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Gis And Machine Learning For Small Area Classifications In Developing Countries
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Book Synopsis GIS and Machine Learning for Small Area Classifications in Developing Countries by : Adegbola Ojo
Download or read book GIS and Machine Learning for Small Area Classifications in Developing Countries written by Adegbola Ojo and published by CRC Press. This book was released on 2020-12-29 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the emergence of contemporary area classifications, population geography has witnessed a renaissance in the area of policy related spatial analysis. Area classifications subsume geodemographic systems which often use data mining techniques and machine learning algorithms to simplify large and complex bodies of information about people and the places in which they live, work and undertake other social activities. Outputs developed from the grouping of small geographical areas on the basis of multi- dimensional data have proved beneficial particularly for decision-making in the commercial sectors of a vast number of countries in the northern hemisphere. This book argues that small area classifications offer countries in the Global South a distinct opportunity to address human population policy related challenges in novel ways using area-based initiatives and evidence-based methods. This book exposes researchers, practitioners, and students to small area segmentation techniques for understanding, interpreting, and visualizing the configuration, dynamics, and correlates of development policy challenges at small spatial scales. It presents strategic and operational responses to these challenges in cost effective ways. Using two developing countries as case studies, the book connects new transdisciplinary ways of thinking about social and spatial inequalities from a scientific perspective with GIS and Data Science. This offers all stakeholders a framework for engaging in practical dialogue on development policy within urban and rural settings, based on real-world examples. Features: The first book to address the huge potential of small area segmentation for sustainable development, combining explanations of concepts, a range of techniques, and current applications. Includes case studies focused on core challenges that confront developing countries and provides thorough analytical appraisal of issues that resonate with audiences from the Global South. Combines GIS and machine learning methods for studying interrelated disciplines such as Demography, Urban Science, Sociology, Statistics, Sustainable Development and Public Policy. Uses a multi-method approach and analytical techniques of primary and secondary data. Embraces a balanced, chronological, and well sequenced presentation of information, which is very practical for readers.
Book Synopsis GIS and Machine Learning for Small Area Classifications in Developing Countries by : Adegbola Ojo
Download or read book GIS and Machine Learning for Small Area Classifications in Developing Countries written by Adegbola Ojo and published by CRC Press. This book was released on 2020-12-30 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the emergence of contemporary area classifications, population geography has witnessed a renaissance in the area of policy related spatial analysis. Area classifications subsume geodemographic systems which often use data mining techniques and machine learning algorithms to simplify large and complex bodies of information about people and the places in which they live, work and undertake other social activities. Outputs developed from the grouping of small geographical areas on the basis of multi- dimensional data have proved beneficial particularly for decision-making in the commercial sectors of a vast number of countries in the northern hemisphere. This book argues that small area classifications offer countries in the Global South a distinct opportunity to address human population policy related challenges in novel ways using area-based initiatives and evidence-based methods. This book exposes researchers, practitioners, and students to small area segmentation techniques for understanding, interpreting, and visualizing the configuration, dynamics, and correlates of development policy challenges at small spatial scales. It presents strategic and operational responses to these challenges in cost effective ways. Using two developing countries as case studies, the book connects new transdisciplinary ways of thinking about social and spatial inequalities from a scientific perspective with GIS and Data Science. This offers all stakeholders a framework for engaging in practical dialogue on development policy within urban and rural settings, based on real-world examples. Features: The first book to address the huge potential of small area segmentation for sustainable development, combining explanations of concepts, a range of techniques, and current applications. Includes case studies focused on core challenges that confront developing countries and provides thorough analytical appraisal of issues that resonate with audiences from the Global South. Combines GIS and machine learning methods for studying interrelated disciplines such as Demography, Urban Science, Sociology, Statistics, Sustainable Development and Public Policy. Uses a multi-method approach and analytical techniques of primary and secondary data. Embraces a balanced, chronological, and well sequenced presentation of information, which is very practical for readers.
Book Synopsis Machine Learning for Spatial Environmental Data by : Mikhail Kanevski
Download or read book Machine Learning for Spatial Environmental Data written by Mikhail Kanevski and published by CRC Press. This book was released on 2009-06-09 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses machine learning algorithms, such as artificial neural networks of different architectures, statistical learning theory, and Support Vector Machines used for the classification and mapping of spatially distributed data. It presents basic geostatistical algorithms as well. The authors describe new trends in machine learning and their application to spatial data. The text also includes real case studies based on environmental and pollution data. It includes a CD-ROM with software that will allow both students and researchers to put the concepts to practice.
