geospatial analysis

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Geospatial Analysis

Author : Michael John De Smith
ISBN : 9781905886609
Genre : Mathematics
File Size : 80. 30 MB
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Addresses a range of analytical techniques that are provided within modern Geographic Information Systems and related geospatial software products. This guide covers: the principal concepts of geospatial analysis; core components of geospatial analysis; and, surface analysis, including surface form analysis, gridding and interpolation methods.

Progress In Geospatial Analysis

Author : Yuji Murayama
ISBN : 9784431540007
Genre : Science
File Size : 57. 90 MB
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This book examines current trends and developments in the methods and applications of geospatial analysis and highlights future development prospects. It provides a comprehensive discussion of remote sensing- and geographical information system (GIS)-based data processing techniques, current practices, theories, models, and applications of geospatial analysis. Data acquisition and processing techniques such as remote sensing image selections, classifications, accuracy assessments, models of GIS data, and spatial modeling processes are the focus of the first part of the book. In the second part, theories and methods related to fuzzy sets, spatial weights and prominence, geographically weighted regression, weight of evidence, Markov-cellular automata, artificial neural network, agent-based simulation, multi-criteria evaluation, analytic hierarchy process, and a GIS network model are included. Part three presents selected best practices in geospatial analysis. The chapters, all by expert authors, are arranged so that readers who are new to the field will gain an overview and important insights. Those readers who are already practitioners will gain from the advanced and updated materials and state-of-the-art developments in geospatial analysis.

Learning R For Geospatial Analysis

Author : Michael Dorman
ISBN : 9781783984374
Genre : Computers
File Size : 33. 73 MB
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This book is intended for anyone who wants to learn how to efficiently analyze geospatial data with R, including GIS analysts, researchers, educators, and students who work with spatial data and who are interested in expanding their capabilities through programming. The book assumes familiarity with the basic geographic information concepts (such as spatial coordinates), but no prior experience with R and/or programming is required. By focusing on R exclusively, you will not need to depend on any external software—a working installation of R is all that is necessary to begin.

Geospatial Analysis Of Environmental Health

Author : Juliana A. Maantay
ISBN : 9400703295
Genre : Medical
File Size : 21. 65 MB
Format : PDF, ePub
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This book focuses on a range of geospatial applications for environmental health research, including environmental justice issues, environmental health disparities, air and water contamination, and infectious diseases. Environmental health research is at an exciting point in its use of geotechnologies, and many researchers are working on innovative approaches. This book is a timely scholarly contribution in updating the key concepts and applications of using GIS and other geospatial methods for environmental health research. Each chapter contains original research which utilizes a geotechnical tool (Geographic Information Systems (GIS), remote sensing, GPS, etc.) to address an environmental health problem. The book is divided into three sections organized around the following themes: issues in GIS and environmental health research; using GIS to assess environmental health impacts; and geospatial methods for environmental health. Representing diverse case studies and geospatial methods, the book is likely to be of interest to researchers, practitioners and students across the geographic and environmental health sciences. The authors are leading researchers and practitioners in the field of GIS and environmental health.

Geospatial Analysis And Modelling Of Urban Structure And Dynamics

Author : Bin Jiang
ISBN : 9048185726
Genre : Science
File Size : 62. 77 MB
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A Coming of Age: Geospatial Analysis and Modelling in the Early Twenty First Century Forty years ago when spatial analysis first emerged as a distinct theme within geography’s quantitative revolution, the focus was largely on consistent methods for measuring spatial correlation. The concept of spatial au- correlation took pride of place, mirroring concerns in time-series analysis about similar kinds of dependence known to distort the standard probability theory used to derive appropriate statistics. Early applications of spatial correlation tended to reflect geographical patterns expressed as points. The perspective taken on such analytical thinking was founded on induction, the search for pattern in data with a view to suggesting appropriate hypotheses which could subsequently be tested. In parallel but using very different techniques came the development of a more deductive style of analysis based on modelling and thence simulation. Here the focus was on translating prior theory into forms for generating testable predictions whose outcomes could be compared with observations about some system or phenomenon of interest. In the intervening years, spatial analysis has broadened to embrace both inductive and deductive approaches, often combining both in different mixes for the variety of problems to which it is now applied.

