Sharing And Using Geospatial Data Across Borders
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Sharing and Using Geospatial Data Across Borders
Spatial Data Infrastructures (SDIs) are key for effective cross-border data-sharing. A Spatial Data Infrastructure is "a framework of policies, institutional arrangements, technologies, data, and people that enable the sharing and effective usage of geographic." As such, they can play a pivotal role in digital government transformation. The present study demonstrates how geospatial data from multiple countries can be used to develop location powered insights. In addition, it provides information on the types of enabling environments that can foster data-driven innovation. The overarching question that the study seeks to respond to is: "What is the current state of play on sharing and using geospatial data across European borders? What can we learn from these practices to support the evolution of Spatial Data Infrastructures?" The study builds on the analysis of data collected through desk research, eight case studies and a dedicated workshop. The case studies, through customised interviews, provide first-hand knowledge and experiences on the exchange of geospatial data across borders in the European context of public, private and non-profit organisations. Insights include benefits such as improved collaboration, economic gains, improved access to information, and new and improved services. Among the challenges that emerged are worth mentioning the lack of technical and organisational interoperability to establish a sustainable ecosystem with a culture of sharing data, including problems with licensing, data portability and privacy issues. This study forms part of the European Location Interoperability Solutions for e-Government (ELISE) action of the European Interoperability solutions for public administrations, businesses and citizens Programme, better known by its acronym ISA. ELISE aims to facilitate the cross-border use of location data and support the digital transformation of public services.
Spatial Data Analysis With R
This is an introduction for social science students to the growing field of spatial data analysis using the R platform. The text assumes no prior knowledge of either, beyond the contents of an introductory statistics course. It uses the open-source software R, and relevant spatial data analysis packages, to provide practical guidance of how to conduct spatial data analysis with readers′ own data sets. The book first briefly introduces students to R, covers some basic concepts in statistical data analysis, and then focuses on discussing the central ideas of spatial data analysis. All the discussions are supported with R scripts so that students can work on their own and produce results that the book helps interpret. Each chapter ends with review questions to test understanding. The book is suited for upper-level undergraduate social science students and graduate students, and other social scientists who are interested in analyzing their spatial data with R. A companion website for the book at https://edge.sagepub.com/yu includes R code and data for students to replicate the examples in the book. The password-protected instructor side of the site includes exercises and answers which can be set for homework.
Geospatial Technologies in Coastal Ecologies Monitoring and Management
Author: Kousik Das Malakar
language: en
Publisher: Springer Nature
Release Date: 2025-07-01
This book contributes to the advancement of scientific knowledge by demonstrating how geospatial technologies can support more effective coastal planning and management. These technologies, such as remote sensing, GIS, and GNSS, play a vital role in monitoring coastal ecosystems and offer powerful tools for data collection, analysis, visualization, and decision-making. They enhance the understanding of coastal needs and enable more informed and sustainable management strategies. Intended for scientists, professionals, researchers, planners, students, and the general public, the book promotes a deeper understanding of how geospatial tools address contemporary coastal challenges. It also emphasizes inclusive decision-making and supports the development of strategies for sustainable socio-ecological coastal systems. The book is structured into six parts. Part One introduces the fundamentals of remote sensing, including sensor networks, satellite systems, aerial imaging, photogrammetry, and air photo interpretation. Part Two covers key GIS concepts, data analysis, database management, digital image processing, and participatory GIS. Part Three explores GNSS and GPS techniques. Part Four discusses the application of geospatial tools in coastal ecological monitoring and management. Part Five presents real-world case studies and field narratives that explore a range of topics, including climatic trend analysis, shoreline dynamics modelling, mangrove canopy health, coastal land use and land cover changes, land surface temperature variations, ecological transformations, mangrove-human conflicts, climate adaptation strategies, the management of climate gaps, spatial considerations in coastal zone management, and the role of climate communication in shaping coastal narratives. And finally, Part Six examines the evolving nature of coastal research, highlighting the role of GIScience in transdisciplinary approaches and strategic decision-making.