Download or read book Spatio temporally Interpretable Geo AI Approaches for Predictive Modeling of Geographic Events written by Arif Masrur and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) or machine learning (ML) techniques have seen explosive use and adaptations in many big data-driven application contexts, including geographic knowledge discovery and predictive modeling of spatial events. However, significant challenges exist for meaningful and practical applications of these advanced AI techniques in the geospatial domain. These challenges are introduced by the 'special' characteristics of geospatial data that manifest dependence, heterogeneity, and non-stationarity in the arrangement of spatial phenomena and their relationships with the driving factors. Spatial phenomena (e.g., wildfires) may also exhibit spatial memory effects and scale-dependent degrees of interactions with the driving factors. If these characteristics are not appropriately addressed, then the estimation of spatiotemporal relationships and predictions can be biased and thus unreliable and less effective in real-world applications. The overarching goal of this dissertation is to present and investigate spatially and spatiotemporally explicit machine and deep learning approaches for enabling accurate, reliable predictions and meaningful physical interpretations of geographic events. The dissertation showcases key challenges in the machine and deep learning-based modeling of spatially heterogeneous and temporally non-stationary relationships between geographic events -- both discrete and continuous -- and their contributing factors. Using the example of historical wildfires in the Alaskan tundra (1981-2019) that manifest climate and biophysical change, the first study highlights methodological challenges to model such events with aspatial machine learning models such as tree-based ensembles, particularly the random forest (RF). Based on that, the second study conceptualizes a spatiotemporally explicit random forest framework for modeling discrete geo-events. Specifically, it focuses on identifying the methodological steps within the aspatial RF that do not allow considering the spatial and temporal patterns that may exist between the predictand and predictors. The resulting proposed method is demonstrated through a large-scale case study to predict wildfire occurrence (1984-2017) and explain spatial and temporal patterns of relationships between fires and their driving factors across the ecoregions of the conterminous United States. Results show that the proposed approach is effective against the general aspatial RF approach in prediction (+6% accuracy) and supports local to global level interpretations on the relationships between wildfires and biophysical drivers. The third study addresses the challenge of accurately predicting dynamic geo-events that manifest scale-dependent spatiotemporal interrelationships between the event's space-time evolution and underlying biophysical factors. Specifically, four different spatiotemporal attention-based sequence to sequence modeling frameworks using Convolutional Long Short-Term Memory (ConvLSTM) networks are proposed to account for learning local to global and long temporal-range spatial relationships while modeling the event progression dynamics in space-time. With the very high spatiotemporal resolution wildfire spread simulation based on a cellular automata-based percolation model, effectiveness of the proposed approaches are investigated for accurate prediction and meaningful biophysical interpretations. Results suggest that attention-based modeling approaches are superior in predicting wildfire locations and with fire-ecologically meaningful physical interpretations, as validated based on the known fire spread-biophysical dynamics in the percolation model data. The dissertation offers novel methodological contributions toward developing spatially and spatiotemporally explicit GeoAI modeling approaches within the spatial data science domain, that can be used by a range of geospatial application domains.
Download or read book Handbook of Geospatial Artificial Intelligence written by Song Gao and published by CRC Press. This book was released on 2023-12-29 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive handbook covers Geospatial Artificial Intelligence (GeoAI), which is the integration of geospatial studies and AI machine (deep) learning and knowledge graph technologies. It explains key fundamental concepts, methods, models, and technologies of GeoAI, and discusses the recent advances, research tools, and applications that range from environmental observation and social sensing to natural disaster responses. As the first single volume on this fast-emerging domain, Handbook of Geospatial Artificial Intelligence is an excellent resource for educators, students, researchers, and practitioners utilizing GeoAI in fields such as information science, environment and natural resources, geosciences, and geography. Features Provides systematic introductions and discussions of GeoAI theory, methods, technologies, applications, and future perspectives Covers a wide range of GeoAI applications and case studies in practice Offers supplementary materials such as data, programming code, tools, and case studies Discusses the recent developments of GeoAI methods and tools Includes contributions written by top experts in cutting-edge GeoAI topics This book is intended for upper-level undergraduate and graduate students from different disciplines and those taking GIS courses in geography or computer sciences as well as software engineers, geospatial industry engineers, GIS professionals in non-governmental organizations, and federal/state agencies who use GIS and want to learn more about GeoAI advances and applications.