Python Geospatial Analysis Cookbook

Author : Michael Diener
ISBN : 9781783555086
Genre : Computers
File Size : 63. 91 MB
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Over 60 recipes to work with topology, overlays, indoor routing, and web application analysis with Python About This Book Explore the practical process of using geospatial analysis to solve simple to complex problems with reusable recipes Concise step-by-step instructions to teach you about projections, vector, raster, overlay, indoor routing and topology analysis Create a basic indoor routing application with geodjango Who This Book Is For If you are a student, teacher, programmer, geospatial or IT administrator, GIS analyst, researcher, or scientist looking to do spatial analysis, then this book is for you. Anyone trying to answer simple to complex spatial analysis questions will get a working demonstration of the power of Python with real-world data. Some of you may be beginners with GIS, but most of you will probably have a basic understanding of geospatial analysis and programming. What You Will Learn Discover the projection and coordinate system information of your data and learn how to transform that data into different projections Import or export your data into different data formats to prepare it for your application or spatial analysis Use the power of PostGIS with Python to take advantage of the powerful analysis functions Execute spatial analysis functions on vector data including clipping, spatial joins, measuring distances, areas, and combining data to new results Create your own set of topology rules to perform and ensure quality assurance rules in Python Find the shortest indoor path with network analysis functions in easy, extensible recipes revolving around all kinds of network analysis problems Visualize your data on a map using the visualization tools and methods available to create visually stunning results Build an indoor routing web application with GeoDjango to include your spatial analysis tools built from the previous recipes In Detail Geospatial development links your data to places on the Earth's surface. Its analysis is used in almost every industry to answer location type questions. Combined with the power of the Python programming language, which is becoming the de facto spatial scripting choice for developers and analysts worldwide, this technology will help you to solve real-world spatial problems. This book begins by tackling the installation of the necessary software dependencies and libraries needed to perform spatial analysis with Python. From there, the next logical step is to prepare our data for analysis; we will do this by building up our tool box to deal with data preparation, transformations, and projections. Now that our data is ready for analysis, we will tackle the most common analysis methods for vector and raster data. To check or validate our results, we will explore how to use topology checks to ensure top-quality results. This is followed with network routing analysis focused on constructing indoor routes within buildings, over different levels. Finally, we put several recipes together in a GeoDjango web application that demonstrates a working indoor routing spatial analysis application. The round trip will provide you all the pieces you need to accomplish your own spatial analysis application to suit your requirements. Style and approach Easy-to-follow, step-by-step recipes, explaining from start to finish how to accomplish real-world tasks.

Mastering Geospatial Analysis With Python

Author : Silas Toms
ISBN : 9781788293815
Genre : Computers
File Size : 35. 9 MB
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Explore GIS processing and learn to work with various tools and libraries in Python. Key Features Analyze and process geospatial data using Python libraries such as; Anaconda, GeoPandas Leverage new ArcGIS API to process geospatial data for the cloud. Explore various Python geospatial web and machine learning frameworks. Book Description Python comes with a host of open source libraries and tools that help you work on professional geoprocessing tasks without investing in expensive tools. This book will introduce Python developers, both new and experienced, to a variety of new code libraries that have been developed to perform geospatial analysis, statistical analysis, and data management. This book will use examples and code snippets that will help explain how Python 3 differs from Python 2, and how these new code libraries can be used to solve age-old problems in geospatial analysis. You will begin by understanding what geoprocessing is and explore the tools and libraries that Python 3 offers. You will then learn to use Python code libraries to read and write geospatial data. You will then learn to perform geospatial queries within databases and learn PyQGIS to automate analysis within the QGIS mapping suite. Moving forward, you will explore the newly released ArcGIS API for Python and ArcGIS Online to perform geospatial analysis and create ArcGIS Online web maps. Further, you will deep dive into Python Geospatial web frameworks and learn to create a geospatial REST API. What you will learn Manage code libraries and abstract geospatial analysis techniques using Python 3. Explore popular code libraries that perform specific tasks for geospatial analysis. Utilize code libraries for data conversion, data management, web maps, and REST API creation. Learn techniques related to processing geospatial data in the cloud. Leverage features of Python 3 with geospatial databases such as PostGIS, SQL Server, and SpatiaLite. Who this book is for The audience for this book includes students, developers, and geospatial professionals who need a reference book that covers GIS data management, analysis, and automation techniques with code libraries built in Python 3.

