This book presents a selection of manuscripts submitted to the 2nd International Conference on Geospatial Information Sciences 2021, a virtual conference held on November 3-5, 2021. These papers were selected by the Scientific Program Committee of the Conference after a rigorous peer-review process. They represent the vast scope of the interdisciplinary research areas that characterize the Geospatial Information Sciences that is done in the discipline. It especially represents a fabulous opportunity to showcase research carried out by young Mexican researchers and showcase it to the rest of the world and enhance the growth of the sciences in the country while, at the same time, enforces them to level up with other research at the international level.
This book highlights advanced applications of geospatial data analytics to address real-world issues in urban society. With a connected world, we are generating spatial at unprecedented rates which can be harnessed for insightful analytics which define the way we analyze past events and define the future directions. This book is an anthology of applications of spatial data and analytics performed on them for gaining insights which can be used for problem solving in an urban setting. Each chapter is contributed by spatially aware data scientists in the making who present spatial perspectives drawn on spatial big data. The book shall benefit mature researchers and student alike to discourse a variety of urban applications which display the use of machine learning algorithms on spatial big data for real-world problem solving.
Advances in Geo-Spatial Information Science presents recent advances regarding fundamental issues of geo-spatial information science (space and time, spatial analysis, uncertainty modeling and geo-visualization), and new scientific and technological research initiatives for geo-spatial information science (such as spatial data mining, mobile data modeling, and location-based services). The book contains selected and revised papers presented at the joint International Conference on Theory, Data Handling and Modelling in GeoSpatial Information Science (Hong Kong, 26–28 May 2010), and brings together three related international academic communities: spatial information science, spatial data handling, and modeling geographic systems. Advances in Geo-Spatial Information Science will be of interest for academics and professionals interested in spatial information science, spatial data handling, and modeling of geographic systems.
This book elucidates how cyberGIS (that is, new-generation geographic information science and systems (GIS) based on advanced computing and cyberinfrastructure) transforms computation- and data-intensive geospatial discovery and innovation. It comprehensively addresses opportunities and challenges, roadmaps for research and development, and major progress, trends, and impacts of cyberGIS in the era of big data. The book serves as an authoritative source of information to fill the void of introducing this exciting and growing field. By providing a set of representative applications and science drivers of cyberGIS, this book demonstrates how cyberGIS has been advanced to enable cutting-edge scientific research and innovative geospatial application development. Such cyberGIS advances are contextualized as diverse but interrelated science and technology frontiers. The book also emphasizes several important social dimensions of cyberGIS such as for empowering deliberative civic engagement and enabling collaborative problem solving through structured participation. In sum, this book will be a great resource to students, academics, and geospatial professionals for leaning cutting-edge cyberGIS, geospatial data science, high-performance computing, and related applications and sciences.
This book provides a cross-section of cutting-edge research areas being pursued by researchers in spatial data handling and geographic information science (GIS). It presents selected papers on the advancement of spatial data handling and GIS in digital cartography, geospatial data integration, geospatial database and data infrastructures, geospatial data modeling, GIS for sustainable development, the interoperability of heterogeneous spatial data systems, location-based services, spatial knowledge discovery and data mining, spatial decision support systems, spatial data structures and algorithms, spatial statistics, spatial data quality and uncertainty, the visualization of spatial data, and web and wireless applications in GIS.
The role open-source geospatial software plays in data handling within the spatial information technology industry is the overarching theme of the book. It also examines new tools and applications for those already using OS approaches to software development.
Data science has recently gained much attention for a number of reasons, and among them is Big Data. Scientists (from almost all disciplines including physics, chemistry, biology, sociology, among others) and engineers (from all fields including civil, environmental, chemical, mechanical, among others) are faced with challenges posed by data volume, variety, and velocity, or Big Data. This book is designed to highlight the unique characteristics of geospatial data, demonstrate the need to different approaches and techniques for obtaining new knowledge from raw geospatial data, and present select state-of-the-art geospatial data science techniques and how they are applied to various geoscience problems.
This volume uniquely links educational theories and the practice of GIScience in higher education contexts to guide classroom practice, present effective practical implementations from peers, and provide resources and strategies for effective teaching methods. The book offers a comprehensive exploration of GIScience education, including current trends and future educational needs in GIScience, and will act as a resource to prepare learners for a world that demands more intensive investment in present-day education and technological literacy. Additionally, the indirect benefit of merging the fragmented literature on GIScience literacy will provide a basis to examine common techniques and enable a new wave of research more rooted in learning theories. In ten chapters, the book is designed to attract an audience from geographic information systems science, geomatics, spatial information science, cartography, information technology, and educational technology as focus disciplines.
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.
Your government warns that 10% of your neighbors have a deadly contagious virus. The producer of a diagnostic test advertises that 90% of its tests are correct for any population. The test indicates that you have the virus. This book’s author claims your test has a 50% chance of being false, given your test’s result. Who do you believe? This book gives you insights necessary to interpret metrics that make a difference in life’s decisions. This book gives methods and software that are essential to analyze change and error. Change describes a phenomenon across time points. Error compares diagnoses with the truth. Other texts give insufficient attention to these topics. This book’s novel ideas dispel popular misconceptions and replace previous methods. The author uses carefully designed graphics and high school mathematics to communicate easily with college students and advanced scientists. Applications include but are not limited to Remote Sensing, Land Change Science, and Geographic Information Science. “A wide range of tools to aid understanding of land cover and its change has been used but scientific progress has sometimes been limited through misuse and misunderstanding. Professor Pontius seeks to rectify this situation by providing a book to accompany the researcher’s toolbox. Metrics That Make a Difference addresses basic issues of relevance to a broad community in a mathematically friendly way and should greatly enhance the ability to elicit correct information. I wish this book existed while I was a grad student.” – Giles Foody, Professor of Geographical Information Science, The University of Nottingham “Metrics That Make a Difference provides a comprehensive synthesis of over two decades of work during which Dr. Pontius researched, developed, and applied these metrics. The book meticulously and successfully guides the reader through the conceptual basis, computations, and proper interpretation of the many metrics derived for different types of variables. The book is not just a mathematical treatise but includes practical guidance to good data analysis and good science. Data scientists from many fields of endeavor will benefit substantially from Dr. Pontius’ articulate review of traditionally used metrics and his presentation of the innovative and novel metrics he has developed. While reading this book, I had multiple ‘aha’ moments about metrics that I shouldn't be using and metrics that I should be using instead.” – Stephen Stehman, Distinguished Teaching Professor, State University of New York