Download or read book Time Integrative Geographic Information Systems written by Thomas Ott and published by Springer Science & Business Media. This book was released on 2001-02-27 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: CD-ROM contains: Examples and code from text.
Download or read book Theories and Methods of Spatio temporal Reasoning in Geographic Space written by Andrew U. Frank and published by Springer. This book was released on 1992 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This volume collects the papers presented at the first international conference dedicated to spatial and temporal reasoning in geographic space, entitled "GIS: from space to territory - theories and methods of spatio-temporal reasoning". Within the National Center for Geographic Information and Analysis (NCGIA, one of the supporters of the conference) the importance of spatial and temporal reasoning was recognized several years ago. Initial research found that spatial reasoning in geographic or large-scale space is different from spatial reasoning in small-scale space, as usually dealt with in robotics and expertsystems. Temporal reasoning has attracted interest in the artificial intelligence community. The volume also includes two invited papers: "Do people understand spatial concepts: the case of first-order primtives" by R.G. Golledge, and "Temporal databases" by R.T. Snodgrass."--PUBLISHER'S WEBSITE.
Download or read book Artificial Intelligence in Earth Science written by Ziheng Sun and published by Elsevier. This book was released on 2023-04-27 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence in Earth Science: Best Practices and Fundamental Challenges provides a comprehensive, step-by-step guide to AI workflows for solving problems in Earth Science. The book focuses on the most challenging problems in applying AI in Earth system sciences, such as training data preparation, model selection, hyperparameter tuning, model structure optimization, spatiotemporal generalization, transforming model results into products, and explaining trained models. In addition, it provides full-stack workflow tutorials to help walk readers through the whole process, regardless of previous AI experience. The book tackles the complexity of Earth system problems in AI engineering, fully guiding geoscientists who are planning to implement AI in their daily work. Provides practical, step-by-step guides for Earth Scientists who are interested in implementing AI techniques in their work Features case studies to show real-world examples of techniques described in the book Includes additional elements to help readers who are new to AI, including end-of-chapter, key concept bulleted lists that concisely cover key concepts in the chapter
Download or read book Event Oriented Approaches in Geographic Information Science written by Kathleen Hornsby and published by Psychology Press. This book was released on 2004 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: This special issue originated from a workshop held in Holden, Maine in November 2002 on the topic of event-oriented approaches for geographic information science. Following the workshop, a call for papers was distributed, resulting in nine papers being submitted for review. Four of these papers appear in this special issue and cover: *events performed by humans from the psychological perspective; *information services that must guide users through a set of decision points that are based on ontologies that typically do not capture dynamic aspects, such as events and actions; *"multiaspect" phenomena, such as floods and wildfires, that are not adequately and separately describable either as dynamic objects or as spatiotemporal fields; and *the foundations for ontologies of the dynamic world in which snapshot views of the world at a single time and happenings over time have an equal but complementary status.
Download or read book Artificial Intelligence in Geography written by Stan Openshaw and published by John Wiley & Sons. This book was released on 1997-07-07 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique work introduces the basic principles of artificial intelligence with applications in geographical teaching and research, GIS, and planning. Written in an accessible, non-technical and witty style, this book marks the beginning of the Al revolution in geography with major implications for teaching and research. The authors provide an easy to understand basic introduction to Al relevant to geography. There are no special mathematical and statistical skills needed, indeed these might well be a hindrance. Al is a different way of looking at the world and it requires a willingness to experiment, and readers who are unhindered by the baggage of obsolete technologies and outmoded philosophies of science will probably do best. The text provides an introduction to expert systems, neural nets, genetic algorithms, smart systems and artificial life and shows how they are likely to transform geographical enquiry. A major methodological milestone in geography The first geographical book on artificial intelligence (Al) No need for previous mathematical or statistical skills/knowledge Accessible style makes a difficult subject available to a wide audience Stan Openshaw is one of the world? s leading researchers into geographical computing, spatial analysis and GIS.
Download or read book Advances in Spatio Temporal Analysis written by Xinming Tang and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Developments in Geographic Information Technology have raised the expectations of users. A static map is no longer enough; there is now demand for a dynamic representation. Time is of great importance when operating on real world geographical phenomena, especially when these are dynamic. Researchers in the field of Temporal Geographical Information Systems (TGIS) have been developing methods of incorporating time into geographical information systems. Spatio-temporal analysis embodies spatial modelling, spatio-temporal modelling and spatial reasoning and data mining. ""Advances in Spatio-Tempo.
