algorithms, techniques and methods for study. This will be a useful reference for researchers and academics in remote sensing, GIS, and spatial analysis, and environmental or urban scientists wanting to implement remote sensing technologies in their research. - Outlines applications of geospatial technologies for visualization of land use dynamics including spatial information about population distributions, built-up areas and degree of urbanization based on global and local datasets - Provides methodology for identification of peri-urban interfaces using techniques to identify peri-urban space and dynamics using remote sensing and GIS techniques - Includes worldwide case studies by experts from different countries increasing the understanding of the nature of global peri-urbanization and growth

In geospatial analysis, navigating the complexities of data interpretation and analysis presents a formidable challenge. Traditional methods often need to efficiently handle vast volumes of geospatial data while providing insightful and actionable results. Scholars and practitioners grapple with manual or rule-based approaches, hindering progress in understanding and addressing pressing issues such as climate change, urbanization, and resource management. Ethics, Machine Learning, and Python in Geospatial Analysis offers a solution to the challenges faced by leveraging the extensive library support and user-friendly interface of Python and machine learning. The book’s meticulously crafted chapters guide readers through the intricacies of Python programming and its application in geospatial analysis, from fundamental concepts to advanced techniques.

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 gathers together innovative research and practical findings relating to urban mobility transformation. It is especially intended to provide academicians, researchers, practitioners and decision makers with effective strategies and techniques that can support urban mobility in a sustainable way. The chapters, which report on contributions presented at the 5th Conference on Sustainable Urban Mobility, held virtually on June 17-19, 2020, from Greece, cover the thematic areas of: social networks and traveler behavior; applications of technologies in transportation and big data analytics; transport infrastructure and traffic management; and transportation modeling and impact assessment. Special attention is given to public transport and demand responsive systems, electromobility, micromobility and automated vehicles. The book addresses the challenges of the near future, highlighting the importance of knowledge transfer, and it is intended to foster communication among universities, industries and public administration.

This book covers a range of topics including selective technologies and algorithms that can potentially contribute to developing an intelligent environment and smarter cities. While the connectivity and efficiency of smart cities is important, the analysis of the impact of construction development and large projects in the city is crucial to decision and policy makers, before the project is approved. This book also presents an agenda for future investigations to address the need for advanced tools such as mobile scanners, Geospatial Artificial Intelligence, Unmanned Aerial Vehicles, Geospatial Augmented Reality apps, Light Detection, and Ranging in smart cities. Some of selected specific tools presented in this book are as a simulator for improving the smart parking practices by modelling drivers with activity plans, a bike optimization algorithm to increase the efficiency of bike stations, an agent-based model simulation of human mobility with the use of mobile phone datasets. In addition, this book describes the use of numerical methods to match the network demand and supply of bicycles, investigate the distribution of railways using different indicators, presents a novel algorithm of direction-aware continuous moving K-nearest neighbor queries in road networks, and presents an efficient staged evacuation planning algorithm for multi-exit buildings.