Book Synopsis Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing by : Hyung-Sup Jung
Download or read book Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing written by Hyung-Sup Jung and published by MDPI. This book was released on 2019-09-03 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: As computer and space technologies have been developed, geoscience information systems (GIS) and remote sensing (RS) technologies, which deal with the geospatial information, have been rapidly maturing. Moreover, over the last few decades, machine learning techniques including artificial neural network (ANN), deep learning, decision tree, and support vector machine (SVM) have been successfully applied to geospatial science and engineering research fields. The machine learning techniques have been widely applied to GIS and RS research fields and have recently produced valuable results in the areas of geoscience, environment, natural hazards, and natural resources. This book is a collection representing novel contributions detailing machine learning techniques as applied to geoscience information systems and remote sensing.
Book Synopsis New Thinking in GIScience by : Bin Li
Download or read book New Thinking in GIScience written by Bin Li and published by Springer Nature. This book was released on 2022-06-30 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of seminal position essays by leading researchers on new development in Geographic Information Sciences (GIScience), covering a wide range of topics and representing a variety of perspectives. The authors propose enrichments and extensions to the conceptual framework of GIScience; discuss a series of transformational methodologies and technologies for analysis and modeling; elaborate on key issues in innovative approaches to data acquisition and integration, across earth sensing to social sensing; and outline frontiers in application domains, spanning from natural science to humanities and social science, e.g., urban science, land use and planning, social governance, transportation, crime, and public health, just name a few. The book provides an overview of the strategic directions on GIScience research and development. It will benefit researchers and practitioners in the field who are seeking a high-level reference regarding those directions.
Book Synopsis GIS and Spatial Analysis by : Jorge Rocha
Download or read book GIS and Spatial Analysis written by Jorge Rocha and published by BoD – Books on Demand. This book was released on 2023-07-12 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of spatial analysis techniques is to describe the patterns existing in spatial data and to establish, preferably quantitatively, the relationships between different geographic variables. The notion of spatial analysis in a Geographic Information Systems (GIS) environment encompasses the idea of integrating spatial data and alphanumeric attributes and translating it into a series of functions related to selection and data search, on the one hand, and with modeling, on the other. There have been substantial advances in spatial analysis techniques in GIS, mainly in the form of more faithfully apprehending the relationships inherent to the geographic phenomenon, something that was proven impossible to do with non-spatial techniques. Nowadays, spatial analysis involves a set of techniques used to analyze and model variables with distribution in space and/or time. The new era of spatial analysis must also consider the possibilities of integrating artificial intelligence in simulation (geosimulation) processes in computerized environments (geocomputation) in close relationship with models developed in real situations. GIS have emerged as useful tools in geographic modeling processes, helping to answer questions about the time variability of the landscape structure, study the behavior of fire, predict areas of urban expansion, analyze propagation phenomena, model animal movement and behavior, and determine periods and areas of high risk of flooding, among other phenomena. GIS and Spatial Analysis is a critical book that provides different methodologies that combine the potential data (including Big Data) analysis with GIS applications. It gives readers a comprehensive overview of the current state-of-the-art methods of spatial analysis, focusing both on the new philosophical and theoretical foundations for spatial analysis and on a flexible framework for analysis in the real world, for problems such as complexity and uncertainty.
Book Synopsis Remote Sensing Intelligent Interpretation for Mine Geological Environment by : Weitao Chen
Download or read book Remote Sensing Intelligent Interpretation for Mine Geological Environment written by Weitao Chen and published by Springer. This book was released on 2023-08-20 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the theory and methods of remote sensing intelligent interpretation based on deep learning. Based on geological and environmental effects on mines, this book constructs a set of systematic mine remote sensing datasets focusing on the multi-level task with the system of “target detection→scene classification→semantic segmentation." Taking China’s Hubei Province as an example, this book focuses on the following four aspects: 1. Development of a multiscale remote sensing dataset of the mining area, including mine target remote sensing dataset, mine (including non-mine areas) remote sensing scene dataset, and semantic segmentation remote sensing dataset of mining land cover. The three datasets are the basis of intelligent interpretation based on deep learning. 2. Research on mine target remote sensing detection method based on deep learning. 3. Research on remote sensing scene classification method of mine and non-mine areas based on deep learning. 4. Research on the fine-scale classification method of mining land cover based on semantic segmentation. The book is a valuable reference both for scholars, practitioners and as well as graduate students who are interested in mining environment research.