Geospatial Analysis And Data Integration For Cultural Resources Evaluation

Author : Agata Lo Tauro
ISBN : 1407308963
Genre : History
File Size : 53. 15 MB
Format : PDF
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A collection of articles on the use of analytical methods in studies concerning geospatial analysis and data integration for cultural heritage evaluation. This volume is presented as a collection of self-contained articles providing easy access to suit the requirements and interests of individual readers. In order to be self-contained, each article is prefaced by a general introduction which briefly provides the theoretical principles and the general background of the discussed methods or techniques. Contents: 1) Airborne Imaging Technology, DTM and MMS in Natural and Cultural Heritage; 2) Open Source Geospatial Analysis for Cultural Landscape Management; 3) GIS Resources for Ecclesiastic Cultural Heritage Documentation; 4) GIS Prototypes and Thermal Characterization for Regional Landscape Plans and Cultural Heritage Master Plan; 5) Mobile GIS for Colour Calibration Procedures; 6) Data Integration for Cultural Landscape and Resource Efficiency; 7) Non Destructive Testing and GIS for Digital Architectural Heritage; 8) Geo-referencing Techniques and Mapping in Cultural and Natural Heritage Analysis; 9) Data Integration for Survey and Conservation; 10) Geospatial and Hyperspectral MIVIS Data for Environmental Analysis; 11) Airborne Imaging Technology, DTM and MMS in Natural and Cultural Heritage; 12) Mobile Investigator and RS for Heritage Protection: the Fire Risk Assessment; 13) Land Use Analysis Achieved by Hyperspectral Evaluation and In Situ Analysis.

Learning Geospatial Analysis With Python

Author : Joel Lawhead
ISBN : 9781783281145
Genre : Computers
File Size : 37. 23 MB
Format : PDF, Kindle
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This is a tutorial-style book that helps you to perform Geospatial and GIS analysis with Python and its tools/libraries. This book will first introduce various Python-related tools/packages in the initial chapters before moving towards practical usage, examples, and implementation in specialized kinds of Geospatial data analysis.This book is for anyone who wants to understand digital mapping and analysis and who uses Python or another scripting language for automation or crunching data manually.This book primarily targets Python developers, researchers, and analysts who want to perform Geospatial, modeling, and GIS analysis with Python.

Geospatial Analysis To Support Urban Planning In Beijing

Author : Ying Long
ISBN : 9783319193427
Genre : Social Science
File Size : 59. 6 MB
Format : PDF, Kindle
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This book describes a comprehensive framework of novel simulation approaches, conventional urban models, and related data mining techniques that will help develop planning support systems in Beijing as well as other mega-metropolitan areas. It investigates the relationships between human behaviors and spatial patterns in order to simulate activities in an urban space, visualize planning alternatives, and support decision making. The book first explains urban space using geometric patterns, such as points, networks, and polygons, that help identify patterns of household and individual human behavior. Next, it details how novel simulation methodologies, such as cellular automaton and multi-agent systems, and conventional urban modeling, such as spatial interaction models, can be used to identify an optimal or a simulated solution for a better urban form. The book develops a comprehensive land use and transportation integrated model used to explore the spatial patterns of mutual interaction between human mobility and urban space. This model can help forecast the distribution of different types of households, rent prices, and land prices, as well as the distribution of routes and traffic volume based on an appraisal of labor demand and supply. This book shows how geospatial analysis can be a useful tool for planners and decision makers to help in ascertaining patterns of activities and support urban planning. Offering both novel and conventional approaches to urban modeling, it will appeal to researchers, students, and policy makers looking for the optimal way to plan the d evelopment of a mega-metropolitan area.

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