Download or read book Computational Movement Analysis written by Patrick Laube and published by Springer. This book was released on 2014-09-12 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This SpringerBrief discusses the characteristics of spatiotemporal movement data, including uncertainty and scale. It investigates three core aspects of Computational Movement Analysis: Conceptual modeling of movement and movement spaces, spatiotemporal analysis methods aiming at a better understanding of movement processes (with a focus on data mining for movement patterns), and using decentralized spatial computing methods in movement analysis. The author presents Computational Movement Analysis as an interdisciplinary umbrella for analyzing movement processes with methods from a range of fields including GIScience, spatiotemporal databases and data mining. Key challenges in Computational Movement Analysis include bridging the semantic gap, privacy issues when movement data involves people, incorporating big and open data, and opportunities for decentralized movement analysis arising from the internet of things. The interdisciplinary concepts of Computational Movement Analysis make this an important book for professionals and students in computer science, geographic information science and its application areas, especially movement ecology and transportation research.
Download or read book Encyclopedia of GIS written by Shashi Shekhar and published by Springer Science & Business Media. This book was released on 2007-12-12 with total page 1392 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Encyclopedia of GIS provides a comprehensive and authoritative guide, contributed by experts and peer-reviewed for accuracy, and alphabetically arranged for convenient access. The entries explain key software and processes used by geographers and computational scientists. Major overviews are provided for nearly 200 topics: Geoinformatics, Spatial Cognition, and Location-Based Services and more. Shorter entries define specific terms and concepts. The reference will be published as a print volume with abundant black and white art, and simultaneously as an XML online reference with hyperlinked citations, cross-references, four-color art, links to web-based maps, and other interactive features.
Download or read book Knowledge Discovery from Sensor Data written by Mohamed Medhat Gaber and published by Springer. This book was released on 2010-04-07 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains thoroughly refereed extended papers from the Second International Workshop on Knowledge Discovery from Sensor Data, Sensor-KDD 2008, held in Las Vegas, NV, USA, in August 2008. The 12 revised papers presented together with an invited paper were carefully reviewed and selected from numerous submissions. The papers feature important aspects of knowledge discovery from sensor data, e.g., data mining for diagnostic debugging; incremental histogram distribution for change detection; situation-aware adaptive visualization; WiFi mining; mobile sensor data mining; incremental anomaly detection; and spatiotemporal neighborhood discovery for sensor data.
Download or read book Applied Spatial Statistics and Econometrics written by Katarzyna Kopczewska and published by Routledge. This book was released on 2020-11-25 with total page 725 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is a comprehensive introduction to applied spatial data analysis using R. Each chapter walks the reader through a different method, explaining how to interpret the results and what conclusions can be drawn. The author team showcases key topics, including unsupervised learning, causal inference, spatial weight matrices, spatial econometrics, heterogeneity and bootstrapping. It is accompanied by a suite of data and R code on Github to help readers practise techniques via replication and exercises. This text will be a valuable resource for advanced students of econometrics, spatial planning and regional science. It will also be suitable for researchers and data scientists working with spatial data.
Download or read book Perspectives on Spatial Data Analysis written by Luc Anselin and published by Springer Science & Business Media. This book was released on 2009-12-24 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial data analysis has seen explosive growth in recent years. Both in mainstream statistics and econometrics as well as in many applied ?elds, the attention to space, location, and interaction has become an important feature of scholarly work. The methodsdevelopedto dealwith problemsofspatialpatternrecognition,spatialau- correlation, and spatial heterogeneity have seen greatly increased adoption, in part due to the availability of user friendlydesktopsoftware. Throughhis theoretical and appliedwork,ArthurGetishasbeena majorcontributing?gureinthisdevelopment. In this volume, we take both a retrospective and a prospective view of the ?eld. We use the occasion of the retirement and move to emeritus status of Arthur Getis to highlight the contributions of his work. In addition, we aim to place it into perspective in light of the current state of the art and future directions in spatial data analysis. To this end, we elected to combine reprints of selected classic contributions by Getiswithchapterswrittenbykeyspatialscientists.Thesescholarswerespeci?cally invited to react to the earlier work by Getis with an eye toward assessing its impact, tracing out the evolution of related research, and to re?ect on the future broadening of spatial analysis. The organizationof the book follows four main themes in Getis’ contributions: • Spatial analysis • Pattern analysis • Local statistics • Applications For each of these themes, the chapters provide a historical perspective on early methodological developments and theoretical insights, assessments of these c- tributions in light of the current state of the art, as well as descriptions of new techniques and applications.