Book Synopsis Introduction to Small Area Estimation Techniques by : Asian Development Bank
Download or read book Introduction to Small Area Estimation Techniques written by Asian Development Bank and published by Asian Development Bank. This book was released on 2020-05-01 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: This guide to small area estimation aims to help users compile more reliable granular or disaggregated data in cost-effective ways. It explains small area estimation techniques with examples of how the easily accessible R analytical platform can be used to implement them, particularly to estimate indicators on poverty, employment, and health outcomes. The guide is intended for staff of national statistics offices and for other development practitioners. It aims to help them to develop and implement targeted socioeconomic policies to ensure that the vulnerable segments of societies are not left behind, and to monitor progress toward the Sustainable Development Goals.
Book Synopsis Classification Methods for Remotely Sensed Data by : Paul Mather
Download or read book Classification Methods for Remotely Sensed Data written by Paul Mather and published by CRC Press. This book was released on 2001-12-06 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remote sensing is an integral part of geography, GIS and cartography, used by academics in the field and professionals in all sorts of occupations. The 1990s saw the development of a range of new methods of classifying remote sensing images and data, both optical imaging and microwave imaging. This comprehensive survey of the various techniques pulls together information from a range of sources and sets it in the context of the basic principles. There is an emphasis on new methods, including neural networks (especially artificial neural networks), fuzzy theory, texture and quantization, and the use of Markov random fields. Students in GIS and remote sensing should find this an essential read when learning about and dealing with new developments in the field. It is concise and accessible and the authors conclude with coverage of the state-of-the-art topics of multisource data analysis, evidential reasoning and genetic algorithms. Including a full color section and basic remote sensing theory, this book will prove invaluable for advanced undergraduate students and graduates/researchers in the field. There is very little published in this field yet, and there is distinct need for such an analysis of this fast-growing area.
Book Synopsis Remote Sensing Image Classification in R by : Courage Kamusoko
Download or read book Remote Sensing Image Classification in R written by Courage Kamusoko and published by . This book was released on 2019 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an introduction to remotely sensed image processing and classification in R using machine learning algorithms. It also provides a concise and practical reference tutorial, which equips readers to immediately start using the software platform and R packages for image processing and classification. This book is divided into five chapters. Chapter 1 introduces remote sensing digital image processing in R, while chapter 2 covers pre-processing. Chapter 3 focuses on image transformation, and chapter 4 addresses image classification. Lastly, chapter 5 deals with improving image classification. R is advantageous in that it is open source software, available free of charge and includes several useful features that are not available in commercial software packages. This book benefits all undergraduate and graduate students, researchers, university teachers and other remote- sensing practitioners interested in the practical implementation of remote sensing in R.
Book Synopsis Classification Methods for Remotely Sensed Data by : Paul Mather
Download or read book Classification Methods for Remotely Sensed Data written by Paul Mather and published by CRC Press. This book was released on 2001-12-06 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remote sensing is an integral part of geography, GIS and cartography, used by academics in the field and professionals in all sorts of occupations. The 1990s saw the development of a range of new methods of classifying remote sensing images and data, both optical imaging and microwave imaging. This comprehensive survey of the various techniques pul
Book Synopsis Key Concepts and Techniques in GIS by : Jochen Albrecht
Download or read book Key Concepts and Techniques in GIS written by Jochen Albrecht and published by SAGE. This book was released on 2007-08-20 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: Key Concepts and Techniques in GIS is a concise overview of the fundamental ideas that inform geographic information science. It provides detailed descriptions of the concepts and techniques that anyone using GIS software must fully understand to analyse spatial data. Short and clearly focussed chapters provide explanations of: spatial relationships and spatial data the creation of digital data, the use and access of existing data, the combination of data the use of modelling techniques and the essential functions of map algebra spatial statistics and spatial analysis geocomputation - including discussion of neural networks, cellular automata, and agent-based modelling Illustrated throughout with explanatory figures, the text also includes a glossary, cross referenced to discussion in the text. Written very much from a user′s perspective, Key Concepts and Techniques in GIS is highly readable refresher course for intermediate level students and practitioners of GIS in the social and the natural sciences.
Book Synopsis Object-Based Image Analysis by : Thomas Blaschke
Download or read book Object-Based Image Analysis written by Thomas Blaschke and published by Springer Science & Business Media. This book was released on 2008-08-09 with total page 804 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together a collection of invited interdisciplinary persp- tives on the recent topic of Object-based Image Analysis (OBIA). Its c- st tent is based on select papers from the 1 OBIA International Conference held in Salzburg in July 2006, and is enriched by several invited chapters. All submissions have passed through a blind peer-review process resulting in what we believe is a timely volume of the highest scientific, theoretical and technical standards. The concept of OBIA first gained widespread interest within the GIScience (Geographic Information Science) community circa 2000, with the advent of the first commercial software for what was then termed ‘obje- oriented image analysis’. However, it is widely agreed that OBIA builds on older segmentation, edge-detection and classification concepts that have been used in remote sensing image analysis for several decades. Nevert- less, its emergence has provided a new critical bridge to spatial concepts applied in multiscale landscape analysis, Geographic Information Systems (GIS) and the synergy between image-objects and their radiometric char- teristics and analyses in Earth Observation data (EO).
Book Synopsis Google Earth Engine Applications by : Lalit Kumar
Download or read book Google Earth Engine Applications written by Lalit Kumar and published by MDPI. This book was released on 2019-04-23 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a rapidly changing world, there is an ever-increasing need to monitor the Earth’s resources and manage it sustainably for future generations. Earth observation from satellites is critical to provide information required for informed and timely decision making in this regard. Satellite-based earth observation has advanced rapidly over the last 50 years, and there is a plethora of satellite sensors imaging the Earth at finer spatial and spectral resolutions as well as high temporal resolutions. The amount of data available for any single location on the Earth is now at the petabyte-scale. An ever-increasing capacity and computing power is needed to handle such large datasets. The Google Earth Engine (GEE) is a cloud-based computing platform that was established by Google to support such data processing. This facility allows for the storage, processing and analysis of spatial data using centralized high-power computing resources, allowing scientists, researchers, hobbyists and anyone else interested in such fields to mine this data and understand the changes occurring on the Earth’s surface. This book presents research that applies the Google Earth Engine in mining, storing, retrieving and processing spatial data for a variety of applications that include vegetation monitoring, cropland mapping, ecosystem assessment, and gross primary productivity, among others. Datasets used range from coarse spatial resolution data, such as MODIS, to medium resolution datasets (Worldview -2), and the studies cover the entire globe at varying spatial and temporal scales.
Book Synopsis GIS and the 2020 Census by : Amor Laaribi
Download or read book GIS and the 2020 Census written by Amor Laaribi and published by Esri Press. This book was released on 2018-07-13 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Census workers need to capture and analyze information at the finest geographic level with mobile and geospatial-based technology. GIS and the 2020 Census: Modernizing Official Statistics provides statistical organizations with the most recent GIS methodologies and technological tools to support census workers' needs at all the stages of a census. Learn how to plan and carry out census work with GIS using new technologies for field data collection and operations management. After planning and collecting data, apply innovative solutions for performing statistical analysis, data integration and dissemination. Additional topics cover cloud computing, big data, Location as a Service (LaaS), and emerging data sources. While GIS and the 2020 Census focuses on using GIS and other geospatial technology in support of census planning and operations, it also offers guidelines for building a statistical-geospatial information infrastructure in support of the 2020 Round of Censuses, evidence-based decision making, and sustainable development. Case studies illustrate concepts in practice.
Book Synopsis Geographic Information Systems in Geospatial Intelligence by : Rustam B. Rustamov
Download or read book Geographic Information Systems in Geospatial Intelligence written by Rustam B. Rustamov and published by BoD – Books on Demand. This book was released on 2020 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: Earth observation systems, by use of space science and technology advances, present a large-scale opportunity for applying remote sensing methods with geographical information system (GIS) developments. Integrating these two methods makes it possible to achieve high-accuracy satellite data processing. This book considers aspects of GIS technology applications with space science technology and innovation approaches. It examines the potential of Earth observation satellite systems as well as existing challenges and problems in the field. Chapters cover topics such as RGB-D sensors for autonomous pothole detection, machine learning in GIS, interferometric synthetic aperture radar (InSAR) modeling, and others.
Book Synopsis Theory and Practice of Business Intelligence in Healthcare by : Khuntia, Jiban
Download or read book Theory and Practice of Business Intelligence in Healthcare written by Khuntia, Jiban and published by IGI Global. This book was released on 2019-12-27 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Business intelligence supports managers in enterprises to make informed business decisions in various levels and domains such as in healthcare. These technologies can handle large structured and unstructured data (big data) in the healthcare industry. Because of the complex nature of healthcare data and the significant impact of healthcare data analysis, it is important to understand both the theories and practices of business intelligence in healthcare. Theory and Practice of Business Intelligence in Healthcare is a collection of innovative research that introduces data mining, modeling, and analytic techniques to health and healthcare data; articulates the value of big volumes of data to health and healthcare; evaluates business intelligence tools; and explores business intelligence use and applications in healthcare. While highlighting topics including digital health, operations intelligence, and patient empowerment, this book is ideally designed for healthcare professionals, IT consultants, hospital directors, data management staff, data analysts, hospital administrators, executives, managers, academicians, students, and researchers seeking current research on the digitization of health records and health systems integration.