Download or read book Analysis of Urban Growth and Sprawl from Remote Sensing Data written by Basudeb Bhatta and published by Springer Science & Business Media. This book was released on 2010-03-03 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive discussion on urban growth and sprawl, and how they can be analyzed using remote sensing imageries. It compiles views of numerous researchers that help in understanding the urban growth and sprawl; their patterns, process, causes, consequences, and countermeasures; how remote sensing data and geographic information system techniques can be used in mapping, monitoring, measuring, analyzing, and simulating the urban growth and sprawl and what are the merits and demerits of available methods and models. This book will be of value for the scientists and researchers engaged in urban geographic research, especially using remote sensing imageries. This book will serve as a rigours literature review for them. Post graduate students of urban geography or urban/regional planning may refer this book as additional studies. This book may help the academicians for preparing lecture notes and delivering lectures. Industry professionals may also be benefited from the discussed methods and models along with numerous citations.
Download or read book Spatio Temporal Statistics with R written by Christopher K. Wikle and published by CRC Press. This book was released on 2019-02-18 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: The world is becoming increasingly complex, with larger quantities of data available to be analyzed. It so happens that much of these "big data" that are available are spatio-temporal in nature, meaning that they can be indexed by their spatial locations and time stamps. Spatio-Temporal Statistics with R provides an accessible introduction to statistical analysis of spatio-temporal data, with hands-on applications of the statistical methods using R Labs found at the end of each chapter. The book: Gives a step-by-step approach to analyzing spatio-temporal data, starting with visualization, then statistical modelling, with an emphasis on hierarchical statistical models and basis function expansions, and finishing with model evaluation Provides a gradual entry to the methodological aspects of spatio-temporal statistics Provides broad coverage of using R as well as "R Tips" throughout. Features detailed examples and applications in end-of-chapter Labs Features "Technical Notes" throughout to provide additional technical detail where relevant Supplemented by a website featuring the associated R package, data, reviews, errata, a discussion forum, and more The book fills a void in the literature and available software, providing a bridge for students and researchers alike who wish to learn the basics of spatio-temporal statistics. It is written in an informal style and functions as a down-to-earth introduction to the subject. Any reader familiar with calculus-based probability and statistics, and who is comfortable with basic matrix-algebra representations of statistical models, would find this book easy to follow. The goal is to give as many people as possible the tools and confidence to analyze spatio-temporal data.
Download or read book Urban Computing written by Yu Zheng and published by MIT Press. This book was released on 2019-02-05 with total page 633 pages. Available in PDF, EPUB and Kindle. Book excerpt: An authoritative treatment of urban computing, offering an overview of the field, fundamental techniques, advanced models, and novel applications. Urban computing brings powerful computational techniques to bear on such urban challenges as pollution, energy consumption, and traffic congestion. Using today's large-scale computing infrastructure and data gathered from sensing technologies, urban computing combines computer science with urban planning, transportation, environmental science, sociology, and other areas of urban studies, tackling specific problems with concrete methodologies in a data-centric computing framework. This authoritative treatment of urban computing offers an overview of the field, fundamental techniques, advanced models, and novel applications. Each chapter acts as a tutorial that introduces readers to an important aspect of urban computing, with references to relevant research. The book outlines key concepts, sources of data, and typical applications; describes four paradigms of urban sensing in sensor-centric and human-centric categories; introduces data management for spatial and spatio-temporal data, from basic indexing and retrieval algorithms to cloud computing platforms; and covers beginning and advanced topics in mining knowledge from urban big data, beginning with fundamental data mining algorithms and progressing to advanced machine learning techniques. Urban Computing provides students, researchers, and application developers with an essential handbook to an evolving interdisciplinary field.
Download or read book Explainable AI Interpreting Explaining and Visualizing Deep Learning written by Wojciech Samek and published by Springer Nature. This book was released on 2019-09-10 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner. The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.
